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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.  The One-stop trial: Does electronic referral and booking by the general practitioner (GPs) to outpatient day case surgery reduce waiting time and costs? A randomized controlled trial protocol 
BMC Surgery  2008;8:14.
Background
Waiting time and costs from referral to day case outpatient surgery are at an unacceptably high level. The waiting time in Norway averages 240 days for common surgical conditions. Furthermore, in North Norway the population is scattered throughout a large geographic area, making the cost of travel to a specialist examination before surgery considerable. Electronic standardised referrals and booking of day case outpatient surgery by GPs are possible through the National Health Network, which links all health care providers in an electronic network. New ways of using this network might reduce the waiting time and cost of outpatient day case surgery.
Materials and Methods
In a randomised controlled trial, selected patients (inguinal hernia, gallstone disease and pilonidal sinus) referred to the university hospital are either randomised to direct electronic referral and booking for outpatient surgery (one stop), or to the traditional patient pathway where all patients are seen at the outpatient clinic several weeks ahead of surgery.
Consultants in gastrointestinal surgery designed standardised referral forms and guidelines. New software has been designed making it possible to implement referral forms, guidelines and patient information in the GP's electronic health record. For "one-stop" referral, GPs must provide mandatory information about the specific condition. Referrals were linked to a booking system, enabling the GPs to book the hospital, day and time for outpatient surgery. The primary endpoints are waiting time and costs. The sample size calculation was based on waiting time. A reduction in waiting time of 60 days (effect size), 25%, is significant, resulting in a sample size of 120 patients in total.
Discussion
Poor communication between primary and secondary care often results in inefficiencies and unsatisfactory outcomes. We hypothesised that standardised referrals would improve the quality of information, making it feasible to use a one-stop approach for all patients undergoing surgery on an outpatient basis for inguinal hernia, pilonidal sinus and gallstones.
In this study we wanted to investigate the waiting time and cost-effectiveness of direct electronic referral and booking of outpatient surgery compared to the traditional patient pathway, where the patient is seen at the outpatient clinic prior to surgery.
Trial registration
This trial has been registered at ClinicalTrials.gov. The trial registration number is: NCT00692497
doi:10.1186/1471-2482-8-14
PMCID: PMC2527297  PMID: 18694477
3.  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
4.  Improving the management and referral of patients with transient ischaemic attacks: a change strategy for a health community 
Problem
Rapid referral and management of patients with transient ischaemic attacks is a key component in the national strategy for stroke prevention. However, patients with transient ischaemic attacks are poorly identified and undertreated.
Design and setting
Before and after evaluation of quality improvement programme with controlled comparison in three primary care trusts reflecting diverse populations and organisational structures in an urban district in the North of England.
Key measures for improvement
The proportion of patients receiving antiplatelet drugs and safe driving advice on referral to a speciality clinic, and the numbers of referrals, adjusted for age, to the specialist clinic before and after the improvement programme.
Strategies for change
Interviews with patient and professionals to identify gaps and barriers to good practice; development of evidence based guidelines for the management of patients with transient ischaemic attacks; interactive multidisciplinary workshops for each primary care trust with feedback of individual audit results of referral practice; outreach visits to teams who were unable to attend the workshops; referral templates and desktop summaries to provide reminders of the guidelines to clinicians; incorporation of standards into professional contracts.
Effects of change
A significant improvement occurred in identification and referral of patients with transient ischaemic attacks to specialist clinics, with a 41% increase in referrals from trained practices compared with control practices. There were also significant improvements in the early treatment and safety advice provided to patients before referral.
Lessons learnt
A strategic approach to effective quality improvement across a diverse health community is feasible and achievable. Careful planning with patient and professional involvement to develop a tailored and multifaceted quality improvement programme to implement evidence based practice can work in very different primