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1.  The Impact of eHealth on the Quality and Safety of Health Care: A Systematic Overview 
PLoS Medicine  2011;8(1):e1000387.
Aziz Sheikh and colleagues report the findings of their systematic overview that assessed the impact of eHealth solutions on the quality and safety of health care.
Background
There is considerable international interest in exploiting the potential of digital solutions to enhance the quality and safety of health care. Implementations of transformative eHealth technologies are underway globally, often at very considerable cost. In order to assess the impact of eHealth solutions on the quality and safety of health care, and to inform policy decisions on eHealth deployments, we undertook a systematic review of systematic reviews assessing the effectiveness and consequences of various eHealth technologies on the quality and safety of care.
Methods and Findings
We developed novel search strategies, conceptual maps of health care quality, safety, and eHealth interventions, and then systematically identified, scrutinised, and synthesised the systematic review literature. Major biomedical databases were searched to identify systematic reviews published between 1997 and 2010. Related theoretical, methodological, and technical material was also reviewed. We identified 53 systematic reviews that focused on assessing the impact of eHealth interventions on the quality and/or safety of health care and 55 supplementary systematic reviews providing relevant supportive information. This systematic review literature was found to be generally of substandard quality with regards to methodology, reporting, and utility. We thematically categorised eHealth technologies into three main areas: (1) storing, managing, and transmission of data; (2) clinical decision support; and (3) facilitating care from a distance. We found that despite support from policymakers, there was relatively little empirical evidence to substantiate many of the claims made in relation to these technologies. Whether the success of those relatively few solutions identified to improve quality and safety would continue if these were deployed beyond the contexts in which they were originally developed, has yet to be established. Importantly, best practice guidelines in effective development and deployment strategies are lacking.
Conclusions
There is a large gap between the postulated and empirically demonstrated benefits of eHealth technologies. In addition, there is a lack of robust research on the risks of implementing these technologies and their cost-effectiveness has yet to be demonstrated, despite being frequently promoted by policymakers and “techno-enthusiasts” as if this was a given. In the light of the paucity of evidence in relation to improvements in patient outcomes, as well as the lack of evidence on their cost-effectiveness, it is vital that future eHealth technologies are evaluated against a comprehensive set of measures, ideally throughout all stages of the technology's life cycle. Such evaluation should be characterised by careful attention to socio-technical factors to maximise the likelihood of successful implementation and adoption.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
There is considerable international interest in exploiting the potential of digital health care solutions, often referred to as eHealth—the use of information and communication technologies—to enhance the quality and safety of health care. Often accompanied by large costs, any large-scale expenditure on eHealth—such as electronic health records, picture archiving and communication systems, ePrescribing, associated computerized provider order entry systems, and computerized decision support systems—has tended to be justified on the grounds that these are efficient and cost-effective means for improving health care. In 2005, the World Health Assembly passed an eHealth resolution (WHA 58.28) that acknowledged, “eHealth is the cost-effective and secure use of information and communications technologies in support of health and health-related fields, including health-care services, health surveillance, health literature, and health education, knowledge and research,” and urged member states to develop and implement eHealth technologies. Since then, implementing eHealth technologies has become a main priority for many countries. For example, England has invested at least £12.8 billion in a National Programme for Information Technology for the National Health Service, and the Obama administration in the United States has committed to a US$38 billion eHealth investment in health care.
Why Was This Study Done?
Despite the wide endorsement of and support for eHealth, the scientific basis of its benefits—which are repeatedly made and often uncritically accepted—remains to be firmly established. A robust evidence-based perspective on the advantages on eHealth could help to suggest priority areas that have the greatest potential for benefit to patients and also to inform international eHealth deliberations on costs. Therefore, in order to better inform the international community, the authors systematically reviewed the published systematic review literature on eHealth technologies and evaluated the impact of these technologies on the quality and safety of health care delivery.
What Did the Researchers Do and Find?
The researchers divided eHealth technologies into three main categories: (1) storing, managing, and transmission of data; (2) clinical decision support; and (3) facilitating care from a distance. Then, implementing methods based on those developed by the Cochrane Collaboration and the NHS Service Delivery and Organisation Programme, the researchers used detailed search strategies and maps of health care quality, safety, and eHealth interventions to identify relevant systematic reviews (and related theoretical, methodological, and technical material) published between 1997 and 2010. Using these techniques, the researchers retrieved a total of 46,349 references from which they identified 108 reviews. The 53 reviews that the researchers finally selected (and critically reviewed) provided the main evidence base for assessing the impact of eHealth technologies in the three categories selected.
In their systematic review of systematic reviews, the researchers included electronic health records and picture archiving communications systems in their evaluation of category 1, computerized provider (or physician) order entry and e-prescribing in category 2, and all clinical information systems that, when used in the context of eHealth technologies, integrate clinical and demographic patient information to support clinician decision making in category 3.
The researchers found that many of the clinical claims made about the most commonly used eHealth technologies were not substantiated by empirical evidence. The evidence base in support of eHealth technologies was weak and inconsistent and importantly, there was insubstantial evidence to support the cost-effectiveness of these technologies. For example, the researchers only found limited evidence that some of the many presumed benefits could be realized; importantly, they also found some evidence that introducing these new technologies may on occasions also generate new risks such as prescribers becoming over-reliant on clinical decision support for e-prescribing, or overestimate its functionality, resulting in decreased practitioner performance.
What Do These Findings Mean?
The researchers found that despite the wide support for eHealth technologies and the frequently made claims by policy makers when constructing business cases to raise funds for large-scale eHealth projects, there is as yet relatively little empirical evidence to substantiate many of the claims made about eHealth technologies. In addition, even for the eHealth technology tools that have proven to be successful, there is little evidence to show that such tools would continue to be successful beyond the contexts in which they were originally developed. Therefore, in light of the lack of evidence in relation to improvements in patient outcomes, as well as the lack of evidence on their cost-effectiveness, the authors say that future eHealth technologies should be evaluated against a comprehensive set of measures, ideally throughout all stages of the technology's life cycle, and include socio-technical factors to maximize the likelihood of successful implementation and adoption in a given context. Furthermore, it is equally important that eHealth projects that have already been commissioned are subject to rigorous, multidisciplinary, and independent evaluation.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000387.
The authors' broader study is: Car J, Black A, Anandan C, Cresswell K, Pagliari C, McKinstry B, et al. (2008) The Impact of eHealth on the Quality and Safety of Healthcare. Available at: http://www.haps.bham.ac.uk/publichealth/cfhep/001.shtml
More information is available on the World Health Assembly eHealth resolution
The World Health Organization provides information at the Global Observatory on eHealth, as well as a global insight into eHealth developments
The European Commission provides Information on eHealth in Europe and some examples of good eHealth practice
More information is provided on NHS Connecting for Health
doi:10.1371/journal.pmed.1000387
PMCID: PMC3022523  PMID: 21267058
2.  Can Broader Diffusion of Value-Based Insurance Design Increase Benefits from US Health Care without Increasing Costs? Evidence from a Computer Simulation Model 
PLoS Medicine  2010;7(2):e1000234.
Using a computer simulation based on US data, R. Scott Braithwaite and colleagues calculate the benefits of value-based insurance design, in which patients pay less for highly cost-effective services.
Background
Evidence suggests that cost sharing (i.e.,copayments and deductibles) decreases health expenditures but also reduces essential care. Value-based insurance design (VBID) has been proposed to encourage essential care while controlling health expenditures. Our objective was to estimate the impact of broader diffusion of VBID on US health care benefits and costs.
Methods and Findings
We used a published computer simulation of costs and life expectancy gains from US health care to estimate the impact of broader diffusion of VBID. Two scenarios were analyzed: (1) applying VBID solely to pharmacy benefits and (2) applying VBID to both pharmacy benefits and other health care services (e.g., devices). We assumed that cost sharing would be eliminated for high-value services (<$100,000 per life-year), would remain unchanged for intermediate- or unknown-value services ($100,000–$300,000 per life-year or unknown), and would be increased for low-value services (>$300,000 per life-year). All costs are provided in 2003 US dollars. Our simulation estimated that approximately 60% of health expenditures in the US are spent on low-value services, 20% are spent on intermediate-value services, and 20% are spent on high-value services. Correspondingly, the vast majority (80%) of health expenditures would have cost sharing that is impacted by VBID. With prevailing patterns of cost sharing, health care conferred 4.70 life-years at a per-capita annual expenditure of US$5,688. Broader diffusion of VBID to pharmaceuticals increased the benefit conferred by health care by 0.03 to 0.05 additional life-years, without increasing costs and without increasing out-of-pocket payments. Broader diffusion of VBID to other health care services could increase the benefit conferred by health care by 0.24 to 0.44 additional life-years, also without increasing costs and without increasing overall out-of-pocket payments. Among those without health insurance, using cost saving from VBID to subsidize insurance coverage would increase the benefit conferred by health care by 1.21 life-years, a 31% increase.
Conclusion
Broader diffusion of VBID may amplify benefits from US health care without increasing health expenditures.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
More money is spent per person on health care in the US than in any other country. US health care expenditure accounts for 16.2% of the gross domestic product and this figure is rising. Indeed, the increase in health care costs is outstripping the economy's growth rate. Consequently, US policy makers and providers of health insurance—health care in the US is largely provided by the private sector and is paid for through private health insurance or through government programs such as Medicare and Medicaid—are looking for better ways to control health expenditures. Although some health care cost reductions can be achieved by increasing efficiency, controlling the quantity of health care consumed is an essential component of strategies designed to reduce health expenditures. These strategies can target health care providers (for example, by requiring primary care physicians to provide referrals before their patients' insurance provides cover for specialist care) or can target consumers, often through cost sharing. Nowadays, most insurance plans include several tiers of cost sharing in which patients pay a larger proportion of the costs of expensive interventions than of cheap interventions.
Why Was This Study Done?
Cost sharing decreases health expenditure but it can also reduce demand for essential care and thus reduce the quality of care. Consequently, some experts have proposed value-based insurance design (VBID), an approach in which the amount of cost sharing is set according to the “value” of an intervention rather than its cost. The value of an intervention is defined as the ratio of the additional benefits to the additional costs of the intervention when compared to the next best alternative intervention. Under VBID, cost sharing could be waived for office visits necessary to control blood pressure in people with diabetes, which deliver high-value care, but could be increased for high-tech scans for dementia, which deliver low-value care. VBID has been adopted by several private health insurance schemes and its core principal is endorsed by US policy makers. However, it is unclear whether wider use of VBID is warranted. In this study, the researchers use a computer simulation of the US health care system to estimate the impact of broader diffusion of VBID on US health care benefits and costs.
What Did the Researchers Do and Find?
The researchers used their computer simulation to estimate the impact of applying VBID to cost sharing for drugs alone and to cost sharing for drugs, procedures, and other health care services for one million hypothetical US patients. In their simulation, the researchers eliminated cost sharing for services that cost less than US$100,000 per life-year gained (high-value services) and increased cost-sharing for services that cost more than US$300,000 per life-year gained (low-value services); cost-sharing remained unchanged for intermediate- or unknown-value services. With the current pattern of cost sharing, 60% of health expenditure is spent on low-value services and health care increases life expectancy by 4.70 years for an annual per person expenditure of US$5,688, the researchers report. With widespread application of VBID to cost sharing for drugs alone, health care increased life expectancy by an additional 0.03 to 0.05 years without increasing costs. With widespread application of VBID to cost sharing for other health care services, health care increased life expectancy by a further 0.24 to 0.44 years without additional costs. Finally, if the costs saved by applying VBID were used to subsidize insurance for the 15% of the US population currently without health insurance, the benefit conferred by health care among these people would increase by 1.21 life-years.
What Do These Findings Mean?
The findings of this study depend on the many assumptions included in the computer simulation, which, although complex, is a greatly simplified representation of the US health care system. Nevertheless, these findings suggest that if VBID were used more widely within the US health care system to encourage the use of high-value services, it might be possible to amplify the benefits from US health care without increasing health expenditures. Importantly, the money saved by VBID could be used to help fund universal insurance, a central aim of US health care reform. More research is needed, however, to determine the value of various health care interventions and to investigate whether other ways of linking value to cost sharing might yield even better gains in life expectancy at little or no additional cost.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000234.
Wikipedia has a page on health care in the United States (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
Families USA works to promote high-quality affordable health care for all Americans and provides information about all aspects of US health care and about US health care reforms
The US Centers for Medicare and Medicaid provides information on the major government health insurance programs and on US national health expenditure statistics
doi:10.1371/journal.pmed.1000234
PMCID: PMC2821897  PMID: 20169114
3.  Home Telehealth for Patients With Chronic Obstructive Pulmonary Disease (COPD) 
Executive Summary
In July 2010, the Medical Advisory Secretariat (MAS) began work on a Chronic Obstructive Pulmonary Disease (COPD) evidentiary framework, an evidence-based review of the literature surrounding treatment strategies for patients with COPD. This project emerged from a request by the Health System Strategy Division of the Ministry of Health and Long-Term Care that MAS provide them with an evidentiary platform on the effectiveness and cost-effectiveness of COPD interventions.
After an initial review of health technology assessments and systematic reviews of COPD literature, and consultation with experts, MAS identified the following topics for analysis: vaccinations (influenza and pneumococcal), smoking cessation, multidisciplinary care, pulmonary rehabilitation, long-term oxygen therapy, noninvasive positive pressure ventilation for acute and chronic respiratory failure, hospital-at-home for acute exacerbations of COPD, and telehealth (including telemonitoring and telephone support). Evidence-based analyses were prepared for each of these topics. For each technology, an economic analysis was also completed where appropriate. In addition, a review of the qualitative literature on patient, caregiver, and provider perspectives on living and dying with COPD was conducted, as were reviews of the qualitative literature on each of the technologies included in these analyses.
The Chronic Obstructive Pulmonary Disease Mega-Analysis series is made up of the following reports, which can be publicly accessed at the MAS website at: http://www.hqontario.ca/en/mas/mas_ohtas_mn.html.
Chronic Obstructive Pulmonary Disease (COPD) Evidentiary Framework
Influenza and Pneumococcal Vaccinations for Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Smoking Cessation for Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Community-Based Multidisciplinary Care for Patients With Stable Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Pulmonary Rehabilitation for Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Long-term Oxygen Therapy for Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Noninvasive Positive Pressure Ventilation for Acute Respiratory Failure Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Noninvasive Positive Pressure Ventilation for Chronic Respiratory Failure Patients With Stable Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Hospital-at-Home Programs for Patients With Acute Exacerbations of Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Home Telehealth for Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Cost-Effectiveness of Interventions for Chronic Obstructive Pulmonary Disease Using an Ontario Policy Model
Experiences of Living and Dying With COPD: A Systematic Review and Synthesis of the Qualitative Empirical Literature
For more information on the qualitative review, please contact Mita Giacomini at: http://fhs.mcmaster.ca/ceb/faculty_member_giacomini.htm.
For more information on the economic analysis, please visit the PATH website: http://www.path-hta.ca/About-Us/Contact-Us.aspx.
The Toronto Health Economics and Technology Assessment (THETA) collaborative has produced an associated report on patient preference for mechanical ventilation. For more information, please visit the THETA website: http://theta.utoronto.ca/static/contact.
Objective
The objective of this analysis was to conduct an evidence-based assessment of home telehealth technologies for patients with chronic obstructive pulmonary disease (COPD) in order to inform recommendations regarding the access and provision of these services in Ontario. This analysis was one of several analyses undertaken to evaluate interventions for COPD. The perspective of this assessment was that of the Ontario Ministry of Health and Long-Term Care, a provincial payer of medically necessary health care services.
Clinical Need: Condition and Target Population
Canada is facing an increase in chronic respiratory diseases due in part to its aging demographic. The projected increase in COPD will put a strain on health care payers and providers. There is therefore an increasing demand for telehealth services that improve access to health care services while maintaining or improving quality and equality of care. Many telehealth technologies however are in the early stages of development or diffusion and thus require study to define their application and potential harms or benefits. The Medical Advisory Secretariat (MAS) therefore sought to evaluate telehealth technologies for COPD.
Technology
Telemedicine (or telehealth) refers to using advanced information and communication technologies and electronic medical devices to support the delivery of clinical care, professional education, and health-related administrative services.
Generally there are 4 broad functions of home telehealth interventions for COPD:
to monitor vital signs or biological health data (e.g., oxygen saturation),
to monitor symptoms, medication, or other non-biologic endpoints (e.g., exercise adherence),
to provide information (education) and/or other support services (such as reminders to exercise or positive reinforcement), and
to establish a communication link between patient and provider.
These functions often require distinct technologies, although some devices can perform a number of these diverse functions. For the purposes of this review, MAS focused on home telemonitoring and telephone only support technologies.
Telemonitoring (or remote monitoring) refers to the use of medical devices to remotely collect a patient’s vital signs and/or other biologic health data and the transmission of those data to a monitoring station for interpretation by a health care provider.
Telephone only support refers to disease/disorder management support provided by a health care provider to a patient who is at home via telephone or videoconferencing technology in the absence of transmission of patient biologic data.
Research Questions
What is the effectiveness, cost-effectiveness, and safety of home telemonitoring compared with usual care for patients with COPD?
What is the effectiveness, cost-effectiveness, and safety of telephone only support programs compared with usual care for patients with COPD?
Research Methods
Literature Search
Search Strategy
A literature search was performed on November 3, 2010 using OVID MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, the Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Cochrane Library, and the International Agency for Health Technology Assessment (INAHTA) for studies published from January 1, 2000 until November 3, 2010. Abstracts were reviewed by a single reviewer and, for those studies meeting the eligibility criteria, full-text articles were obtained. Reference lists were also examined for any additional relevant studies not identified through the search. Articles with unknown eligibility were reviewed with a second clinical epidemiologist, and then a group of epidemiologists until consensus was established. The quality of evidence was assessed as high, moderate, low, or very low according to GRADE methodology.
Inclusion Criteria – Question #1
frequent transmission of a patient’s physiological data collected at home and without a health care professional physically present to health care professionals for routine monitoring through the use of a communication technology;
monitoring combined with a coordinated management and feedback system based on transmitted data;
telemonitoring as a key component of the intervention (subjective determination);
usual care as provided by the usual care provider for the control group;
randomized controlled trials (RCTs), controlled clinical trials (CCTs), systematic reviews, and/or meta-analyses;
published between January 1, 2000 and November 3, 2010.
Inclusion Criteria – Question #2
scheduled or frequent contact between patient and a health care professional via telephone or videoconferencing technology in the absence of transmission of patient physiological data;
monitoring combined with a coordinated management and feedback system based on transmitted data;
telephone support as a key component of the intervention (subjective determination);
usual care as provided by the usual care provider for the control group;
RCTs, CCTs, systematic reviews, and/or meta-analyses;
published between January 1, 2000 and November 3, 2010.
Exclusion Criteria
published in a language other than English;
intervention group (and not control) receiving some form of home visits by a medical professional, typically a nurse (i.e., telenursing) beyond initial technology set-up and education, to collect physiological data, or to somehow manage or treat the patient;
not recording patient or health system outcomes (e.g., technical reports testing accuracy, reliability or other development-related outcomes of a device, acceptability/feasibility studies, etc.);
not using an independent control group that received usual care (e.g., studies employing historical or periodic controls).
Outcomes of Interest
hospitalizations (primary outcome)
mortality
emergency department visits
length of stay
quality of life
other […]
Subgroup Analyses (a priori)
length of intervention (primary)
severity of COPD (primary)
Quality of Evidence
The quality of evidence assigned to individual studies was determined using a modified CONSORT Statement Checklist for Randomized Controlled Trials. (1) The CONSORT Statement was adapted to include 3 additional quality measures: the adequacy of control group description, significant differential loss to follow-up between groups, and greater than or equal to 30% study attrition. Individual study quality was defined based on total scores according to the CONSORT Statement checklist: very low (0 to < 40%), low (≥ 40 to < 60%), moderate (≥ 60 to < 80%), and high (≥ 80 to 100%).
The quality of the body of evidence was assessed as high, moderate, low, or very low according to the GRADE Working Group criteria. The following definitions of quality were used in grading the quality of the evidence:
Summary of Findings
Six publications, representing 5 independent trials, met the eligibility criteria for Research Question #1. Three trials were RCTs reported across 4 publications, whereby patients were randomized to home telemonitoring or usual care, and 2 trials were CCTs, whereby patients or health care centers were nonrandomly assigned to intervention or usual care.
A total of 310 participants were studied across the 5 included trials. The mean age of study participants in the included trials ranged from 61.2 to 74.5 years for the intervention group and 61.1 to 74.5 years for the usual care group. The percentage of men ranged from 40% to 64% in the intervention group and 46% to 72% in the control group.
All 5 trials were performed in a moderate to severe COPD patient population. Three trials initiated the intervention following discharge from hospital. One trial initiated the intervention following a pulmonary rehabilitation program. The final trial initiated the intervention during management of patients at an outpatient clinic.
Four of the 5 trials included oxygen saturation (i.e., pulse oximetry) as one of the biological patient parameters being monitored. Additional parameters monitored included forced expiratory volume in one second, peak expiratory flow, and temperature.
There was considerable clinical heterogeneity between trials in study design, methods, and intervention/control. In relation to the telemonitoring intervention, 3 of the 5 included studies used an electronic health hub that performed multiple functions beyond the monitoring of biological parameters. One study used only a pulse oximeter device alone with modem capabilities. Finally, in 1 study, patients measured and then forwarded biological data to a nurse during a televideo consultation. Usual care varied considerably between studies.
Only one trial met the eligibility criteria for Research Question #2. The included trial was an RCT that randomized 60 patients to nurse telephone follow-up or usual care (no telephone follow-up). Participants were recruited from the medical department of an acute-care hospital in Hong Kong and began receiving follow-up after discharge from the hospital with a diagnosis of COPD (no severity restriction). The intervention itself consisted of only two 10-to 20-minute telephone calls, once between days 3 to 7 and once between days 14 to 20, involving a structured, individualized educational and supportive programme led by a nurse that focused on 3 components: assessment, management options, and evaluation.
Regarding Research Question #1:
Low to very low quality evidence (according to GRADE) finds non-significant effects or conflicting effects (of significant or non-significant benefit) for all outcomes examined when comparing home telemonitoring to usual care.
There is a trend towards significant increase in time free of hospitalization and use of other health care services with home telemonitoring, but these findings need to be confirmed further in randomized trials of high quality.
There is severe clinical heterogeneity between studies that limits summary conclusions.
The economic impact of home telemonitoring is uncertain and requires further study.
Home telemonitoring is largely dependent on local information technologies, infrastructure, and personnel, and thus the generalizability of external findings may be low. Jurisdictions wishing to replicate home telemonitoring interventions should likely test those interventions within their jurisdictional framework before adoption, or should focus on home-grown interventions that are subjected to appropriate evaluation and proven effective.
Regarding Research Question #2:
Low quality evidence finds significant benefit in favour of telephone-only support for self-efficacy and emergency department visits when compared to usual care, but non-significant results for hospitalizations and hospital length of stay.
There are very serious issues with the generalizability of the evidence and thus additional research is required.
PMCID: PMC3384362  PMID: 23074421
4.  Configuring Balanced Scorecards for Measuring Health System Performance: Evidence from 5 Years' Evaluation in Afghanistan 
PLoS Medicine  2011;8(7):e1001066.
Anbrasi Edward and colleagues report the results of a balanced scorecard performance system used to examine 29 key performance indicators over a 5-year period in Afghanistan, between 2004 and 2008.
Background
In 2004, Afghanistan pioneered a balanced scorecard (BSC) performance system to manage the delivery of primary health care services. This study examines the trends of 29 key performance indicators over a 5-year period between 2004 and 2008.
Methods and Findings
Independent evaluations of performance in six domains were conducted annually through 5,500 patient observations and exit interviews and 1,500 provider interviews in >600 facilities selected by stratified random sampling in each province. Generalized estimating equation (GEE) models were used to assess trends in BSC parameters. There was a progressive improvement in the national median scores scaled from 0–100 between 2004 and 2008 in all six domains: patient and community satisfaction of services (65.3–84.5, p<0.0001); provider satisfaction (65.4–79.2, p<0.01); capacity for service provision (47.4–76.4, p<0.0001); quality of services (40.5–67.4, p<0.0001); and overall vision for pro-poor and pro-female health services (52.0–52.6). The financial domain also showed improvement until 2007 (84.4–95.7, p<0.01), after which user fees were eliminated. By 2008, all provinces achieved the upper benchmark of national median set in 2004.
Conclusions
The BSC has been successfully employed to assess and improve health service capacity and service delivery using performance benchmarking during the 5-year period. However, scorecard reconfigurations are needed to integrate effectiveness and efficiency measures and accommodate changes in health systems policy and strategy architecture to ensure its continued relevance and effectiveness as a comprehensive health system performance measure. The process of BSC design and implementation can serve as a valuable prototype for health policy planners managing performance in similar health care contexts.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Traditionally, the performance of a health system (the complete network of health care agencies, facilities, and providers in a defined geographical region) has been measured in terms of health outcomes: how many people have been treated, how many got better, and how many died. But, nowadays, with increased demand for improved governance and accountability, policy makers are seeking comprehensive performance measures that show in detail how innovations designed to strengthen health systems are affecting service delivery and health outcomes. One such performance measure is the “balanced scorecard,” an integrated management and measurement tool that enables organizations to clarify their vision and strategy and translate them into action. The balanced scorecard—essentially a list of key performance indicators and performance benchmarks in several domains—was originally developed for industry but is now becoming a popular strategic management tool in the health sector. For example, balanced scorecards have been successfully integrated into the Dutch and Italian public health care systems.
Why Was This Study Done?
Little is known about the use of balanced scorecards in the national public health care systems of developing countries but the introduction of performance management into health system reform in fragile states in particular (developing countries where the state fails to perform the fundamental functions necessary to meet its citizens' basic needs and expectations) could help to promote governance and leadership, and facilitate essential policy changes. One fragile state that has introduced the balanced scorecard system for public health care management is Afghanistan, which emerged from decades of conflict in 2002 with some of the world's worst health indicators. To deal with an extremely high burden of disease, the Ministry of Public Health (MOPH) designed a Basic Package of Health Services (BPHS), which is delivered by nongovernmental organizations and MOPH agencies. In 2004, the MOPH introduced the National Health Service Performance Assessment (NHSPA), an annual country-wide assessment of service provision and patient satisfaction and pioneered a balanced scorecard, which uses data collected in the NHSPA, to manage the delivery of primary health care services. In this study, the researchers examine the trends between 2004 and 2008 of the 29 key performance indicators in six domains included in this balanced scorecard, and consider the potential and limitations of the scorecard as a management tool to measure and improve health service delivery in Afghanistan and other similar countries.
What Did the Researchers Do and Find?
Each year of the study, a random sample of 25 facilities (district hospitals and comprehensive and basic health centers) in 28 of Afghanistan's 34 provinces was chosen (one province did not have functional facilities in 2004 and the other five missing provinces were inaccessible because of ongoing conflicts). NHSPA surveyors collected approximately 5,000 patient observations, 5,000 exit interviews with patients or their caregivers, and 1,500 health provider interviews by observing consultations involving five children under 5 years old and five patients over 5 years old in each facility. The researchers then used this information to evaluate the key performance indicators in the balanced scorecard and a statistical method called generalized estimating equation modeling to assess trends in these indicators. They report that there was a progressive improvement in national average scores in all six domains (patients and community satisfaction with services, provider satisfaction, capacity for service provision, quality of services, overall vision for pro-poor and pro-female health services, and financial systems) between 2004 and 2008.
What Do These Findings Mean?
These findings suggest that the balanced scorecard was successfully used to improve health system capacity and service delivery through performance benchmarking over the 5-year study period. Importantly, the use of the balanced scorecard helped to show the effects of investments, facilitate policy change, and create a more evidence-based decision-making culture in Afghanistan's primary health care system. However, the researchers warn that the continuing success of the balanced scorecard in Afghanistan will depend on its ability to accommodate changes in health systems policy. Furthermore, reconfigurations of the scorecard are needed to include measures of the overall effectiveness and efficiency of the health system such as mortality rates. More generally, the researchers conclude that the balanced scorecard offers a promising measure of health system performance that could be used to examine the effectiveness of health care strategies and innovations in other fragile and developing countries.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001066.
A 2010 article entitled An Afghan Success Story: The Balanced Scorecard and Improved Health Services in The Globe, a newsletter produced by the Department of International Health at the John Hopkins Bloomberg School of Public Health, provides a detailed description of the balanced scorecard used in this study
Wikipedia has a page on health systems and on balanced scorecards (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
The World Health Organization country profile of Afghanistan provides information on the country's health system and burden of disease (in several languages)
doi:10.1371/journal.pmed.1001066
PMCID: PMC3144209  PMID: 21814499
5.  The Role of Health Systems Factors in Facilitating Access to Psychotropic Medicines: A Cross-Sectional Analysis of the WHO-AIMS in 63 Low- and Middle-Income Countries 
PLoS Medicine  2012;9(1):e1001166.
In a cross-sectional analysis of WHO-AIMS data, Ryan McBain and colleagues investigate the associations between health system components and access to psychotropic drugs in 63 low and middle income countries.
Background
Neuropsychiatric conditions comprise 14% of the global burden of disease and 30% of all noncommunicable disease. Despite the existence of cost-effective interventions, including administration of psychotropic medicines, the number of persons who remain untreated is as high as 85% in low- and middle-income countries (LAMICs). While access to psychotropic medicines varies substantially across countries, no studies to date have empirically investigated potential health systems factors underlying this issue.
Methods and Findings
This study uses a cross-sectional sample of 63 LAMICs and country regions to identify key health systems components associated with access to psychotropic medicines. Data from countries that completed the World Health Organization Assessment Instrument for Mental Health Systems (WHO-AIMS) were included in multiple regression analyses to investigate the role of five major mental health systems domains in shaping medicine availability and affordability. These domains are: mental health legislation, human rights implementations, mental health care financing, human resources, and the role of advocacy groups. Availability of psychotropic medicines was associated with features of all five mental health systems domains. Most notably, within the domain of mental health legislation, a comprehensive national mental health plan was associated with 15% greater availability; and in terms of advocacy groups, the participation of family-based organizations in the development of mental health legislation was associated with 17% greater availability. Only three measures were related with affordability of medicines to consumers: level of human resources, percentage of countries' health budget dedicated to mental health, and availability of mental health care in prisons. Controlling for country development, as measured by the Human Development Index, health systems features were associated with medicine availability but not affordability.
Conclusions
Results suggest that strengthening particular facets of mental health systems might improve availability of psychotropic medicines and that overall country development is associated with affordability.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Mental disorders—conditions that involve impairment of thinking, emotions, and behavior—are extremely common. Worldwide, mental illness affects about 450 million people and accounts for 13.5% of the global burden of disease. About one in four people will have a mental health problem at some time in their life. For some people, this will be a short period of mild depression, anxiety, or stress. For others, it will be a serious, long-lasting condition such as schizophrenia, bipolar disorder, or major depression. People with mental health problems need help and support from professionals and from their friends and families to help them cope with their illness but are often discriminated against, which can make their illness worse. Treatments include counseling and psychotherapy (talking therapies), and psychotropic medicines—drugs that act mainly on the brain. Left untreated, many people with serious mental illnesses commit suicide.
Why Was This Study Done?
About 80% of people with mental illnesses live in low- and middle-income countries (LAMICs) where up to 85% of patients remain untreated. Access to psychotropic medicines, which constitute an essential and cost-effective component in the treatment of mental illnesses, is particularly poor in many LAMICs. To improve this situation, it is necessary to understand what health systems factors limit the availability and affordability of psychotropic drugs; a health system is the sum of all the organizations, institutions, and resources that act together to improve health. In this cross-sectional study, the researchers look for associations between specific health system components and access to psychotropic medicines by analyzing data collected from LAMICs using the World Health Organization's Assessment Instrument for Mental Health Systems (WHO-AIMS). A cross-sectional study analyzes data collected at a single time. WHO-AIMS, which was created to evaluate mental health systems primarily in LAMICs, is a 155-item survey that Ministries of Health and other country-based agencies can use to collect information on mental health indicators.
What Did the Researchers Do and Find?
The researchers used WHO-AIMS data from 63 countries/country regions and multiple regression analysis to evaluate the role of mental health legislation, human rights implementation, mental health care financing, human resources, and advocacy in shaping medicine availability and affordability. For each of these health systems domains, the researchers developed one or more summary measurements. For example, they measured financing as the percentage of government health expenditure directed toward mental health. Availability of psychotropic medicines was defined as the percentage of mental health facilities in which at least one psychotropic medication for each therapeutic category was always available. Affordability was measured by calculating the percentage of daily minimum wage needed to purchase medicine by the average consumer. The availability of psychotropic medicines was related to features of all five mental health systems domains, report the researchers. Notably, having a national mental health plan (part of the legislation domain) and the participation (advocacy) of family-based organizations in mental health legislation formulation were associated with 15% and 17% greater availability of medicines, respectively. By contrast, only the levels of human resources and financing, and the availability of mental health care in prisons (part of the human rights domain) were associated with the affordability of psychotropic medicines. Once overall country development was taken into account, most of the associations between health systems factors and medicine availability remained significant, while the associations between health systems factors and medicine affordability were no longer significant. In part, this was because country development was more strongly associated with affordability and explained most of the relationships: for example, countries with greater overall development have higher expenditures on mental health and greater medicine affordability compared to availability.
What Do These Findings Mean?
These findings indicate that access to psychotropic medicines in LAMICs is related to key components within the mental health systems of these countries but that availability and affordability are affected to different extents by these components. They also show that country development plays a strong role in determining affordability but has less effect on determining availability. Because cross-sectional data were used in this study, these findings only indicate associations; they do not imply causality. They are also limited by the relatively small number of observations included in this study, by the methods used to collect mental health systems data in many LAMICs, and by the possibility that some countries may have reported biased results. Despite these limitations, these findings suggest that strengthening specific mental health system features may be an important way to facilitate access to psychotropic medicines but also highlight the role that country wealth and development play in promoting the treatment of mental disorders.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/ 10.1371/journal.pmed.1001166.
The US National Institute of Mental Health provides information on all aspects of mental health (in English and Spanish)
The UK National Health Service Choices website provides information on mental health; its Live Well feature provides practical advice on dealing with mental health problems and personal stories
The UK charity Mind provides further information about mental illness, including personal stories
MedlinePlus provides links to many other sources of information on mental health (in English and Spanish)
Information on WHO-AIMS, including versions of the instrument in several languages, and WHO-AIMS country reports are available
doi:10.1371/journal.pmed.1001166
PMCID: PMC3269418  PMID: 22303288
6.  An Epidemiological Network Model for Disease Outbreak Detection 
PLoS Medicine  2007;4(6):e210.
Background
Advanced disease-surveillance systems have been deployed worldwide to provide early detection of infectious disease outbreaks and bioterrorist attacks. New methods that improve the overall detection capabilities of these systems can have a broad practical impact. Furthermore, most current generation surveillance systems are vulnerable to dramatic and unpredictable shifts in the health-care data that they monitor. These shifts can occur during major public events, such as the Olympics, as a result of population surges and public closures. Shifts can also occur during epidemics and pandemics as a result of quarantines, the worried-well flooding emergency departments or, conversely, the public staying away from hospitals for fear of nosocomial infection. Most surveillance systems are not robust to such shifts in health-care utilization, either because they do not adjust baselines and alert-thresholds to new utilization levels, or because the utilization shifts themselves may trigger an alarm. As a result, public-health crises and major public events threaten to undermine health-surveillance systems at the very times they are needed most.
Methods and Findings
To address this challenge, we introduce a class of epidemiological network models that monitor the relationships among different health-care data streams instead of monitoring the data streams themselves. By extracting the extra information present in the relationships between the data streams, these models have the potential to improve the detection capabilities of a system. Furthermore, the models' relational nature has the potential to increase a system's robustness to unpredictable baseline shifts. We implemented these models and evaluated their effectiveness using historical emergency department data from five hospitals in a single metropolitan area, recorded over a period of 4.5 y by the Automated Epidemiological Geotemporal Integrated Surveillance real-time public health–surveillance system, developed by the Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology on behalf of the Massachusetts Department of Public Health. We performed experiments with semi-synthetic outbreaks of different magnitudes and simulated baseline shifts of different types and magnitudes. The results show that the network models provide better detection of localized outbreaks, and greater robustness to unpredictable shifts than a reference time-series modeling approach.
Conclusions
The integrated network models of epidemiological data streams and their interrelationships have the potential to improve current surveillance efforts, providing better localized outbreak detection under normal circumstances, as well as more robust performance in the face of shifts in health-care utilization during epidemics and major public events.
Most surveillance systems are not robust to shifts in health care utilization. Ben Reis and colleagues developed network models that detected localized outbreaks better and were more robust to unpredictable shifts.
Editors' Summary
Background.
The main task of public-health officials is to promote health in communities around the world. To do this, they need to monitor human health continually, so that any outbreaks (epidemics) of infectious diseases (particularly global epidemics or pandemics) or any bioterrorist attacks can be detected and dealt with quickly. In recent years, advanced disease-surveillance systems have been introduced that analyze data on hospital visits, purchases of drugs, and the use of laboratory tests to look for tell-tale signs of disease outbreaks. These surveillance systems work by comparing current data on the use of health-care resources with historical data or by identifying sudden increases in the use of these resources. So, for example, more doctors asking for tests for salmonella than in the past might presage an outbreak of food poisoning, and a sudden rise in people buying over-the-counter flu remedies might indicate the start of an influenza pandemic.
Why Was This Study Done?
Existing disease-surveillance systems don't always detect disease outbreaks, particularly in situations where there are shifts in the baseline patterns of health-care use. For example, during an epidemic, people might stay away from hospitals because of the fear of becoming infected, whereas after a suspected bioterrorist attack with an infectious agent, hospitals might be flooded with “worried well” (healthy people who think they have been exposed to the agent). Baseline shifts like these might prevent the detection of increased illness caused by the epidemic or the bioterrorist attack. Localized population surges associated with major public events (for example, the Olympics) are also likely to reduce the ability of existing surveillance systems to detect infectious disease outbreaks. In this study, the researchers developed a new class of surveillance systems called “epidemiological network models.” These systems aim to improve the detection of disease outbreaks by monitoring fluctuations in the relationships between information detailing the use of various health-care resources over time (data streams).
What Did the Researchers Do and Find?
The researchers used data collected over a 3-y period from five Boston hospitals on visits for respiratory (breathing) problems and for gastrointestinal (stomach and gut) problems, and on total visits (15 data streams in total), to construct a network model that included all the possible pair-wise comparisons between the data streams. They tested this model by comparing its ability to detect simulated disease outbreaks implanted into data collected over an additional year with that of a reference model based on individual data streams. The network approach, they report, was better at detecting localized outbreaks of respiratory and gastrointestinal disease than the reference approach. To investigate how well the network model dealt with baseline shifts in the use of health-care resources, the researchers then added in a large population surge. The detection performance of the reference model decreased in this test, but the performance of the complete network model and of models that included relationships between only some of the data streams remained stable. Finally, the researchers tested what would happen in a situation where there were large numbers of “worried well.” Again, the network models detected disease outbreaks consistently better than the reference model.
What Do These Findings Mean?
These findings suggest that epidemiological network systems that monitor the relationships between health-care resource-utilization data streams might detect disease outbreaks better than current systems under normal conditions and might be less affected by unpredictable shifts in the baseline data. However, because the tests of the new class of surveillance system reported here used simulated infectious disease outbreaks and baseline shifts, the network models may behave differently in real-life situations or if built using data from other hospitals. Nevertheless, these findings strongly suggest that public-health officials, provided they have sufficient computer power at their disposal, might improve their ability to detect disease outbreaks by using epidemiological network systems alongside their current disease-surveillance systems.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040210.
Wikipedia pages on public health (note that Wikipedia is a free online encyclopedia that anyone can edit, and is available in several languages)
A brief description from the World Health Organization of public-health surveillance (in English, French, Spanish, Russian, Arabic, and Chinese)
A detailed report from the US Centers for Disease Control and Prevention called “Framework for Evaluating Public Health Surveillance Systems for the Early Detection of Outbreaks”
The International Society for Disease Surveillance Web site
doi:10.1371/journal.pmed.0040210
PMCID: PMC1896205  PMID: 17593895
7.  Automated Detection of Infectious Disease Outbreaks in Hospitals: A Retrospective Cohort Study 
PLoS Medicine  2010;7(2):e1000238.
Susan Huang and colleagues describe an automated statistical software, WHONET-SaTScan, its application in a hospital, and the potential it has to identify hospital infection clusters that had escaped routine detection.
Background
Detection of outbreaks of hospital-acquired infections is often based on simple rules, such as the occurrence of three new cases of a single pathogen in two weeks on the same ward. These rules typically focus on only a few pathogens, and they do not account for the pathogens' underlying prevalence, the normal random variation in rates, and clusters that may occur beyond a single ward, such as those associated with specialty services. Ideally, outbreak detection programs should evaluate many pathogens, using a wide array of data sources.
Methods and Findings
We applied a space-time permutation scan statistic to microbiology data from patients admitted to a 750-bed academic medical center in 2002–2006, using WHONET-SaTScan laboratory information software from the World Health Organization (WHO) Collaborating Centre for Surveillance of Antimicrobial Resistance. We evaluated patients' first isolates for each potential pathogenic species. In order to evaluate hospital-associated infections, only pathogens first isolated >2 d after admission were included. Clusters were sought daily across the entire hospital, as well as in hospital wards, specialty services, and using similar antimicrobial susceptibility profiles. We assessed clusters that had a likelihood of occurring by chance less than once per year. For methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant enterococci (VRE), WHONET-SaTScan–generated clusters were compared to those previously identified by the Infection Control program, which were based on a rule-based criterion of three occurrences in two weeks in the same ward. Two hospital epidemiologists independently classified each cluster's importance. From 2002 to 2006, WHONET-SaTScan found 59 clusters involving 2–27 patients (median 4). Clusters were identified by antimicrobial resistance profile (41%), wards (29%), service (13%), and hospital-wide assessments (17%). WHONET-SaTScan rapidly detected the two previously known gram-negative pathogen clusters. Compared to rule-based thresholds, WHONET-SaTScan considered only one of 73 previously designated MRSA clusters and 0 of 87 VRE clusters as episodes statistically unlikely to have occurred by chance. WHONET-SaTScan identified six MRSA and four VRE clusters that were previously unknown. Epidemiologists considered more than 95% of the 59 detected clusters to merit consideration, with 27% warranting active investigation or intervention.
Conclusions
Automated statistical software identified hospital clusters that had escaped routine detection. It also classified many previously identified clusters as events likely to occur because of normal random fluctuations. This automated method has the potential to provide valuable real-time guidance both by identifying otherwise unrecognized outbreaks and by preventing the unnecessary implementation of resource-intensive infection control measures that interfere with regular patient care.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Admission to a hospital is often a life-saving necessity—individuals injured in a road accident, for example, may need immediate medical and surgical attention if they are to survive. Unfortunately, many patients acquire infections, some of which are life-threatening, during their stay in a hospital. The World Health Organization has estimated that, globally, 8.7% of hospital patients develop hospital-acquired infections (infections that are identified more than two days after admission to hospital). In the US alone, 2 million people develop a hospital-acquired infection every year, often an infection of a surgical wound, or a urinary tract or lung infection. Infections are common among hospital patients because increasing age or underlying illnesses can reduce immunity to infection and because many medical and surgical procedures bypass the body's natural protective barriers. In addition, poor infection control practices can facilitate the transmission of bacteria—including meticillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE)—and other infectious agents (pathogens) between patients.
Why Was This Study Done?
Sometimes, the number of cases of hospital-acquired infections increases unexpectedly or a new infection emerges. Such clusters account for relatively few health care–associated infections, but, because they may arise from the transmission of a pathogen within a hospital, they need to be rapidly identified and measures implemented (for example, isolation of affected patients) to stop transmission if an outbreak is confirmed. Currently, the detection of clusters of hospital-acquired infections is based on simple rules, such as the occurrence of three new cases of a single pathogen in two weeks on the same ward. This rule-based approach relies on the human eye to detect infection clusters within microbiology data (information collected on the pathogens isolated from patients), it focuses on a few pathogens, and it does not consider the random variation in infection rates or the possibility that clusters might be associated with shared facilities rather than with individual wards. In this study, the researchers test whether an automated statistical system can detect outbreaks of hospital-acquired infections quickly and accurately.
What Did the Researchers Do and Find?
The researchers combined two software packages used to track diseases in populations to create the WHONET-SaTScan cluster detection tool. They then compared the clusters of hospital-acquired infection identified by the new tool in microbiology data from a 750-bed US academic medical center with those generated by the hospital's infection control program, which was largely based on the simple rule described above. WHONET-SaTScan found 59 clusters of infection that occurred between 2002 and 2006, about three-quarters of which were identified by characteristics other than a ward-based location. Nearly half the cluster alerts were generated on the basis of shared antibiotic susceptibility patterns. Although WHONET-SaTScan identified all the clusters previously identified by the hospital's infection control program, it classified most of these clusters as likely to be the result of normal random variations in infection rates rather than the result of “true” outbreaks. By contrast, the hospital's infection control department only identified three of the 59 statistically significant clusters identified by WHONET-SaTScan. Furthermore, the new tool identified six previously unknown MRSA outbreaks and four previously unknown VRE outbreaks. Finally, two hospital epidemiologists (scientists who study diseases in populations) classified 95% of the clusters detected by WHONET-SaTScan as worthy of consideration by the hospital infection control team and a quarter of the clusters as warranting active investigation or intervention.
What Do These Findings Mean?
These findings suggest that automated statistical software should be able to detect clusters of hospital-acquired infections that would escape detection using routine rule-based systems. Importantly, they also suggest that an automated system would be able to discount a large number of supposed outbreaks identified by rule-based systems. These findings need to be confirmed in other settings and in prospective studies in which the outcomes of clusters detected with WHONET-SaTScan are carefully analyzed. For now, however, these findings suggest that automated statistical tools could provide hospital infection control experts with valuable real-time guidance by identifying outbreaks that would be missed by routine detection methods and by preventing the implementation of intensive and costly infection control measures in situations where they are unnecessary.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000238.
The World Health Organization's Prevention of Hospital-Acquired Infections, A Practical Guide contains detailed information on all aspects of hospital-acquired infections
MedlinePlus provides links to information on infection control in hospitals (in English and Spanish)
The US Centers for Disease Control and Prevention also provides information on infectious diseases in health care settings (in English and Spanish)
The WHONET/Baclink software and the SatScan software, the two components of WHONET-SaTScan are both available on the internet (the WHONET-SaTScan cluster detection tool is freely available as part of the version of WHONET/BacLink released June 2009)
doi:10.1371/journal.pmed.1000238
PMCID: PMC2826381  PMID: 20186274
8.  Electronic Tools for Health Information Exchange 
Background
As patients experience transitions in care, there is a need to share information between care providers in an accurate and timely manner. With the push towards electronic medical records and other electronic tools (eTools) (and away from paper-based health records) for health information exchange, there remains uncertainty around the impact of eTools as a form of communication.
Objective
To examine the impact of eTools for health information exchange in the context of care coordination for individuals with chronic disease in the community.
Data Sources
A literature search was performed on April 26, 2012, using OVID MEDLINE, OVID MEDLINE In-Process and Other Non-Indexed Citations, OVID EMBASE, EBSCO Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Wiley Cochrane Library, and the Centre for Reviews and Dissemination database, for studies published until April 26, 2012 (no start date limit was applied).
Review Methods
A systematic literature search was conducted, and meta-analysis conducted where appropriate. Outcomes of interest fell into 4 categories: health services utilization, disease-specific clinical outcomes, process-of-care indicators, and measures of efficiency. The quality of the evidence was assessed individually for each outcome. Expert panels were assembled for stakeholder engagement and contextualization.
Results
Eleven articles were identified (4 randomized controlled trials and 7 observational studies). There was moderate quality evidence of a reduction in hospitalizations, hospital length of stay, and emergency department visits following the implementation of an electronically generated laboratory report with recommendations based on clinical guidelines. The evidence showed no difference in disease-specific outcomes; there was no evidence of a positive impact on process-of-care indicators or measures of efficiency.
Limitations
A limited body of research specifically examined eTools for health information exchange in the population and setting of interest. This evidence included a combination of study designs and was further limited by heterogeneity in individual technologies and settings in which they were implemented.
Conclusions
There is evidence that the right eTools in the right environment and context can significantly impact health services utilization. However, the findings from this evidence-based analysis raise doubts about the ability of eTools with care-coordination capabilities to independently improve the quality of outpatient care. While eTools may be able to support and sustain processes, inefficiencies embedded in the health care system may require more than automation alone to resolve.
Plain Language Summary
Patients with chronic diseases often work with many different health care providers. To ensure smooth transitions from one setting to the next, health care providers must share information and coordinate care effectively. Electronic medical records (eTools) are being used more and more to coordinate patient care, but it is not yet known whether they are more effective than paper-based health records. In this analysis, we reviewed the evidence for the use of eTools to exchange information and coordinate care for people with chronic diseases in the community. There was some evidence that eTools reduced the number of hospital and emergency department visits, as well as patients' length of stay in the hospital, but there was no evidence that eTools improved the overall quality of patient care.
PMCID: PMC3814806  PMID: 24194799
9.  Impact of Advanced (Open) Access Scheduling on Patients With Chronic Diseases 
Background
The goal of advanced access scheduling is to eliminate wait times for physician visits by ensuring access to same-day appointments, regardless of urgency or health care need. The intent is to reduce delays in access, leading to improvements in clinical care and patient satisfaction, and reductions in the use of urgent care.
Objective
To evaluate whether implementation of an advanced access scheduling system reduced other types of health service utilization and/or improved clinical measures and patient satisfaction among adults with chronic diseases.
Data Sources and Review Methods
A literature search was performed on January 29, 2012, for studies published from 1946 (OVID) or 1980 (EMBASE) to January 29, 2012. Systematic reviews, randomized controlled trials, and observational studies were eligible if they evaluated advanced access implementation in adults with chronic diseases and reported health resource utilization, patient outcomes, or patient satisfaction. Results were summarized descriptively.
Results
One systematic review in a primary care population and 4 observational studies (5 papers) in chronic disease and/or geriatric populations were identified. The systematic review concluded that advanced access did not improve clinical outcomes, but there was no evidence of harm. Findings from the observational studies in chronic disease populations were consistent with those of the systematic review. Advanced access implementation was not consistently associated with changes in clinical outcomes, patient satisfaction, or health service utilization.
Limitations
All studies were retrospective: 3 studies (4 papers) included historical controls only, and 1 included contemporaneous controls. Findings were inconsistent across studies for a number of outcomes.
Conclusions
Based on low to very low quality evidence, advanced access did not have a statistically (or clinically) significant impact on health service utilization among patients with diabetes and/or coronary artery disease (CAD). Very low quality evidence showed a significant reduction in the proportion of patients with diabetes and CAD admitted to hospital whose length of stay was greater than 3 days. Evidence was inconsistent for changes in clinical outcomes for patients with diabetes or CAD. Very low quality evidence showed no increase in patient satisfaction with an advanced access scheduling system.
Plain Language Summary
Timeliness of health care access—reducing wait times and delays for those receiving and providing care—is a key measure of health system quality. However, in international comparison studies, Canada ranked either last or next to last when it came to timely access to regular doctors. Efforts in Ontario to address delays in access have included the implementation of the Advanced Access and Efficiency for Primary Care initiative through the Quality Improvement and Innovation Partnership, later incorporated into Health Quality Ontario.
Advanced access is a physician appointment scheduling system that aims to eliminate wait times for physician visits and ensure same-day access for all patients, regardless of urgency or health care need. While it can generally be agreed that timely access to health care is necessary for all patients, same-day access may not always be required. Indeed, advanced access may adversely affect the care of patients with chronic diseases if clinics implement strict same-day appointment rules and patients cannot pre-book follow-up appointments. This review evaluated the effect of advanced access scheduling on clinical outcomes, patient satisfaction, and health service utilization in patients with selected chronic diseases, as part of the Optimizing Chronic Disease Management in the Outpatient (Community) Setting mega-analysis.
In patients with diabetes or coronary artery disease, advanced access implementation had little or no impact on acute health care use (hospitalizations, emergency department visits, and/or urgent care visits) and had inconsistent effects on clinical outcomes (blood glucose, low-density lipoprotein [LDL] cholesterol, and blood pressure). Two studies reported reduced monitoring of patients with chronic diseases after implementation of advanced access. Another study reported improved patient management (regular blood glucose and cholesterol testing) after advanced access implementation, but this was attributed to improved provider continuity rather than to reduced appointment wait times. There was no increase in patient satisfaction with the advanced access scheduling system. The quality of the evidence ranged from low to very low.
PMCID: PMC3796762  PMID: 24133569
10.  Hospital-at-Home Programs for Patients With Acute Exacerbations of Chronic Obstructive Pulmonary Disease (COPD) 
Executive Summary
In July 2010, the Medical Advisory Secretariat (MAS) began work on a Chronic Obstructive Pulmonary Disease (COPD) evidentiary framework, an evidence-based review of the literature surrounding treatment strategies for patients with COPD. This project emerged from a request by the Health System Strategy Division of the Ministry of Health and Long-Term Care that MAS provide them with an evidentiary platform on the effectiveness and cost-effectiveness of COPD interventions.
After an initial review of health technology assessments and systematic reviews of COPD literature, and consultation with experts, MAS identified the following topics for analysis: vaccinations (influenza and pneumococcal), smoking cessation, multidisciplinary care, pulmonary rehabilitation, long-term oxygen therapy, noninvasive positive pressure ventilation for acute and chronic respiratory failure, hospital-at-home for acute exacerbations of COPD, and telehealth (including telemonitoring and telephone support). Evidence-based analyses were prepared for each of these topics. For each technology, an economic analysis was also completed where appropriate. In addition, a review of the qualitative literature on patient, caregiver, and provider perspectives on living and dying with COPD was conducted, as were reviews of the qualitative literature on each of the technologies included in these analyses.
The Chronic Obstructive Pulmonary Disease Mega-Analysis series is made up of the following reports, which can be publicly accessed at the MAS website at: http://www.hqontario.ca/en/mas/mas_ohtas_mn.html.
Chronic Obstructive Pulmonary Disease (COPD) Evidentiary Framework
Influenza and Pneumococcal Vaccinations for Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Smoking Cessation for Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Community-Based Multidisciplinary Care for Patients With Stable Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Pulmonary Rehabilitation for Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Long-term Oxygen Therapy for Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Noninvasive Positive Pressure Ventilation for Acute Respiratory Failure Patients With Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Noninvasive Positive Pressure Ventilation for Chronic Respiratory Failure Patients With Stable Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Hospital-at-Home Programs for Patients With Acute Exacerbations of Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Home Telehealth for Patients with Chronic Obstructive Pulmonary Disease (COPD): An Evidence-Based Analysis
Cost-Effectiveness of Interventions for Chronic Obstructive Pulmonary Disease Using an Ontario Policy Model
Experiences of Living and Dying With COPD: A Systematic Review and Synthesis of the Qualitative Empirical Literature
For more information on the qualitative review, please contact Mita Giacomini at: http://fhs.mcmaster.ca/ceb/faculty_member_giacomini.htm.
For more information on the economic analysis, please visit the PATH website: http://www.path-hta.ca/About-Us/Contact-Us.aspx.
The Toronto Health Economics and Technology Assessment (THETA) collaborative has produced an associated report on patient preference for mechanical ventilation. For more information, please visit the THETA website: http://theta.utoronto.ca/static/contact.
Objective
The objective of this analysis was to compare hospital-at-home care with inpatient hospital care for patients with acute exacerbations of chronic obstructive pulmonary disease (COPD) who present to the emergency department (ED).
Clinical Need: Condition and Target Population
Acute Exacerbations of Chronic Obstructive Pulmonary Disease
Chronic obstructive pulmonary disease is a disease state characterized by airflow limitation that is not fully reversible. This airflow limitation is usually both progressive and associated with an abnormal inflammatory response of the lungs to noxious particles or gases. The natural history of COPD involves periods of acute-onset worsening of symptoms, particularly increased breathlessness, cough, and/or sputum, that go beyond normal day-to-day variations; these are known as acute exacerbations.
Two-thirds of COPD exacerbations are caused by an infection of the tracheobronchial tree or by air pollution; the cause in the remaining cases is unknown. On average, patients with moderate to severe COPD experience 2 or 3 exacerbations each year.
Exacerbations have an important impact on patients and on the health care system. For the patient, exacerbations result in decreased quality of life, potentially permanent losses of lung function, and an increased risk of mortality. For the health care system, exacerbations of COPD are a leading cause of ED visits and hospitalizations, particularly in winter.
Technology
Hospital-at-home programs offer an alternative for patients who present to the ED with an exacerbation of COPD and require hospital admission for their treatment. Hospital-at-home programs provide patients with visits in their home by medical professionals (typically specialist nurses) who monitor the patients, alter patients’ treatment plans if needed, and in some programs, provide additional care such as pulmonary rehabilitation, patient and caregiver education, and smoking cessation counselling.
There are 2 types of hospital-at-home programs: admission avoidance and early discharge hospital-at-home. In the former, admission avoidance hospital-at-home, after patients are assessed in the ED, they are prescribed the necessary medications and additional care needed (e.g., oxygen therapy) and then sent home where they receive regular visits from a medical professional. In early discharge hospital-at-home, after being assessed in the ED, patients are admitted to the hospital where they receive the initial phase of their treatment. These patients are discharged into a hospital-at-home program before the exacerbation has resolved. In both cases, once the exacerbation has resolved, the patient is discharged from the hospital-at-home program and no longer receives visits in his/her home.
In the models that exist to date, hospital-at-home programs differ from other home care programs because they deal with higher acuity patients who require higher acuity care, and because hospitals retain the medical and legal responsibility for patients. Furthermore, patients requiring home care services may require such services for long periods of time or indefinitely, whereas patients in hospital-at-home programs require and receive the services for a short period of time only.
Hospital-at-home care is not appropriate for all patients with acute exacerbations of COPD. Ineligible patients include: those with mild exacerbations that can be managed without admission to hospital; those who require admission to hospital; and those who cannot be safely treated in a hospital-at-home program either for medical reasons and/or because of a lack of, or poor, social support at home.
The proposed possible benefits of hospital-at-home for treatment of exacerbations of COPD include: decreased utilization of health care resources by avoiding hospital admission and/or reducing length of stay in hospital; decreased costs; increased health-related quality of life for patients and caregivers when treated at home; and reduced risk of hospital-acquired infections in this susceptible patient population.
Ontario Context
No hospital-at-home programs for the treatment of acute exacerbations of COPD were identified in Ontario. Patients requiring acute care for their exacerbations are treated in hospitals.
Research Question
What is the effectiveness, cost-effectiveness, and safety of hospital-at-home care compared with inpatient hospital care of acute exacerbations of COPD?
Research Methods
Literature Search
Search Strategy
A literature search was performed on August 5, 2010, using OVID MEDLINE, OVID MEDLINE In-Process and Other Non-Indexed Citations, OVID EMBASE, EBSCO Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Wiley Cochrane Library, and the Centre for Reviews and Dissemination database for studies published from January 1, 1990, to August 5, 2010. Abstracts were reviewed by a single reviewer and, for those studies meeting the eligibility criteria, full-text articles were obtained. Reference lists and health technology assessment websites were also examined for any additional relevant studies not identified through the systematic search.
Inclusion Criteria
English language full-text reports;
health technology assessments, systematic reviews, meta-analyses, and randomized controlled trials (RCTs);
studies performed exclusively in patients with a diagnosis of COPD or studies including patients with COPD as well as patients with other conditions, if results are reported for COPD patients separately;
studies performed in patients with acute exacerbations of COPD who present to the ED;
studies published between January 1, 1990, and August 5, 2010;
studies comparing hospital-at-home and inpatient hospital care for patients with acute exacerbations of COPD;
studies that include at least 1 of the outcomes of interest (listed below).
Cochrane Collaboration reviews have defined hospital-at-home programs as those that provide patients with active treatment for their acute exacerbation in their home by medical professionals for a limited period of time (in this case, until the resolution of the exacerbation). If a hospital-at-home program had not been available, these patients would have been admitted to hospital for their treatment.
Exclusion Criteria
< 18 years of age
animal studies
duplicate publications
grey literature
Outcomes of Interest
Patient/clinical outcomes
mortality
lung function (forced expiratory volume in 1 second)
health-related quality of life
patient or caregiver preference
patient or caregiver satisfaction with care
complications
Health system outcomes
hospital readmissions
length of stay in hospital and hospital-at-home
ED visits
transfer to long-term care
days to readmission
eligibility for hospital-at-home
Statistical Methods
When possible, results were pooled using Review Manager 5 Version 5.1; otherwise, results were summarized descriptively. Data from RCTs were analyzed using intention-to-treat protocols. In addition, a sensitivity analysis was done assigning all missing data/withdrawals to the event. P values less than 0.05 were considered significant. A priori subgroup analyses were planned for the acuity of hospital-at-home program, type of hospital-at-home program (early discharge or admission avoidance), and severity of the patients’ COPD. Additional subgroup analyses were conducted as needed based on the identified literature. Post hoc sample size calculations were performed using STATA 10.1.
Quality of Evidence
The quality of each included study was assessed, taking into consideration allocation concealment, randomization, blinding, power/sample size, withdrawals/dropouts, and intention-to-treat analyses.
The quality of the body of evidence was assessed as high, moderate, low, or very low according to the GRADE Working Group criteria. The following definitions of quality were used in grading the quality of the evidence:
Summary of Findings
Fourteen studies met the inclusion criteria and were included in this review: 1 health technology assessment, 5 systematic reviews, and 7 RCTs.
The following conclusions are based on low to very low quality of evidence. The reviewed evidence was based on RCTs that were inadequately powered to observe differences between hospital-at-home and inpatient hospital care for most outcomes, so there is a strong possibility of type II error. Given the low to very low quality of evidence, these conclusions must be considered with caution.
Approximately 21% to 37% of patients with acute exacerbations of COPD who present to the ED may be eligible for hospital-at-home care.
Of the patients who are eligible for care, some may refuse to participate in hospital-at-home care.
Eligibility for hospital-at-home care may be increased depending on the design of the hospital-at-home program, such as the size of the geographical service area for hospital-at-home and the hours of operation for patient assessment and entry into hospital-at-home.
Hospital-at-home care for acute exacerbations of COPD was associated with a nonsignificant reduction in the risk of mortality and hospital readmissions compared with inpatient hospital care during 2- to 6-month follow-up.
Limited, very low quality evidence suggests that hospital readmissions are delayed in patients who received hospital-at-home care compared with those who received inpatient hospital care (mean additional days before readmission comparing hospital-at-home to inpatient hospital care ranged from 4 to 38 days).
There is insufficient evidence to determine whether hospital-at-home care, compared with inpatient hospital care, is associated with improved lung function.
The majority of studies did not find significant differences between hospital-at-home and inpatient hospital care for a variety of health-related quality of life measures at follow-up. However, follow-up may have been too late to observe an impact of hospital-at-home care on quality of life.
A conclusion about the impact of hospital-at-home care on length of stay for the initial exacerbation (defined as days in hospital or days in hospital plus hospital-at-home care for inpatient hospital and hospital-at-home, respectively) could not be determined because of limited and inconsistent evidence.
Patient and caregiver satisfaction with care is high for both hospital-at-home and inpatient hospital care.
PMCID: PMC3384361  PMID: 23074420
11.  A Multifaceted Intervention to Implement Guidelines and Improve Admission Paediatric Care in Kenyan District Hospitals: A Cluster Randomised Trial 
PLoS Medicine  2011;8(4):e1001018.
Philip Ayieko and colleagues report the outcomes of a cluster-randomized trial carried out in eight Kenyan district hospitals evaluating the effects of a complex intervention involving improved training and supervision for clinicians. They found a higher performance of hospitals assigned to the complex intervention on a variety of process of care measures, as compared to those receiving the control intervention.
Background
In developing countries referral of severely ill children from primary care to district hospitals is common, but hospital care is often of poor quality. However, strategies to change multiple paediatric care practices in rural hospitals have rarely been evaluated.
Methods and Findings
This cluster randomized trial was conducted in eight rural Kenyan district hospitals, four of which were randomly assigned to a full intervention aimed at improving quality of clinical care (evidence-based guidelines, training, job aides, local facilitation, supervision, and face-to-face feedback; n = 4) and the remaining four to control intervention (guidelines, didactic training, job aides, and written feedback; n = 4). Prespecified structure, process, and outcome indicators were measured at baseline and during three and five 6-monthly surveys in control and intervention hospitals, respectively. Primary outcomes were process of care measures, assessed at 18 months postbaseline.
In both groups performance improved from baseline. Completion of admission assessment tasks was higher in intervention sites at 18 months (mean = 0.94 versus 0.65, adjusted difference 0.54 [95% confidence interval 0.05–0.29]). Uptake of guideline recommended therapeutic practices was also higher within intervention hospitals: adoption of once daily gentamicin (89.2% versus 74.4%; 17.1% [8.04%–26.1%]); loading dose quinine (91.9% versus 66.7%, 26.3% [−3.66% to 56.3%]); and adequate prescriptions of intravenous fluids for severe dehydration (67.2% versus 40.6%; 29.9% [10.9%–48.9%]). The proportion of children receiving inappropriate doses of drugs in intervention hospitals was lower (quinine dose >40 mg/kg/day; 1.0% versus 7.5%; −6.5% [−12.9% to 0.20%]), and inadequate gentamicin dose (2.2% versus 9.0%; −6.8% [−11.9% to −1.6%]).
Conclusions
Specific efforts are needed to improve hospital care in developing countries. A full, multifaceted intervention was associated with greater changes in practice spanning multiple, high mortality conditions in rural Kenyan hospitals than a partial intervention, providing one model for bridging the evidence to practice gap and improving admission care in similar settings.
Trial registration
Current Controlled Trials ISRCTN42996612
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In 2008, nearly 10 million children died in early childhood. Nearly all these deaths were in low- and middle-income countries—half were in Africa. In Kenya, for example, 74 out every 1,000 children born died before they reached their fifth birthday. About half of all childhood (pediatric) deaths in developing countries are caused by pneumonia, diarrhea, and malaria. Deaths from these common diseases could be prevented if all sick children had access to quality health care in the community (“primary” health care provided by health centers, pharmacists, family doctors, and traditional healers) and in district hospitals (“secondary” health care). Unfortunately, primary health care facilities in developing countries often lack essential diagnostic capabilities and drugs, and pediatric hospital care is frequently inadequate with many deaths occurring soon after admission. Consequently, in 1996, as part of global efforts to reduce childhood illnesses and deaths, the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF) introduced the Integrated Management of Childhood Illnesses (IMCI) strategy. This approach to child health focuses on the well-being of the whole child and aims to improve the case management skills of health care staff at all levels, health systems, and family and community health practices.
Why Was This Study Done?
The implementation of IMCI has been evaluated at the primary health care level, but its implementation in district hospitals has not been evaluated. So, for example, interventions designed to encourage the routine use of WHO disease-specific guidelines in rural pediatric hospitals have not been tested. In this cluster randomized trial, the researchers develop and test a multifaceted intervention designed to improve the implementation of treatment guidelines and admission pediatric care in district hospitals in Kenya. In a cluster randomized trial, groups of patients rather than individual patients are randomly assigned to receive alternative interventions and the outcomes in different “clusters” of patients are compared. In this trial, each cluster is a district hospital.
What Did the Researchers Do and Find?
The researchers randomly assigned eight Kenyan district hospitals to the “full” or “control” intervention, interventions that differed in intensity but that both included more strategies to promote implementation of best practice than are usually applied in Kenyan rural hospitals. The full intervention included provision of clinical practice guidelines and training in their use, six-monthly survey-based hospital assessments followed by face-to-face feedback of survey findings, 5.5 days training for health care workers, provision of job aids such as structured pediatric admission records, external supervision, and the identification of a local facilitator to promote guideline use and to provide on-site problem solving. The control intervention included the provision of clinical practice guidelines (without training in their use) and job aids, six-monthly surveys with written feedback, and a 1.5-day lecture-based seminar to explain the guidelines. The researchers compared the implementation of various processes of care (activities of patients and doctors undertaken to ensure delivery of care) in the intervention and control hospitals at baseline and 18 months later. The performance of both groups of hospitals improved during the trial but more markedly in the intervention hospitals than in the control hospitals. At 18 months, the completion of admission assessment tasks and the uptake of guideline-recommended clinical practices were both higher in the intervention hospitals than in the control hospitals. Moreover, a lower proportion of children received inappropriate doses of drugs such as quinine for malaria in the intervention hospitals than in the control hospitals.
What Do These Findings Mean?
These findings show that specific efforts are needed to improve pediatric care in rural Kenya and suggest that interventions that include more approaches to changing clinical practice may be more effective than interventions that include fewer approaches. These findings are limited by certain aspects of the trial design, such as the small number of participating hospitals, and may not be generalizable to other hospitals in Kenya or to hospitals in other developing countries. Thus, although these findings seem to suggest that efforts to implement and scale up improved secondary pediatric health care will need to include more than the production and dissemination of printed materials, further research including trials or evaluation of test programs are necessary before widespread adoption of any multifaceted approach (which will need to be tailored to local conditions and available resources) can be contemplated.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001018.
WHO provides information on efforts to reduce global child mortality and on Integrated Management of Childhood Illness (IMCI); the WHO pocket book “Hospital care for children contains guidelines for the management of common illnesses with limited resources (available in several languages)
UNICEF also provides information on efforts to reduce child mortality and detailed statistics on child mortality
The iDOC Africa Web site, which is dedicated to improving the delivery of hospital care for children and newborns in Africa, provides links to the clinical guidelines and other resources used in this study
doi:10.1371/journal.pmed.1001018
PMCID: PMC3071366  PMID: 21483712
12.  A Multifaceted Intervention to Improve the Quality of Care of Children in District Hospitals in Kenya: A Cost-Effectiveness Analysis 
PLoS Medicine  2012;9(6):e1001238.
A cost-effective analysis conducted by Edwine Barasa and colleagues estimates that a complex intervention aimed at improving quality of pediatric care would be affordable and cost-effective in Kenya.
Background
To improve care for children in district hospitals in Kenya, a multifaceted approach employing guidelines, training, supervision, feedback, and facilitation was developed, for brevity called the Emergency Triage and Treatment Plus (ETAT+) strategy. We assessed the cost effectiveness of the ETAT+ strategy, in Kenyan hospitals. Further, we estimate the costs of scaling up the intervention to Kenya nationally and potential cost effectiveness at scale.
Methods and Findings
Our cost-effectiveness analysis from the provider's perspective used data from a previously reported cluster randomized trial comparing the full ETAT+ strategy (n = 4 hospitals) with a partial intervention (n = 4 hospitals). Effectiveness was measured using 14 process measures that capture improvements in quality of care; their average was used as a summary measure of quality. Economic costs of the development and implementation of the intervention were determined (2009 US$). Incremental cost-effectiveness ratios were defined as the incremental cost per percentage improvement in (average) quality of care. Probabilistic sensitivity analysis was used to assess uncertainty. The cost per child admission was US$50.74 (95% CI 49.26–67.06) in intervention hospitals compared to US$31.1 (95% CI 30.67–47.18) in control hospitals. Each percentage improvement in average quality of care cost an additional US$0.79 (95% CI 0.19–2.31) per admitted child. The estimated annual cost of nationally scaling up the full intervention was US$3.6 million, approximately 0.6% of the annual child health budget in Kenya. A “what-if” analysis assuming conservative reductions in mortality suggests the incremental cost per disability adjusted life year (DALY) averted by scaling up would vary between US$39.8 and US$398.3.
Conclusion
Improving quality of care at scale nationally with the full ETAT+ strategy may be affordable for low income countries such as Kenya. Resultant plausible reductions in hospital mortality suggest the intervention could be cost-effective when compared to incremental cost-effectiveness ratios of other priority child health interventions.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
According to latest global estimates from UNICEF, 7.6 million children currently die every year before they reach five years of age. Half of these deaths occur in children in sub-Saharan Africa and tragically, most of these deaths are due to a few treatable and preventable diseases, such as pneumonia, malaria, and diarrhea, for which effective interventions are already available. In order to meet the target of the 4th Millennium Development Goal—which aims to reduce the under-five child mortality rate by two-thirds from 1990 levels by 2015—delivering these interventions is essential.
In Kenya, the under-five child mortality rate must be reduced by half from its 2008 level in order to meet the Millennium Development Goal (MDG) target and so improving the management of serious child illness might help achieve this goal. A study published last year in PLoS Medicine described such an approach and included the development and implementation of evidence-based clinical practice guidelines linked to health worker training, follow-up supervision, performance feedback, and facilitation in eight district hospitals in Kenya.
Why Was This Study Done?
In the study mentioned above, the researchers compared the implementation of various processes of care in intervention and control hospitals at baseline and 18 months later and found that performance improved more in the intervention hospitals than in the control hospitals. However, while this strategy was effective at improving the quality of health care, it is unclear whether scaling up the approach would be a good use of limited resources. So in this study, the same researchers performed a cost-effectiveness analysis (which they conducted alongside the original trial) of their quality improvement intervention and estimated the costs and effects of scaling up this approach to cover the entire population of Kenya.
What Did the Researchers Do and Find?
In order to perform the cost part of the analysis, the researchers collected the relevant information on costs by using clinical and accounting record reviews and interviews with those involved in developing and implementing the intervention. The researchers evaluated the effectiveness part of the analysis by comparing the implementation of their improved quality of care strategy as delivered in the intervention hospitals with the partial intervention as delivered in the control hospitals by calculating the mean percentage improvement in the 14 process of care indicators at 18 months. Finally, the researchers calculated the costs of scaling up the intervention by applying their results to the whole of Kenya—121 hospital facilities with an estimated annual child admission rate of 2,000 per facility.
The researchers found that the quality of care (as measured by the process of care indicators) was 25% higher in intervention hospitals than in control hospitals, while the cost per child admission was US$50.74 in intervention hospitals compared to US$31.1 in control hospitals. The researchers calculated that each percentage improvement in the average quality of care was achieved at an additional cost of US$0.79 per admitted child. Extrapolating these results to all of Kenya, the estimated annual cost of scaling up the intervention nationally was US$3.6 million, about 0.6% of the annual child health budget in Kenya.
What Do These Findings Mean?
The findings of this cost-effectiveness analysis suggests that a comprehensive quality improvement intervention is effective at improving standards of care but at an additional cost, which may be relatively cost effective compared with basic care if the improvements observed are associated with decreases in child inpatient mortality. The absolute costs for scaling up are comparable to, or even lower than, costs of other, major child health interventions. As the international community is giving an increasing focus to strengthening health systems, these findings provide a strong case for scaling up this intervention, which improves quality of care and service provision for the major causes of child mortality, in rural hospitals throughout Kenya and other district hospitals in sub-Saharan Africa.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001238.
The researchers' original article appeared in PLoS Medicine in 2011: Ayieko P, Ntoburi S, Wagai J, Opondo C, Opiyo N, et al. (2011) A Multifaceted Intervention to Implement Guidelines and Improve Admission Paediatric Care in Kenyan District Hospitals: A Cluster Randomised Trial. PLoS Med 8(4): e1001018. doi:10.1371/journal.pmed.1001018
The IDOC Africa provides further information on the ETAT+ strategy
The World Health Organization (WHO) provides information on MDG 4, including strategies to reduce global child mortality) and the WHO pocket-book “Hospital care for children” includes guidelines for the management of common but serious childhood illnesses in resource-limited settings
UNICEF www.unicef.org also publishes information on global child mortality rates and the Countdown to 2015 website tracks coverage levels for health interventions proven to reduce child mortality
doi:10.1371/journal.pmed.1001238
PMCID: PMC3373608  PMID: 22719233
13.  The Effectiveness of Mobile-Health Technologies to Improve Health Care Service Delivery Processes: A Systematic Review and Meta-Analysis 
PLoS Medicine  2013;10(1):e1001363.
Caroline Free and colleagues systematically review controlled trials of mobile technology interventions to improve health care delivery processes and show that current interventions give only modest benefits and that high-quality trials measuring clinical outcomes are needed.
Background
Mobile health interventions could have beneficial effects on health care delivery processes. We aimed to conduct a systematic review of controlled trials of mobile technology interventions to improve health care delivery processes.
Methods and Findings
We searched for all controlled trials of mobile technology based health interventions using MEDLINE, EMBASE, PsycINFO, Global Health, Web of Science, Cochrane Library, UK NHS HTA (Jan 1990–Sept 2010). Two authors independently extracted data on allocation concealment, allocation sequence, blinding, completeness of follow-up, and measures of effect. We calculated effect estimates and we used random effects meta-analysis to give pooled estimates.
We identified 42 trials. None of the trials had low risk of bias. Seven trials of health care provider support reported 25 outcomes regarding appropriate disease management, of which 11 showed statistically significant benefits. One trial reported a statistically significant improvement in nurse/surgeon communication using mobile phones. Two trials reported statistically significant reductions in correct diagnoses using mobile technology photos compared to gold standard. The pooled effect on appointment attendance using text message (short message service or SMS) reminders versus no reminder was increased, with a relative risk (RR) of 1.06 (95% CI 1.05–1.07, I2 = 6%). The pooled effects on the number of cancelled appointments was not significantly increased RR 1.08 (95% CI 0.89–1.30). There was no difference in attendance using SMS reminders versus other reminders (RR 0.98, 95% CI 0.94–1.02, respectively). To address the limitation of the older search, we also reviewed more recent literature.
Conclusions
The results for health care provider support interventions on diagnosis and management outcomes are generally consistent with modest benefits. Trials using mobile technology-based photos reported reductions in correct diagnoses when compared to the gold standard. SMS appointment reminders have modest benefits and may be appropriate for implementation. High quality trials measuring clinical outcomes are needed.
Please see later in the article for the Editors' Summary
Editors’ Summary
Background
Over the past few decades, computing and communication technologies have changed dramatically. Bulky, slow computers have been replaced by portable devices that can complete increasingly complex tasks in less and less time. Similarly, landlines have been replaced by mobile phones and other mobile communication technologies that can connect people anytime and anywhere, and that can transmit text messages (short message service; SMS), photographs, and data at the touch of a button. These advances have led to the development of mobile-health (mHealth)—the use of mobile computing and communication technologies in health care and public health. mHealth has many applications. It can be used to facilitate data collection and to encourage health-care consumers to adopt healthy lifestyles or to self-manage chronic conditions. It can also be used to improve health-care service delivery processes by targeting health-care providers or communication between these providers and their patients. So, for example, mobile technologies can be used to provide clinical management support in settings where there are no specialist clinicians, and they can be used to send patients test results and timely reminders of appointments.
Why Was This Study Done?
Many experts believe that mHealth interventions could greatly improve health-care delivery processes, particularly in resource-poor settings. The results of several controlled trials (studies that compare the outcomes of people who do or do not receive an intervention) of mHealth interventions designed to improve health-care delivery processes have been published. However, these data have not been comprehensively reviewed, and the effectiveness of this type of mHealth intervention has not been quantified. Here, the researchers rectify this situation by undertaking a systematic review and meta-analysis of controlled trials of mobile technology-based interventions designed to improve health-care service delivery processes. A systematic review is a study that uses predefined criteria to identify all the research on a given topic; a meta-analysis is a statistical approach that is used to pool the results of several independent studies.
What Did the Researchers Do and Find?
The researchers identified 42 controlled trials that investigated mobile technology-based interventions designed to improve health-care service delivery processes. None of the trials were of high quality—many had methodological problems likely to affect the accuracy of their findings—and nearly all were undertaken in high-income countries. Thirty-two of the trials tested interventions directed at health-care providers. Of these trials, seven investigated interventions providing health-care provider education, 18 investigated interventions supporting clinical diagnosis and treatment, and seven investigated interventions to facilitate communication between health-care providers. Several of the trials reported that the tested intervention led to statistically significant improvements (improvements unlikely to have happened by chance) in outcomes related to disease management. However, two trials that used mobile phones to transmit photos to off-site clinicians for diagnosis reported significant reductions in correct diagnoses compared to diagnosis by an on-site specialist. Ten of the 42 trials investigated interventions targeting communication between health-care providers and patients. Eight of these trials investigated SMS-based appointment reminders. Meta-analyses of the results of these trials indicated that using SMS appointment reminders significantly but modestly increased patient attendance compared to no reminders. However, SMS reminders were no more effective than postal or phone call reminders, and texting reminders to patients who persistently missed appointments did not significantly change the number of cancelled appointments.
What Do These Findings Mean?
These findings indicate that some mHealth interventions designed to improve health-care service delivery processes are modestly effective, but they also highlight the need for more trials of these interventions. Specifically, these findings show that although some interventions designed to provide support for health-care providers modestly improved some aspects of clinical diagnosis and management, other interventions had deleterious effects—most notably, the use of mobile technology–based photos for diagnosis. In terms of mHealth interventions targeting communication between health-care providers and patients, the finding that SMS appointment reminders have modest benefits suggests that implementation of this intervention should be considered, at least in high-income settings. However, the researchers stress that more trials are needed to robustly establish the ability of mobile technology-based interventions to improve health-care delivery processes. These trials need to be of high quality, they should be undertaken in resource-limited settings as well as in high-income countries, and, ideally, they should consider interventions that combine mHealth and conventional approaches.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001363.
A related PLOS Medicine Research Article by Free et al. investigates the effectiveness of mHealth technology-based health behavior change and disease management interventions for health-care consumers
Wikipedia has a page on mHealth (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
mHealth: New horizons for health through mobile technologies is a global survey of mHealth prepared by the World Health Organization’s Global Observatory for eHealth (eHealth is health-care practice supported by electronic processes and communication)
The mHealth in Low-Resource Settings website, which is maintained by the Netherlands Royal Tropical Institute, provides information on the current use, potential, and limitations of mHealth in low-resource settings
The US National Institutes of Health Fogarty International Center provides links to resources and information about mHealth
doi:10.1371/journal.pmed.1001363
PMCID: PMC3566926  PMID: 23458994
14.  Uncovering Treatment Burden as a Key Concept for Stroke Care: A Systematic Review of Qualitative Research 
PLoS Medicine  2013;10(6):e1001473.
In a systematic review of qualitative research, Katie Gallacher and colleagues examine the evidence related to treatment burden after stroke from the patient perspective.
Please see later in the article for the Editors' Summary
Background
Patients with chronic disease may experience complicated management plans requiring significant personal investment. This has been termed ‘treatment burden’ and has been associated with unfavourable outcomes. The aim of this systematic review is to examine the qualitative literature on treatment burden in stroke from the patient perspective.
Methods and Findings
The search strategy centred on: stroke, treatment burden, patient experience, and qualitative methods. We searched: Scopus, CINAHL, Embase, Medline, and PsycINFO. We tracked references, footnotes, and citations. Restrictions included: English language, date of publication January 2000 until February 2013. Two reviewers independently carried out the following: paper screening, data extraction, and data analysis. Data were analysed using framework synthesis, as informed by Normalization Process Theory. Sixty-nine papers were included. Treatment burden includes: (1) making sense of stroke management and planning care, (2) interacting with others, (3) enacting management strategies, and (4) reflecting on management. Health care is fragmented, with poor communication between patient and health care providers. Patients report inadequate information provision. Inpatient care is unsatisfactory, with a perceived lack of empathy from professionals and a shortage of stimulating activities on the ward. Discharge services are poorly coordinated, and accessing health and social care in the community is difficult. The study has potential limitations because it was restricted to studies published in English only and data from low-income countries were scarce.
Conclusions
Stroke management is extremely demanding for patients, and treatment burden is influenced by micro and macro organisation of health services. Knowledge deficits mean patients are ill equipped to organise their care and develop coping strategies, making adherence less likely. There is a need to transform the approach to care provision so that services are configured to prioritise patient needs rather than those of health care systems.
Systematic Review Registration
International Prospective Register of Systematic Reviews CRD42011001123
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every year, 15 million people have a stroke. About 5 million of these people die within a few days, and another 5 million are left disabled. Stroke occurs when the blood supply of the brain is suddenly interrupted by a blood vessel in the brain being blocked by a blood clot (ischemic stroke) or bursting (hemorrhagic stroke). Deprived of the oxygen normally carried to them by the blood, the brain cells near the blockage die. The symptoms of stroke depend on which part of the brain is damaged but include sudden weakness or paralysis along one side of the body, vision loss in one or both eyes, and confusion or trouble speaking or understanding speech. Anyone experiencing these symptoms should seek immediate medical attention because prompt treatment can limit the damage to the brain. In the longer term, post-stroke rehabilitation can help individuals overcome the physical disabilities caused by stroke, and drugs that thin the blood, reduce blood pressure and reduce cholesterol (major risk factors for stroke) alongside behavioral counseling can reduce the risk of a second stroke.
Why Was This Study Done?
Treatment for, and rehabilitation from, stroke is a lengthy process that requires considerable personal investment from the patient. The term “treatment burden” describes the self-care practices that patients with stroke and other chronic diseases must perform to follow the complicated management strategies that have been developed for these conditions. Unfortunately, treatment burden can overwhelm patients. They may be unable to cope with the multiple demands placed on them by health-care providers and systems for their self-care, a situation that leads to poor adherence to therapies and poor outcomes. For example, patients may find it hard to complete all the exercises designed to help them regain full movement of their limbs after a stroke. Treatment burden has been poorly examined in relation to stroke. Here, the researchers identify and describe the treatment burden in stroke by undertaking a systematic review (a study that uses predefined criteria to identify all the literature on a given topic) of qualitative studies on the patient experience of stroke management. Qualitative studies collect non-quantitative data so, for example, a qualitative study on stroke treatment might ask people how the treatment made them feel whereas a quantitative study might compare clinical outcomes between those receiving and not receiving the treatment.
What Did the Researchers Do and Find?
The researchers identified 69 qualitative studies dealing with the experiences of stroke management of adult patients and analyzed the data in these papers using framework synthesis—an approach that divides data into thematic categories. Specifically, the researchers used a coding framework informed by normalization process theory, a sociological theory of the implementation, embedding and integration of tasks and practices; embedding is the process of making tasks and practices a routine part of everyday life and integration refers to sustaining these embedded practices. The researchers identified four main areas of treatment burden for stroke: making sense of stroke management and planning care; interacting with others, including health care professionals, family and other patients with stroke; enacting management strategies (including enduring institutional admissions, managing stroke in the community, reintegrating into society and adjusting to life after stroke); and reflecting on management to make decisions about self-care. Moreover, they identified problems in all these areas, including inadequate provision of information, poor communication with health-care providers, and unsatisfactory inpatient care.
What Do These Findings Mean?
These findings show that stroke management is extremely demanding for patients and is influenced by both the micro and macro organization of health services. At the micro organizational level, fragmented care and poor communication between patients and clinicians and between health-care providers can mean patients are ill equipped to organize their care and develop coping strategies, which makes adherence to management strategies less likely. At the macro organizational level, it can be hard for patients to obtain the practical and financial help they need to manage their stroke in the community. Overall, these findings suggest that care provision for stroke needs to be transformed so that the needs of patients rather than the needs of health-care systems are prioritized. Further work is required, however, to understand how the patient experience of treatment burden is affected by the clinical characteristics of stroke, by disability level, and by other co-existing diseases. By undertaking such work, it should be possible to generate a patient-reported outcome measure of treatment burden that, if used by policy makers and health-care providers, has the potential to improve the quality of stroke care.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001473.
The US National Institute of Neurological Disorders and Stroke provides information about all aspects of stroke (in English and Spanish); its Know Stroke site provides educational materials about stroke prevention, treatment, and rehabilitation including personal stories (in English and Spanish); the US National Institutes of Health SeniorHealth website has additional information about stroke
The Internet Stroke Center provides detailed information about stroke for patients, families, and health professionals (in English and Spanish)
The UK National Health Service Choices website also provides information about stroke for patients and their families, including personal stories
MedlinePlus has links to additional resources about stroke (in English and Spanish)
The UK not-for-profit website Healthtalkonline provides personal stories about stroke
Wikipedia provides information on the burden of treatment and on the normalization process theory (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1001473
PMCID: PMC3692487  PMID: 23824703
15.  Access To Essential Maternal Health Interventions and Human Rights Violations among Vulnerable Communities in Eastern Burma 
PLoS Medicine  2008;5(12):e242.
Background
Health indicators are poor and human rights violations are widespread in eastern Burma. Reproductive and maternal health indicators have not been measured in this setting but are necessary as part of an evaluation of a multi-ethnic pilot project exploring strategies to increase access to essential maternal health interventions. The goal of this study is to estimate coverage of maternal health services prior to this project and associations between exposure to human rights violations and access to such services.
Methods and Findings
Selected communities in the Shan, Mon, Karen, and Karenni regions of eastern Burma that were accessible to community-based organizations operating from Thailand were surveyed to estimate coverage of reproductive, maternal, and family planning services, and to assess exposure to household-level human rights violations within the pilot-project target population. Two-stage cluster sampling surveys among ever-married women of reproductive age (15–45 y) documented access to essential antenatal care interventions, skilled attendance at birth, postnatal care, and family planning services. Mid-upper arm circumference, hemoglobin by color scale, and Plasmodium falciparum parasitemia by rapid diagnostic dipstick were measured. Exposure to human rights violations in the prior 12 mo was recorded. Between September 2006 and January 2007, 2,914 surveys were conducted. Eighty-eight percent of women reported a home delivery for their last pregnancy (within previous 5 y). Skilled attendance at birth (5.1%), any (39.3%) or ≥ 4 (16.7%) antenatal visits, use of an insecticide-treated bed net (21.6%), and receipt of iron supplements (11.8%) were low. At the time of the survey, more than 60% of women had hemoglobin level estimates ≤ 11.0 g/dl and 7.2% were Pf positive. Unmet need for contraceptives exceeded 60%. Violations of rights were widely reported: 32.1% of Karenni households reported forced labor and 10% of Karen households had been forced to move. Among Karen households, odds of anemia were 1.51 (95% confidence interval [CI] 0.95–2.40) times higher among women reporting forced displacement, and 7.47 (95% CI 2.21–25.3) higher among those exposed to food security violations. The odds of receiving no antenatal care services were 5.94 (95% CI 2.23–15.8) times higher among those forcibly displaced.
Conclusions
Coverage of basic maternal health interventions is woefully inadequate in these selected populations and substantially lower than even the national estimates for Burma, among the lowest in the region. Considerable political, financial, and human resources are necessary to improve access to maternal health care in these communities.
Luke Mullany and colleagues examine access to essential maternal health interventions and human rights violations within vulnerable communities in eastern Burma.
Editors' Summary
Background.
After decades of military rule, Burma has one of the world's worst health-care systems and high levels of ill health. For example, maternal mortality (deaths among women from pregnancy-related causes) is around 360 per 100,000 live births in Burma, whereas in neighboring Thailand it is only 44 per 100,000 live births. Maternal health is even worse in the Shan, Karenni, Karen and Mon states in eastern Burma where ethnic conflicts and enforced village relocations have internally displaced more than half a million people. Here, maternal mortality is thought to be about 1000 per 100, 000 live births. In an effort to improve access to life-saving maternal health interventions in these states, Burmese community-based health organizations, the Johns Hopkins Center for Public Health and Human Rights and the Global Health Access Program in the USA, and the Mae Tao Clinic (a health-worker training center in Thailand) recently set up the Mobile Obstetric Maternal Health Workers (MOM) Project. In this pilot project, local health workers from 12 communities in eastern Burma received training in antenatal care, emergency obstetrics (the care of women during childbirth), blood transfusion, and family planning at the Mae Tao Clinic. Back in Burma, these maternal health workers trained additional local health workers and traditional birth attendants. All these individuals now provide maternal health care to their communities.
Why Was This Study Done?
The effectiveness of the MOM project can only be evaluated if accurate baseline information on women's access to maternal health-care services is available. This information is also needed to ensure the wise use of scarce health-care resources. However, very little is known about reproductive and maternal health in eastern Burma. In this study, the researchers analyze the information on women's access to reproductive and maternal health-care services that was collected during the initial field implementation stage of the MOM project. In addition, they analyze whether exposure to enforced village relocations and other human rights violations affect access to maternal health-care services.
What Did the Researchers Do and Find?
Trained survey workers asked nearly 3000 ever-married women of reproductive age in the selected communities about their access to antenatal and postnatal care, skilled birth attendants, and family planning. They measured each woman's mid-upper arm circumference (an indicator of nutritional status) and tested them for anemia (iron deficiency) and infection with malaria parasites (a common cause of anemia in tropical countries). Finally, they asked the women about any recent violations of their human rights such as forced labour or relocation. Nearly 90% of the women reported a home delivery for their last baby. A skilled attendant was present at only one in 20 births and only one in three women had any antenatal care. One third of the women received postnatal care and only a third said they had access to effective contraceptives. Few women had received iron supplements or had used insecticide-treated bednets to avoid malaria-carrying mosquitos. Consequently, more than half the women were anemic and 7.2% were infected with malaria parasites. Many women also showed signs of poor nutrition. Finally, human rights violations were widely reported by the women. In Karen, the region containing most of the study communities, forced relocation tripled the risk of women developing anemia and greatly decreased their chances of receiving any antenatal care.
What Do These Findings Mean?
These findings show that access to maternal health-care interventions is extremely limited and that poor nutrition, anemia, and malaria, all of which increase the risk of pregnancy complications, are widespread in the communities in the MOM project. Because these communities had some basic health services and access to training in Thailand before the project started, these results probably underestimate the lack of access to maternal health-care services in eastern Burma. Nevertheless, it is clear that considerable political, financial, and human resources will be needed to improve maternal health in this region. Finally, the findings also reveal a link between human rights violations and reduced access to maternal health-care services. Thus, the scale of human rights violations will need to be considered when evaluating programs designed to improve maternal health in Burma and in other places where there is ongoing conflict.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050242.
This research article is further discussed in a PLoS Medicine Perspective by Macaya Douoguih
The World Health Organization provides information on all aspects of health in Burma (in several languages)
The Mae Tao Clinic also provides general information about Burma and its health services
More information about the MOM project is available in a previous publication by the researchers
The Burma Campaign UK and Human Rights Watch both provide detailed information about human rights violations in Burma
The United Nations Population Fund provides information about safe motherhood and ongoing efforts to save mothers' lives around the world
doi:10.1371/journal.pmed.0050242
PMCID: PMC2605890  PMID: 19108601
16.  Quality of Private and Public Ambulatory Health Care in Low and Middle Income Countries: Systematic Review of Comparative Studies 
PLoS Medicine  2011;8(4):e1000433.
Paul Garner and colleagues conducted a systematic review of 80 studies to compare the quality of private versus public ambulatory health care in low- and middle-income countries.
Background
In developing countries, the private sector provides a substantial proportion of primary health care to low income groups for communicable and non-communicable diseases. These providers are therefore central to improving health outcomes. We need to know how their services compare to those of the public sector to inform policy options.
Methods and Findings
We summarised reliable research comparing the quality of formal private versus public ambulatory health care in low and middle income countries. We selected studies against inclusion criteria following a comprehensive search, yielding 80 studies. We compared quality under standard categories, converted values to a linear 100% scale, calculated differences between providers within studies, and summarised median values of the differences across studies. As the results for for-profit and not-for-profit providers were similar, we combined them. Overall, median values indicated that many services, irrespective of whether public or private, scored low on infrastructure, clinical competence, and practice. Overall, the private sector performed better in relation to drug supply, responsiveness, and effort. No difference between provider groups was detected for patient satisfaction or competence. Synthesis of qualitative components indicates the private sector is more client centred.
Conclusions
Although data are limited, quality in both provider groups seems poor, with the private sector performing better in drug availability and aspects of delivery of care, including responsiveness and effort, and possibly being more client orientated. Strategies seeking to influence quality in both groups are needed to improve care delivery and outcomes for the poor, including managing the increasing burden of non-communicable diseases.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
The provision of private (“for-profit” hospitals and self-employed practitioners, and “not-for-profit” non-government providers, including faith-based organizations) versus public health care services in low and middle income countries raises considerable ideological debate. Ideological arguments aside—which can be very passionate on both sides—there is general agreement that improving the quality of both public and private health care could have a major impact on improved health outcomes, especially as the private sector is so widely used in low and middle income countries. For example, almost three quarters and half of children from the poorest households of South Asia and sub-Saharan Africa, respectively, seek health care from a private provider when they are ill. Private providers are also increasingly responsible for outpatient care for non-communicable diseases.
As a result of the mixed health care system in many low and middle income countries, adequate oversight and stewardship of the mixed system from the national government is essential yet often missing.
Why Was This Study Done?
An understanding of how quality and performance in the private sector compares with that in the public sector would help governments to prioritize where they need to concentrate their efforts. So, for example, if the private sector is generally providing poorer quality care than the public sector, then there is an imperative to improve the quality and outcomes; on the other hand, if the quality of care offered by the private sector is good, the policy priority is to influence the market to further improve access to such health care for low income groups.
In order to help with this comparison, the researchers wanted to systematically identify and summarize the results of studies that directly compared the quality of care offered by public providers with the one offered by “formal” private providers (recognized by law) and “informal” private providers (providers that are not legally recognized, such as lay health workers and shop keepers). For the purposes of this study the researchers focused their comparison on the private and public provision of outpatient care in low and middle income countries.
What Did the Researchers Do and Find?
In their literature review, the researchers searched for relevant studies reported in English, French, or German and published between January 1970 and April 2009. Only studies that compared private and public outpatient medical services in the same country, at the same time, using the same methods, and which met particular quality criteria, were included in the analysis. The researchers also had strict criteria for including qualitative studies, and they retrieved the full text of articles, contacted study authors where appropriate, and verified with a second researcher most (80%) of the extracted study data. In order to evaluate and compare the studies, the researchers converted study values to a linear 100% scale, calculated differences between providers within studies, and summarized the median values of the differences across studies.
The researchers identified a total of 8,812 relevant titles and abstracts and found 80 studies that included direct quantitative comparisons of public and private formal providers. Ten studies included qualitative data. Most studies were conducted after 1990, and mainly in sub-Saharan Africa (n = 39) and Asia and the Pacific (n = 23). Most studies did not report socio-economic status of public and private service users, and only five studies presented data by different income groups. No study compared the same individual providers working in public and private care settings. Only two studies compared public providers and private informal providers, so the authors excluded these from subsequent analysis.
For the formal sector, since the results for “for-profit” and “not-for-profit” providers were similar, the researchers decided to combine the results. Overall, the researchers found that the median values indicated that many services, irrespective of whether public or private, scored low (less than 50%) on infrastructure, clinical competence, and practice. Generally, the private sector performed better in relation to drug supply, responsiveness, and effort, but there was no detectable difference between provider groups for patient satisfaction. Furthermore, a synthesis of qualitative data suggested that the private sector may be more client-centered.
What Do These Findings Mean?
Based on the findings of this review, there is a clear need to consider the quality of primary health services in both the public and private sector in order to improve health outcomes in low and middle income countries. These findings also indicate that, for some aspects of care, on average the private sector provided better quality services. The overall low quality of care in both the formal private and public sector found in this review is worrying, and calls for the governments of low and middle income countries to find and implement effective strategies to improve the quality in both sectors. This is particularly important given the increasing volume of conditions that require relatively sophisticated, long-term ambulatory medical care, such as non-communicable diseases.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000433.
This study is further discussed in a PLoS Medicine Perspective by Jishnu Das
WHO has more information on health service delivery in low- and middle-income countries
WHO has more information on noncommunicable diseases
The World Bank's World Development Report for 2004 addresses health care for poor people
doi:10.1371/journal.pmed.1000433
PMCID: PMC3075233  PMID: 21532746
17.  The Effectiveness of Emergency Obstetric Referral Interventions in Developing Country Settings: A Systematic Review 
PLoS Medicine  2012;9(7):e1001264.
In a systematic review of the literature, Julia Hussein and colleagues seek to determine the effect of referral interventions that enable emergency access to health facilities for pregnant women living in developing countries.
Background
Pregnancy complications can be unpredictable and many women in developing countries cannot access health facilities where life-saving care is available. This study assesses the effects of referral interventions that enable pregnant women to reach health facilities during an emergency, after the decision to seek care is made.
Methods and findings
Selected bibliographic databases were searched with no date or language restrictions. Randomised controlled trials and quasi experimental study designs with a comparison group were included. Outcomes of interest included maternal and neonatal mortality and other intermediate measures such as service utilisation. Two reviewers independently selected, appraised, and extracted articles using predefined fields. Forest plots, tables, and qualitative summaries of study quality, size, and direction of effect were used for analysis.
Nineteen studies were included. In South Asian settings, four studies of organisational interventions in communities that generated funds for transport reduced neonatal deaths, with the largest effect seen in India (odds ratio 0·48 95% CI 0·34–0·68). Three quasi experimental studies from sub-Saharan Africa reported reductions in stillbirths with maternity waiting home interventions, with one statistically significant result (OR 0.56 95% CI 0.32–0.96). Effects of interventions on maternal mortality were unclear. Referral interventions usually improved utilisation of health services but the opposite effect was also documented. The effects of multiple interventions in the studies could not be disentangled. Explanatory mechanisms through which the interventions worked could not be ascertained.
Conclusions
Community mobilisation interventions may reduce neonatal mortality but the contribution of referral components cannot be ascertained. The reduction in stillbirth rates resulting from maternity waiting homes needs further study. Referral interventions can have unexpected adverse effects. To inform the implementation of effective referral interventions, improved monitoring and evaluation practices are necessary, along with studies that develop better understanding of how interventions work.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every year, about 350,000 women die from pregnancy- or childbirth-related complications. Almost all of these “maternal” deaths occur in developing countries. In sub-Saharan Africa, for example, the maternal mortality ratio (MMR, the number of maternal deaths per 100,000 live births) is 500 and a woman's life-time risk of dying from complications of pregnancy or childbirth is 1 in 39. By contrast, the MMR in industrialized countries is 12 and women have a life-time risk of maternal death of 1 in 4,700. Most maternal deaths are caused by hemorrhage (severe bleeding after childbirth), post-delivery infections, obstructed (difficult) labor, and blood pressure disorders during pregnancy, all of which are preventable or treatable conditions. Unfortunately, it is hard to predict which women will develop pregnancy complications, many complications rapidly become life-threatening and, in developing countries, women often deliver at home, far from emergency obstetric services; obstetrics deals with the care of women and their children during pregnancy, childbirth, and the postnatal period.
Why Was This Study Done?
It should be possible to reduce maternal deaths (and the deaths of babies during pregnancy, childbirth, and early life) in developing countries by ensuring that pregnant women are referred to emergency obstetric services quickly when the need arises. Unfortunately, in such countries referral to emergency obstetric care is beset with problems such as difficult geographical terrain, transport costs, lack of vehicles, and suboptimal location and distribution of health care facilities. In this systematic review (a study that uses predefined criteria to identify all the research on a given topic), the researchers assess the effectiveness of interventions designed to reduce the “phase II delay” in referral to emergency obstetric care in developing countries—the time it takes a woman to reach an appropriate health care facility once a problem has been recognized and the decision has been taken to seek care. Delays in diagnosis and the decision to seek care are phase I delays in referral, whereas delays in receiving care once a women reaches a health care facility are phase III delays.
What Did the Researchers Do and Find?
The researchers identified 19 published studies that described 14 interventions designed to overcome phase II delays in emergency obstetric referral and that met their criteria for inclusion in their systematic review. About half of the interventions were organizational. That is, they were designed to overcome barriers to referral such as costs. Most of the remaining interventions were structural. That is, they involved the provision of, for example, ambulances and maternity waiting homes—placed close to a health care facility where women can stay during late pregnancy. Although seven studies provided data on maternal mortality, none showed a sustained, statistically significant reduction (a reduction unlikely to have occurred by chance) in maternal deaths. Four studies in South Asia in which communities generated funds for transport reduced neonatal deaths (deaths of babies soon after birth), but the only statistically significant effect of this community mobilization intervention was seen in India where neonatal deaths were halved. Three studies from sub-Saharan Africa reported that the introduction of maternity waiting homes reduced stillbirths but this reduction was only significant in one study. Finally, although referral interventions generally improved the utilization of health services, in one study the provision of bicycle ambulances to take women to the hospital reduced the proportion of women delivering in health facilities, probably because women felt that bicycle ambulances drew unwanted attention to them during labor and so preferred to stay at home.
What Do These Findings Mean?
These findings suggest that community mobilization interventions may reduce neonatal mortality and that maternity waiting rooms may reduce stillbirths. Importantly, they also highlight how referral interventions can have unexpected adverse effects. However, because the studies included in this systematic review included multiple interventions designed to reduce delays at several stages of the referral process, it is not possible to disentangle the contribution of each component of the intervention. Moreover, it is impossible at present to determine why (or even if) any of the interventions reduced maternal mortality. Thus, the researchers conclude, improved monitoring of interventions and better evaluation of outcomes is essential to inform the implementation of effective referral interventions, and more studies are needed to improve understanding of how referral interventions work.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001264.
The United Nations Children's Fund (UNICEF) provides information on maternal mortality, including the WHO/UNICEF./UNFPA/World Bank 2008 country estimates of maternal mortality
The World Health Organization provides information on maternal health, including information about Millennium Development Goal 5, which aims to reduce maternal mortality (in several languages); the Millennium Development Goals, which were agreed by world leaders in 2000, are designed to eradicate extreme poverty worldwide by 2015
Immpact is a global research initiative for the evaluation of safe motherhood intervention strategies
Veil of Tears contains personal stories from Afghanistan about loss in childbirth; the non-governmental health development organization AMREF provides personal stories about maternal health in Africa
Maternal Death: The Avoidable Crisis is a briefing paper published by Médecins Sans Frontières (MSF) in March 2012
doi:10.1371/journal.pmed.1001264
PMCID: PMC3393680  PMID: 22807658
18.  Patient-Safety-Related Hospital Deaths in England: Thematic Analysis of Incidents Reported to a National Database, 2010–2012 
PLoS Medicine  2014;11(6):e1001667.
Sukhmeet Panesar and colleagues classified reports of patient-safety-related hospital deaths in England to identify patterns of cases where improvements might be possible.
Please see later in the article for the Editors' Summary
Background
Hospital mortality is increasingly being regarded as a key indicator of patient safety, yet methodologies for assessing mortality are frequently contested and seldom point directly to areas of risk and solutions. The aim of our study was to classify reports of deaths due to unsafe care into broad areas of systemic failure capable of being addressed by stronger policies, procedures, and practices. The deaths were reported to a patient safety incident reporting system after mandatory reporting of such incidents was introduced.
Methods and Findings
The UK National Health Service database was searched for incidents resulting in a reported death of an adult over the period of the study. The study population comprised 2,010 incidents involving patients aged 16 y and over in acute hospital settings. Each incident report was reviewed by two of the authors, and, by scrutinising the structured information together with the free text, a main reason for the harm was identified and recorded as one of 18 incident types. These incident types were then aggregated into six areas of apparent systemic failure: mismanagement of deterioration (35%), failure of prevention (26%), deficient checking and oversight (11%), dysfunctional patient flow (10%), equipment-related errors (6%), and other (12%). The most common incident types were failure to act on or recognise deterioration (23%), inpatient falls (10%), healthcare-associated infections (10%), unexpected per-operative death (6%), and poor or inadequate handover (5%). Analysis of these 2,010 fatal incidents reveals patterns of issues that point to actionable areas for improvement.
Conclusions
Our approach demonstrates the potential utility of patient safety incident reports in identifying areas of service failure and highlights opportunities for corrective action to save lives.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Being admitted to the hospital is worrying for patients and for their relatives. Will the patient recover or die in the hospital? Some seriously ill patients will inevitably die, but in an ideal world, no one should die in the hospital because of inadequate or unsafe care (an avoidable death). No one should die, for example, because healthcare professionals fail to act on signs that indicate a decline in a patient's clinical condition. Hospital mortality (death) is often regarded as a key indicator of patient safety in hospitals, and death rate indicators such as the “hospital standardized mortality ratio” (the ratio of the actual number of acute in-hospital deaths to the expected number of in-hospital deaths) are widely used to monitor and improve hospital safety standards. In England, for example, a 2012 report that included this measure as an indicator of hospital performance led to headlines of “worryingly high” hospital death rates and to a review of the quality of care in the hospitals with the highest death rates.
Why Was This Study Done?
Hospital standardized mortality ratios and other measures of in-patient mortality can be misleading because they can, for example, reflect the burden of disease near the hospital rather than the hospital's quality of care or safety levels. Moreover, comparative data on hospital mortality rates are of limited value in identifying areas of risk to patients or solutions to the problem of avoidable deaths. In this study, to identify areas of service failure amenable to improvement through strengthened clinical policies, procedures, and practices, the researchers undertake a thematic analysis of deaths in hospitals in England that were reported by healthcare staff to a mandatory patient-safety-related incident reporting system. Since 2004, staff in the UK National Health Service (the NHS comprises the publicly funded healthcare systems in England, Scotland, Wales, and Northern Ireland) have been encouraged to report any unintended or unexpected incident in which they believe a patient's safety was compromised. Since June 2010, it has been mandatory for staff in England and Wales to report deaths due to patient-safety-related incidents. A thematic analysis examines patterns (“themes”) within nonnumerical (qualitative) data.
What Did the Researchers Do and Find?
By searching the NHS database of patient-safety-related incidents, the researchers identified 2010 incidents that occurred between 1 June 2010 and 31 October 2012 that resulted in the death of adult patients in acute hospital settings. By scrutinizing the structured information in each incident report and the associated free text in which the reporter described what happened and why they think it happened, the researchers classified the reports into 18 incident categories. These categories fell into six broad areas of systemic failure—mismanagement of deterioration (35% of incidents), failure of prevention (26%), deficient checking and oversight (11%), dysfunctional patient flow (10%), equipment-related errors (6%), and other (12%, incidents where the problem underlying death was unclear). Management of deterioration, for example, included the incident categories “failure to act on or recognize deterioration” (23% of reported incidents), “failure to give ordered treatment/support in a timely manner,” and “failure to observe.” Failure of prevention included the incident categories “falls” (10% of reported incidents), “healthcare-associated infections” (also 10% of reported incidents), “pressure sores,” “suicides,” and “deep vein thrombosis/pulmonary embolism.”
What Do These Findings Mean?
Although the accuracy of these findings may be limited by data quality and by other aspects of the study design, they reveal patterns of patient-safety-related deaths in hospitals in England and highlight areas of healthcare that can be targeted for improvement. The finding that the mismanagement of deterioration of acutely ill patients is involved in a third of patient-safety-related deaths identifies an area of particular concern in the NHS and, potentially, in other healthcare systems. One way to reduce deaths associated with the mismanagement of deterioration, suggest the researchers, might be to introduce a standardized early warning score to ensure uniform identification of this population of patients. The researchers also suggest that more effort should be put into designing programs to prevent falls and other incidents and into ensuring that these programs are effectively implemented. More generally, the classification system developed here has the potential to help hospital boards and clinicians identify areas of patient care that require greater scrutiny and intervention and thereby save the lives of many hospital patients.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001667.
The NHS provides information about patient safety, including a definition of a patient safety incident and information on reporting patient safety incidents
The NHS Choices website includes several “Behind the Headlines” articles that discuss patient safety in hospitals, including an article that discusses the 2012 report of high hospital death rates in England, “Fit for the Future?” and another that discusses the Keogh review of the quality of care in the hospitals with highest death rates
The US Agency for Healthcare Research and Quality provides information on patient safety in the US
Wikipedia has pages on thematic analysis and on patient safety (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1001667
PMCID: PMC4068985  PMID: 24959751
19.  Utilization and expenditures of veterans obtaining primary care in community clinics and VA medical centers: an observational cohort study 
Background
To compare VA inpatient and outpatient utilization and expenditures of veterans seeking primary care in community-based outpatient clinics (CBOCs) and VA medical centers (VAMCs) in fiscal years 2000 (FY00) and 2001.
Methods
The sample included 25,092 patients who obtained primary care exclusively from 108 CBOCs in FY00, 26,936 patients who obtained primary care exclusively from 72 affiliated VAMCs in FY00, and 11,450 "crossover" patients who obtained primary care in CBOCs and VAMCs in FY00. VA utilization and expenditure data were drawn from the VA's system-wide cost accounting system. Veteran demographic characteristics and a 1999 Diagnostic Cost Group risk score were obtained from VA administrative files. Outpatient utilization (primary care, specialty care, mental health, pharmacy, radiology and laboratory) and inpatient utilization were estimated using count data models and expenditures were estimated using one-part or two-part models. The second part of two-part models was estimated using generalized linear regressions.
Results
CBOC patients had a slightly more primary care visits per year than VAMC patients (p < 0.0001), but lower primary care costs (-$71, p < 0.0001). CBOC patients had lower odds of one or more specialty, mental health, ancillary visits and hospital stays per year, and fewer numbers of visits and stays if they had any and lower specialty, mental health, ancillary and inpatient expenditures (all, p < 0.0001). As a result, CBOC patients had lower total outpatient and overall expenditures than VAMC patients (p < 0.0001).
Conclusion
CBOCs provided veterans improved access to primary care and other services, but expenditures were contained because CBOC patients who sought health care had fewer visits and hospital stays than comparable VAMC patients. These results suggest a more complex pattern of health care utilization and expenditures by CBOC patients than has been found in prior studies. This study also illustrates that CBOCs continue to be a critical primary care and mental health access point for veterans.
doi:10.1186/1472-6963-7-56
PMCID: PMC1855054  PMID: 17442115
20.  A self-evaluation tool for integrated care services: the Development Model for Integrated Care applied in practice 
Purpose
The purpose of the workshop is to show the applications of the Development Model for Integrated Care (DMIC) in practice. This relatively new and validated model, can be used by integrated care practices to evaluate their integrated care, to assess their phase of development and reveal improvement areas. In the workshop the results of the use of the model in three types of integrated care settings in the Netherlands will be presented. Participants are offered practical instruments based on the validated DMIC to use in their own setting and will be introduced to the webbased tool.
Context
To integrate care from multiple providers into a coherent and streamlined client-focused service, a large number of activities and agreements have to be implemented like streamlining information flows and adequate transfers of clients. In the large range of possible activities it is often not clear what essential activities are and where to start or continue. Also, knowledge about how to further develop integrated care services is needed. The Development Model for Integrated Care (DMIC), based on PhD research of Mirella Minkman, describes nine clusters containing in total 89 elements that contribute to the integration of care. The clusters are named: ‘client-centeredness’, ‘delivery system’, ‘performance management’, ‘quality of care’, ‘result-focused learning’, ‘interprofessional teamwork’, ‘roles and tasks’, ‘commitment’, and ‘transparant entrepreneurship’ [1–3]. In 2011 a new digital webbased self-evolution tool which contains the 89 elements grouped in nine clusters was developed. The DMIC also describes four phases of development [4]. The model is empirically validated in practice by assessing the relevance and implementation of the elements and development phases in 84 integrated care services in The Netherlands: in stroke, acute myocardial infarct (AMI), and dementia services. The validation studies are recently published [5, 6]. In 2011 also other integrated care services started using the model [7]. Vilans developed a digital web-based self-evaluation tool for integrated care services based on the DMIC. A palliative care network, four diabetes services, a youth care service and a network for autism used the self-evaluation tool to evaluate the development of their integrated care service. Because of its generic character, the model and tool are believed to be also interesting internationally.
Data sources
In the workshop we will present the results of three studies in integrated diabetes, youth and palliative care. The three projects consist of multiple steps, see below. Workshop participants could also work with the DMIC following these steps.
One: Preparation of the digital self-evolution tool for integrated care services
Although they are very different, the three integrated care services all wanted to gain insight in their development and improvement opportunities. We tailored the digital self-evaluation tool for each specific integrated care services, but for all the basis was the DMIC. Personal accounts for the digital DMIC self-evalution survey were sent to multiple partners working in each integrated care service (4–16 partners).
Two: Use of the online self-evaluation tool each partner of the local integrated care setting evaluated the integrated care by filling in the web-based questionnaire. The tool consists of three parts (A-C) named: general information about the integrated care practice (A); the clusters and elements of the DMIC (B); and the four phases of development (C). The respondents rated the relevance and presence of each element in their integrated care practice. Respondents were asked to estimate in which phase of development their thought their service was.
Three: Analysing the results
Advisers from Vilans, the Centre of excellence for long-term care in the Netherlands, analysed the self-evolution results in cooperation with the integrated care coordinators. The results show the total amount of implemented integrated care elements per cluster in spider graphs and the development phase as calculated by the DMIC model. Suggestions for further development of the integrated care services were analysed and reported.
Four: Discussing the implications for further development
In a workshop with the local integrated care partners the results of the self-evaluation were presented and discussed. We noticed remarkable results and highlight elements for further development. In addition, we gave advice for further development appropriate to the development phase of the integrated care service. Furthermore, the professionals prioritized the elements and decided which elements to start working on. This resulted in a (quality improvement) plan for the further development of the integrated care service.
Five: Reporting results
In a report all the results of the survey (including consensus scores) and the workshops came together. The integrated care coordinators stated that the reports really helped them to assess their improvement strategy. Also, there was insight in the development phase of their service which gave tools for further development.
Case description
The three cases presented are a palliative network, an integrated diabetes services and an integrated care network for youth in the Netherlands. The palliative care network wanted to reflect on their current development, to build a guiding framework for further development of the network. About sixteen professionals within the network worked with the digital self-evaluation tool and the DMIC: home care organisations, welfare organizations, hospice centres, health care organisations, community organizations.
For diabetes care, a Dutch health care insurance company wished to gain insight in the development of the contracted integrated care services to stimulate further development of the services. Professionals of three diabetes integrated care services were invited to fill in the digital self-evaluation tool. Of each integrated care service professionals like a general practitioner, a diabetes nurse, a medical specialist, a dietician and a podiatrist were invited. In youth care, a local health organisation wondered whether the DMIC could be helpful to visualize the results of youth integrated care services at process- and organisational level. The goal of the project was to define indicators at a process- and organisational level for youth care services based on the DMIC. In the future, these indicators might be used to evaluate youth care integrated care services and improve the quality of youth care within the Netherlands.
Conclusions and discussion
It is important for the quality of integrated care services that the involved coordinators, managers and professionals are aware of the development process of the integrated care service and that they focus on elements which can further develop and improve their integrated care. However, we noticed that integrated care services in the Netherlands experience difficulties in developing their integrated care service. It is often not clear what essential activities are to work on and how to further develop the integrated care service. A guiding framework for the development of integrated care was missing. The DMIC model has been developed for that reason and offers a useful tool for assessment, self-evaluation or improvement of integrated care services in practice. The model has been validated for AMI, dementia and stroke services. The latest new studies in diabetes, palliative care and youth care gave further insight in the generic character of the DMIC. Based on these studies it can be assumed that the DMIC can be used for multiple types of integrated care services. The model is assumed to be interesting for an international audience. Improving integrated care is a complex topic in a large number of countries; the DMIC is also based on the international literature. Dutch integrated care coordinators stated that the DMIC helped them to assess their integrated care development in practice and supported them in obtaining ideas for expanding and improving their integrated care activities.
The web-based self-evaluation tool focuses on a process- and organisational level of integrated care. Also, the self assessed development phase can be compared to the development phase as calculated by the DMIC tool. The cases showed this is fruitful input for discussions. When using the tool, the results can also be used in quality policy reports and improvement plans. The web-based tool is being tested at this moment in practice, but in San Marino we can present the latest webversion and demonstrate with a short video how to use the tool and model. During practical exercises in the workshop the participants will experience how the application of the DMIC can work for them in practice or in research. For integrated care researchers and policy makers, the DMIC questionnaire and tool is a promising method for further research and policy plans in integrated care.
PMCID: PMC3617779
development model for integrated care; development of integrated care services; implementation and improvement of integrated care; self evaluation
21.  Community-Based Care for the Specialized Management of Heart Failure 
Executive Summary
In August 2008, the Medical Advisory Secretariat (MAS) presented a vignette to the Ontario Health Technology Advisory Committee (OHTAC) on a proposed targeted health care delivery model for chronic care. The proposed model was defined as multidisciplinary, ambulatory, community-based care that bridged the gap between primary and tertiary care, and was intended for individuals with a chronic disease who were at risk of a hospital admission or emergency department visit. The goals of this care model were thought to include: the prevention of emergency department visits, a reduction in hospital admissions and re-admissions, facilitation of earlier hospital discharge, a reduction or delay in long-term care admissions, and an improvement in mortality and other disease-specific patient outcomes.
OHTAC approved the development of an evidence-based assessment to determine the effectiveness of specialized community based care for the management of heart failure, Type 2 diabetes and chronic wounds.
Please visit the Medical Advisory Secretariat Web site at: www.health.gov.on.ca/ohtas to review the following reports associated with the Specialized Multidisciplinary Community-Based care series.
Specialized multidisciplinary community-based care series: a summary of evidence-based analyses
Community-based care for the specialized management of heart failure: an evidence-based analysis
Community-based care for chronic wound management: an evidence-based analysis
Please note that the evidence-based analysis of specialized community-based care for the management of diabetes titled: “Community-based care for the management of type 2 diabetes: an evidence-based analysis” has been published as part of the Diabetes Strategy Evidence Platform at this URL: http://www.health.gov.on.ca/english/providers/program/mas/tech/ohtas/tech_diabetes_20091020.html
Please visit the Toronto Health Economics and Technology Assessment Collaborative Web site at: http://theta.utoronto.ca/papers/MAS_CHF_Clinics_Report.pdf to review the following economic project associated with this series:
Community-based Care for the specialized management of heart failure: a cost-effectiveness and budget impact analysis.
Objective
The objective of this evidence-based analysis was to determine the effectiveness of specialized multidisciplinary care in the management of heart failure (HF).
Clinical Need: Target Population and Condition
HF is a progressive, chronic condition in which the heart becomes unable to sufficiently pump blood throughout the body. There are several risk factors for developing the condition including hypertension, diabetes, obesity, previous myocardial infarction, and valvular heart disease.(1) Based on data from a 2005 study of the Canadian Community Health Survey (CCHS), the prevalence of congestive heart failure in Canada is approximately 1% of the population over the age of 12.(2) This figure rises sharply after the age of 45, with prevalence reports ranging from 2.2% to 12%.(3) Extrapolating this to the Ontario population, an estimated 98,000 residents in Ontario are believed to have HF.
Disease management programs are multidisciplinary approaches to care for chronic disease that coordinate comprehensive care strategies along the disease continuum and across healthcare delivery systems.(4) Evidence for the effectiveness of disease management programs for HF has been provided by seven systematic reviews completed between 2004 and 2007 (Table 1) with consistency of effect demonstrated across four main outcomes measures: all cause mortality and hospitalization, and heart-failure specific mortality and hospitalization. (4-10)
However, while disease management programs are multidisciplinary by definition, the published evidence lacks consistency and clarity as to the exact nature of each program and usual care comparators are generally ill defined. Consequently, the effectiveness of multidisciplinary care for the management of persons with HF is still uncertain. Therefore, MAS has completed a systematic review of specialized, multidisciplinary, community-based care disease management programs compared to a well-defined usual care group for persons with HF.
Evidence-Based Analysis Methods
Research Questions
What is the effectiveness of specialized, multidisciplinary, community-based care (SMCCC) compared with usual care for persons with HF?
Literature Search Strategy
A comprehensive literature search was completed of electronic databases including MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, Cochrane Library and Cumulative Index to Nursing & Allied Health Literature. Bibliographic references of selected studies were also searched. After a review of the title and abstracts, relevant studies were obtained and the full reports evaluated. All studies meeting explicit inclusion and exclusion criteria were retained. Where appropriate, a meta-analysis was undertaken to determine the pooled estimate of effect of specialized multidisciplinary community-based care for explicit outcomes. The quality of the body of evidence, defined as one or more relevant studies was determined using GRADE Working Group criteria. (11)
Inclusion Criteria
Randomized controlled trial
Systematic review with meta analysis
Population includes persons with New York Heart Association (NYHA) classification 1-IV HF
The intervention includes a team consisting of a nurse and physician one of which is a specialist in HF management.
The control group receives care by a single practitioner (e.g. primary care physician (PCP) or cardiologist)
The intervention begins after discharge from the hospital
The study reports 1-year outcomes
Exclusion Criteria
The intervention is delivered predominately through home-visits
Studies with mixed populations where discrete data for HF is not reported
Outcomes of Interest
All cause mortality
All cause hospitalization
HF specific mortality
HF specific hospitalization
All cause duration of hospital stay
HF specific duration of hospital stay
Emergency room visits
Quality of Life
Summary of Findings
One large and seven small randomized controlled trials were obtained from the literature search.
A meta-analysis was completed for four of the seven outcomes including:
All cause mortality
HF-specific mortality
All cause hospitalization
HF-specific hospitalization.
Where the pooled analysis was associated with significant heterogeneity, subgroup analyses were completed using two primary categories:
direct and indirect model of care; and
type of control group (PCP or cardiologist).
The direct model of care was a clinic-based multidisciplinary HF program and the indirect model of care was a physician supervised, nurse-led telephonic HF program.
All studies, except one, were completed in jurisdictions outside North America. (12-19) Similarly, all but one study had a sample size of less than 250. The mean age in the studies ranged from 65 to 77 years. Six of the studies(12;14-18) included populations with a NYHA classification of II-III. In two studies, the control treatment was a cardiologist (12;15) and two studies reported the inclusion of a dietitian, physiotherapist and psychologist as members of the multidisciplinary team (12;19).
All Cause Mortality
Eight studies reported all cause mortality (number of persons) at 1 year follow-up. (12-19) When the results of all eight studies were pooled, there was a statistically significant RRR of 29% with moderate heterogeneity (I2 of 38%). The results of the subgroup analyses indicated a significant RRR of 40% in all cause mortality when SMCCC is delivered through a direct team model (clinic) and a 35% RRR when SMCCC was compared with a primary care practitioner.
HF-Specific Mortality
Three studies reported HF-specific mortality (number of persons) at 1 year follow-up. (15;18;19) When the results of these were pooled, there was an insignificant RRR of 42% with high statistical heterogeneity (I2 of 60%). The GRADE quality of evidence is moderate for the pooled analysis of all studies.
All Cause Hospitalization
Seven studies reported all cause hospitalization at 1-year follow-up (13-15;17-19). When pooled, their results showed a statistically insignificant 12% increase in hospitalizations in the SMCCC group with high statistical heterogeneity (I2 of 81%). A significant RRR of 12% in all cause hospitalization in favour of the SMCCC care group was achieved when SMCCC was delivered using an indirect model (telephonic) with an associated (I2 of 0%). The Grade quality of evidence was found to be low for the pooled analysis of all studies and moderate for the subgroup analysis of the indirect team care model.
HF-Specific Hospitalization
Six studies reported HF-specific hospitalization at 1-year follow-up. (13-15;17;19) When pooled, the results of these studies showed an insignificant RRR of 14% with high statistical heterogeneity (I2 of 60%); however, the quality of evidence for the pooled analysis of was low.
Duration of Hospital Stay
Seven studies reported duration of hospital stay, four in terms of mean duration of stay in days (14;16;17;19) and three in terms of total hospital bed days (12;13;18). Most studies reported all cause duration of hospital stay while two also reported HF-specific duration of hospital stay. These data were not amenable to meta-analyses as standard deviations were not provided in the reports. However, in general (and in all but one study) it appears that persons receiving SMCCC had shorter hospital stays, whether measured as mean days in hospital or total hospital bed days.
Emergency Room Visits
Only one study reported emergency room visits. (14) This was presented as a composite of readmissions and ER visits, where the authors reported that 77% (59/76) of the SMCCC group and 84% (63/75) of the usual care group were either readmitted or had an ER visit within the 1 year of follow-up (P=0.029).
Quality of Life
Quality of life was reported in five studies using the Minnesota Living with HF Questionnaire (MLHFQ) (12-15;19) and in one study using the Nottingham Health Profile Questionnaire(16). The MLHFQ results are reported in our analysis. Two studies reported the mean score at 1 year follow-up, although did not provide the standard deviation of the mean in their report. One study reported the median and range scores at 1 year follow-up in each group. Two studies reported the change scores of the physical and emotional subscales of the MLHFQ of which only one study reported a statistically significant change from baseline to 1 year follow-up between treatment groups in favour of the SMCCC group in the physical sub-scale. A significant change in the emotional subscale scores from baseline to 1 year follow-up in the treatment groups was not reported in either study.
Conclusion
There is moderate quality evidence that SMCCC reduces all cause mortality by 29%. There is low quality evidence that SMCCC contributes to a shorter duration of hospital stay and improves quality of life compared to usual care. The evidence supports that SMCCC is effective when compared to usual care provided by either a primary care practitioner or a cardiologist. It does not, however, suggest an optimal model of care or discern what the effective program components are. A field evaluation could address this uncertainty.
PMCID: PMC3377506  PMID: 23074521
22.  The Influence of Distance and Level of Care on Delivery Place in Rural Zambia: A Study of Linked National Data in a Geographic Information System 
PLoS Medicine  2011;8(1):e1000394.
Using linked national data in a geographic information system system, Sabine Gabrysch and colleagues investigate the effects of distance to care and level of care on women's use of health facilities for delivery in rural Zambia.
Background
Maternal and perinatal mortality could be reduced if all women delivered in settings where skilled attendants could provide emergency obstetric care (EmOC) if complications arise. Research on determinants of skilled attendance at delivery has focussed on household and individual factors, neglecting the influence of the health service environment, in part due to a lack of suitable data. The aim of this study was to quantify the effects of distance to care and level of care on women's use of health facilities for delivery in rural Zambia, and to compare their population impact to that of other important determinants.
Methods and Findings
Using a geographic information system (GIS), we linked national household data from the Zambian Demographic and Health Survey 2007 with national facility data from the Zambian Health Facility Census 2005 and calculated straight-line distances. Health facilities were classified by whether they provided comprehensive EmOC (CEmOC), basic EmOC (BEmOC), or limited or substandard services. Multivariable multilevel logistic regression analyses were performed to investigate the influence of distance to care and level of care on place of delivery (facility or home) for 3,682 rural births, controlling for a wide range of confounders. Only a third of rural Zambian births occurred at a health facility, and half of all births were to mothers living more than 25 km from a facility of BEmOC standard or better. As distance to the closest health facility doubled, the odds of facility delivery decreased by 29% (95% CI, 14%–40%). Independently, each step increase in level of care led to 26% higher odds of facility delivery (95% CI, 7%–48%). The population impact of poor geographic access to EmOC was at least of similar magnitude as that of low maternal education, household poverty, or lack of female autonomy.
Conclusions
Lack of geographic access to emergency obstetric care is a key factor explaining why most rural deliveries in Zambia still occur at home without skilled care. Addressing geographic and quality barriers is crucial to increase service use and to lower maternal and perinatal mortality. Linking datasets using GIS has great potential for future research and can help overcome the neglect of health system factors in research and policy.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Approximately 360,000 women die each year in pregnancy and childbirth, of which more than 200,000 in sub-Saharan Africa, where a woman's lifetime risk of dying during or following pregnancy remains as high as 1 in 31 (compared to 1 in 4,300 in the developed world). The target of Millennium Development Goal 5 is to reduce the maternal mortality ratio by three quarters by 2015. Most maternal and neonatal deaths in low-income countries could be prevented if all women delivered their babies in settings where skilled birth attendants (such as midwives) were available and could provide emergency obstetric care to both mothers and babies in case of complications. Yet every year roughly 50 million women give birth at home without skilled care.
Why was this study done?
The likelihood of a woman giving birth in a health facility under the care of a skilled birth attendant depends on many factors. These include characteristics of the mother and her family, such as education level and household wealth, and aspects of the health service environment—distance to the nearest health facility and the quality of care provided at that facility, for example. However, research to date has typically focused on household and individual factors, neglecting the influence of the health service environment on choice of delivery place, largely because suitable data was not available. In this study in rural Zambia, the researchers aimed to quantify the effects of the health service environment, namely distance to health care and the level of care provided, on pregnant women's use of health facilities for giving birth. To put these factors in context, the researchers compared the impact of distance to quality care on place of delivery to that of other important factors, such as poverty and education.
What did the researchers do and find?
Using a geographic information system (GIS), the researchers linked national household data (from the 2007 Zambia Demographic and Health Survey) with national facility data (from the 2005 Zambian Health Facility Census) and calculated straight-line distances between women's villages and health facilities. Health facilities were classified as providing comprehensive emergency obstetric care, basic emergency obstetric care, or limited or substandard services by using reported capability to perform a certain number of the eight emergency obstetric care signal functions: injectable antibiotics, injectable oxytocics, injectable anticonvulsants, manual removal of placenta, manual removal of retained products, assisted vaginal delivery, cesarean section, and blood transfusion, as well as criteria on staffing, opening hours and referral capacity. The researchers used data from 3,682 rural births and multivariable multilevel logistic regression analyses to investigate whether distance to, and level of care at the closest delivery facility influence place of delivery (health facility or home), keeping other influential factors constant.
The researchers found that only a third of births in rural Zambia occurred at a health facility, and half of all mothers who gave birth lived more than 25 km from a health facility that provided basic emergency obstetric services. As distance to the closest health facility doubled, the odds of a women giving birth in a health facility decreased by 29%. Independently, each step increase in the level of emergency obstetric care provided at the closest delivery facility led to an increased likelihood (26% higher odds) of a woman delivering her baby at a facility. The researchers estimated that the impact of poor geographic access to emergency obstetric services was of similar magnitude as that of low maternal education, household poverty, or lack of female autonomy.
What do these findings mean?
The results of this study suggest that poor geographic access to emergency obstetric care is a key factor in explaining why most women in rural Zambia still deliver their babies at home without skilled care. Therefore, in order to increase the number of women delivering in health facilities and thus reduce maternal and neonatal mortality, it is crucial to address the geographic and quality barriers to delivery service use. Furthermore, the methodology used in this study—linking datasets using GIS— has great potential for future research as it can help explore the influence of health system factors also for other health problems.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000394.
Information about emergency obstetric care is provided by the United Nations Population Fund (UNFPA)
Various topics on maternal health are presented by WHO, WHO Regional Office Africa, by UNPFA, and UNICEF
WHO offers detailed information about MDG5
Family Care International offers more information about maternal and neonatal health
The Averting Maternal Death and Disability program (AMDD) provides information on needs assessments of emergency obstetric and newborn care
Countdown to 2015 tracks progress in maternal, newborn, and child survival
WHO provides free online viewing of BBC Fight for Life videos describing delivery experiences in different countries
doi:10.1371/journal.pmed.1000394
PMCID: PMC3026699  PMID: 21283606
23.  Chronic Disease Patients’ Experiences With Accessing Health Care in Rural and Remote Areas 
Background
Rurality can contribute to the vulnerability of people with chronic diseases. Qualitative research can identify a wide range of health care access issues faced by patients living in a remote or rural setting.
Objective
To systematically review and synthesize qualitative research on the advantages and disadvantages rural patients with chronic diseases face when accessing both rural and distant care.
Data Sources
This report synthesizes 12 primary qualitative studies on the topic of access to health care for rural patients with chronic disease. Included studies were published between 2002 and 2012 and followed adult patients in North America, Europe, Australia, and New Zealand.
Review Methods
Qualitative meta-synthesis was used to integrate findings across primary research studies.
Results
Three major themes were identified: geography, availability of health care professionals, and rural culture. First, geographic distance from services poses access barriers, worsened by transportation problems or weather conditions. Community supports and rurally located services can help overcome these challenges. Second, the limited availability of health care professionals (coupled with low education or lack of peer support) increases the feeling of vulnerability. When care is available locally, patients appreciate long-term relationships with individual clinicians and care personalized by familiarity with the patient as a person. Finally, patients may feel culturally marginalized in the urban health care context, especially if health literacy is low. A culture of self-reliance and community belonging in rural areas may incline patients to do without distant care and may mitigate feelings of vulnerability.
Limitations
Qualitative research findings are not intended to generalize directly to populations, although meta-synthesis across a number of qualitative studies builds an increasingly robust understanding that is more likely to be transferable. Selected studies focused on the vulnerability experiences of rural dwellers with chronic disease; findings emphasize the patient rather than the provider perspective.
Conclusions
This study corroborates previous knowledge and concerns about access issues in rural and remote areas, such as geographical distance and shortage of health care professionals and services. Unhealthy behaviours and reduced willingness to seek care increase patients’ vulnerability. Patients’ perspectives also highlight rural culture’s potential to either exacerbate or mitigate access issues.
Plain Language Summary
People who live in a rural area may feel more vulnerable—that is, more easily harmed by their health problems or experiences with the health care system. Qualitative research looks at these experiences from the patient’s point of view. We found 3 broad concerns in the studies we looked at. The first was geography: needing to travel long distances for health care can make care hard to reach, especially if transportation is difficult or the weather is bad. The second concern was availability of health professionals: rural areas often lack health care services. Patients may also feel powerless in “referral games” between rural and urban providers. People with low education or without others to help them may find navigating care more difficult. When rural services are available, patients like seeing clinicians who have known them for a long time, and like how familiar clinicians treat them as a whole person. The third concern was rural culture: patients may feel like outsiders in city hospitals or clinics. As well, in rural communities, people may share a feeling of self-reliance and community belonging. This may make them more eager to take care of themselves and each other, and less willing to seek distant care. Each of these factors can increase or decrease patient vulnerability, depending on how health services are provided.
PMCID: PMC3817950  PMID: 24228078
24.  Effect of a Community-Based Nursing Intervention on Mortality in Chronically Ill Older Adults: A Randomized Controlled Trial 
PLoS Medicine  2012;9(7):e1001265.
Kenneth Coburn and colleagues report findings from a randomized trial evaluating the effects of a complex nursing intervention on mortality risk among older individuals diagnosed with chronic health conditions.
Background
Improving the health of chronically ill older adults is a major challenge facing modern health care systems. A community-based nursing intervention developed by Health Quality Partners (HQP) was one of 15 different models of care coordination tested in randomized controlled trials within the Medicare Coordinated Care Demonstration (MCCD), a national US study. Evaluation of the HQP program began in 2002. The study reported here was designed to evaluate the survival impact of the HQP program versus usual care up to five years post-enrollment.
Methods and Findings
HQP enrolled 1,736 adults aged 65 and over, with one or more eligible chronic conditions (coronary artery disease, heart failure, diabetes, asthma, hypertension, or hyperlipidemia) during the first six years of the study. The intervention group (n = 873) was offered a comprehensive, integrated, and tightly managed system of care coordination, disease management, and preventive services provided by community-based nurse care managers working collaboratively with primary care providers. The control group (n = 863) received usual care. Overall, a 25% lower relative risk of death (hazard ratio [HR] 0.75 [95% CI 0.57–1.00], p = 0.047) was observed among intervention participants with 86 (9.9%) deaths in the intervention group and 111 (12.9%) deaths in the control group during a mean follow-up of 4.2 years. When covariates for sex, age group, primary diagnosis, perceived health, number of medications taken, hospital stays in the past 6 months, and tobacco use were included, the adjusted HR was 0.73 (95% CI 0.55–0.98, p = 0.033). Subgroup analyses did not demonstrate statistically significant interaction effects for any subgroup. No suspected program-related adverse events were identified.
Conclusions
The HQP model of community-based nurse care management appeared to reduce all-cause mortality in chronically ill older adults. Limitations of the study are that few low-income and non-white individuals were enrolled and implementation was in a single geographic region of the US. Additional research to confirm these findings and determine the model's scalability and generalizability is warranted.
Trial Registration
ClinicalTrials.gov NCT01071967
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In almost every country in the world, the proportion of people aged over 60 years is growing faster than any other age group because of increased life expectancy. This demographic change has several implications for public health, especially as older age is a risk factor for many chronic diseases—diseases of long duration and generally slow progression. Chronic diseases, such as heart disease, stroke, cancer, chronic respiratory diseases, and diabetes, are by far the leading cause of death in the world, representing almost two-thirds of all deaths. Therefore in most countries, the challenge of managing increasingly ageing populations who have chronic illnesses demands an urgent response and countries such as the United States are actively researching possible solutions.
Why Was This Study Done?
Some studies suggest that innovations in chronic disease management that are led by nurses may help address the epidemic of chronic diseases by increasing the quality and reducing the cost of care. However, to date, reports of the evaluation of such interventions lack rigor and do not provide evidence of improved long-term health outcomes or reduced health care costs. So in this study, the researchers used the gold standard of research, a randomized controlled trial, to examine the impact of a community-based nurse care management model for older adults with chronic illnesses in the United States as part of a series of studies supported by the Centers for Medicare and Medicaid Services.
What Did the Researchers Do and Find?
The researchers recruited eligible patients aged 65 years and over with heart failure, coronary heart disease, asthma, diabetes, hypertension, and/or hyperlipidemia who received traditional Medicare—a fee for service insurance scheme in which beneficiaries can choose to receive their care from any Medicare provider—from participating primary care practices in Pennsylvania. The researchers then categorized patients according to their risk on the basis of several factors including the number of chronic diseases each individual had before randomizing patients to receive usual care or the nurse-led intervention. The intervention included an individualized plan comprising education, symptom monitoring, medication, counseling for adherence, help identifying, arranging, and monitoring community health and social service referrals in addition to group interventions such as weight loss maintenance and exercise classes. The researchers checked whether any participating patients had died by using the online Social Security Death Master File. Then the researchers used a statistical model to calculate the risk of death in both groups.
Of the 1,736 patients the researchers recruited into the trial, 873 were randomized to receive the intervention and 863 were in the control group (usual care). The researchers found that 86 (9.9%) participants in the intervention group and 111 (12.9%) participants in the control group died during the study period, representing a 25% lower relative risk of death among the intervention group. However, when the researchers considered other factors, such as sex, age group, primary diagnosis, perceived health, number of medications taken, hospital stays in the past 6 months, and tobacco use in their statistical model, this risk was slightly altered—0.73 risk of death in the intervention group.
What Do These Findings Mean?
These findings suggest that that community-based nurse care management is associated with a reduction in all-cause mortality among older adults with chronic illnesses who are beneficiaries of the fee for service Medicare scheme in the United States. These findings also support the important role of nurses in improving health outcomes in this group of patients and show the feasibility of implementing this program in collaboration with primary care practices. Future research is needed to test the adaptability, scalability, and generalizability of this model of care.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001265.
This study is further discussed in a PLoS Medicine Perspective by Arlene Bierman
Information about the Centers for Medicare and Medicaid Services is available
The World Health Organization provides statistics on the prevalence of both chronic illness and ageing
Heath Quality Partners provide information about the study
doi:10.1371/journal.pmed.1001265
PMCID: PMC3398966  PMID: 22815653
25.  Reduction in Clostridium difficile Infection Rates after Mandatory Hospital Public Reporting: Findings from a Longitudinal Cohort Study in Canada 
PLoS Medicine  2012;9(7):e1001268.
A population-based study conducted by Nick Daneman and colleagues in Ontario, Canada reports on the association between population reporting of hospital infection rates and a reduction in population burden of Clostridium difficile colitis.
Background
The role of public reporting in improving hospital quality of care is controversial. Reporting of hospital-acquired infection rates has been introduced in multiple health care systems, but its relationship to infection rates has been understudied. Our objective was to determine whether mandatory public reporting by hospitals is associated with a reduction in hospital rates of Clostridium difficile infection.
Methods and Findings
We conducted a longitudinal, population-based cohort study in Ontario (Canada's largest province) between April 1, 2002, and March 31, 2010. We included all patients (>1 y old) admitted to 180 acute care hospitals. Using Poisson regression, we developed a model to predict hospital- and age-specific monthly rates of C. difficile disease per 10,000 patient-days prior to introduction of public reporting on September 1, 2008. We then compared observed monthly rates of C. difficile infection in the post-intervention period with rates predicted by the pre-intervention predictive model. In the pre-intervention period there were 33,634 cases of C. difficile infection during 39,221,113 hospital days, with rates increasing from 7.01 per 10,000 patient-days in 2002 to 10.79 in 2007. In the first calendar year after the introduction of public reporting, there was a decline in observed rates of C. difficile colitis in Ontario to 8.92 cases per 10,000 patient-days, which was significantly lower than the predicted rate of 12.16 (95% CI 11.35–13.04) cases per 10,000 patient-days (p<0.001). Over this period, public reporting was associated with a 26.7% (95% CI 21.4%–31.6%) reduction in C. difficile cases, or a projected 1,970 cases averted per year (95% CI 1,476–2,500). The effect was specific to C. difficile, with rates of community-acquired gastrointestinal infections and urinary tract infections unchanged. A limitation of our study is that this observational study design cannot rule out the influence of unmeasured temporal confounders.
Conclusions
Public reporting of hospital C. difficile rates was associated with a substantial reduction in the population burden of this infection. Future research will be required to discern the direct mechanism by which C. difficile infection rates may have been reduced in response to public reporting.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
A stay in hospital can be lifesaving but can expose people to health care–associated infections. One of these—Clostridium difficile infection—is a major cause of infectious disease illness and death in developed countries. C. difficile bacteria cause diarrhea and, more rarely, life-threatening inflammation of the gut (colitis). They are present in the gut of about 3% of adults but do not normally cause any problems because other “good” bacteria keep them in check. However, antibiotics destroy these good bacteria, and if a person who has taken antibiotics becomes infected with C. difficile before good bacteria repopulate the gut, C. difficile can multiply rapidly and produce toxins that cause illness. Because C. difficile is usually acquired from other infected patients and their contaminated environments, and because antibiotic use is highly prevalent in hospitals, most C. difficile infections are acquired in hospitals and nursing homes. Infections can be prevented by practicing good hygiene in health care environments (for example, washing hands regularly with soap and water), by isolating patients who are infected with C. difficile, and by prescribing antibiotics for other infections sparingly.
Why Was This Study Done?
Hospitals often need encouragement to improve infection control and other aspects of care. One potential way to improve the quality of hospital care is mandatory public reporting of measures of care quality. This intervention may help hospitals identify areas of poor performance to target for improvement or may motivate them to improve care quality to avoid the shame of a bad performance report. Although many health care systems have introduced public reporting of hospital-acquired infections, the effects of this intervention have been poorly studied. In this longitudinal cohort study, the researchers use population-based health care data to evaluate the impact of the introduction of mandatory hospital public reporting of the rates of hospital-acquired C. difficile infection in Ontario, Canada. Since September 1, 2008, hospitals in Ontario have been required to send monthly data on hospital-acquired C. difficile infections to the Ontario Ministry of Health and Long-Term Care for posting on a public website.
What Did the Researchers Do and Find?
The researchers used health care administrative data for all patients older than one year admitted to acute care hospitals in Ontario between April 1, 2002, and March 31, 2010, to develop a model to predict monthly rates of C. difficile disease per 10,000 patient-days based on rates in the period before the introduction of public reporting. They then compared the observed rates of C. difficile disease after the introduction of public reporting with the rates predicted by this model. In the pre-intervention period, there were nearly 34,000 cases of C. difficile disease during about 39 million hospital days. Rates of C. difficile disease increased from 7.01 cases per 10,000 patient-days in 2002 to 10.79 cases per 10,000 patient-days in 2007. After the introduction of public reporting, the C. difficile disease rate fell to 8.92 cases per 10,000 patient-days, which is significantly (that is, unlikely to have occurred by chance) lower than the 12.16 cases per 10,000 patient-days predicted by the pre-intervention model. Finally, the researchers estimate that public reporting was associated with a 26.6% reduction in C. difficile disease cases and that it averted about 1,900 cases per year.
What Do These Findings Mean?
These findings suggest that mandatory public reporting of hospital rates of C. difficile disease may reduce the population burden of this serious infection. Because this is an observational study, these findings do not prove that the introduction of mandatory public reporting actually caused a reduction in infection rates. Some other uncharacterized factor might be responsible for the decrease in C. difficile disease in Ontario hospitals since late 2008. Moreover, the many assumptions included in the predictive model means that the estimated number of cases averted by the introduction of public reporting may be inaccurate. Although further research is needed to determine how public reporting might affect C. difficile disease rates, the researchers suggest that, in this study, mandatory public reporting may have increased the prominence of C. difficile on hospital quality improvement agendas and may have motivated hospitals to adhere more closely to best practices in C. difficile prevention.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001268.
The US Centers for Disease Control and Prevention provides detailed information about C. difficile infection, including an article called Making Health Care Safer: Stopping C. difficile Infections
The UK National Health Service Choices website provides information about C. difficile infections
The Health Protection Agency provides information about mandatory reporting of C. difficile infections in England and Wales and a fact sheet on C. difficile
Information about public reporting of hospital C. difficile rates in Ontario is available (in English and French)
MedlinePlus provides links to further resources about C. difficile infections (in English and Spanish)
The UK Clostridium Difficle Support website has a forum containing personal stories about C. difficile infection
doi:10.1371/journal.pmed.1001268
PMCID: PMC3398960  PMID: 22815656

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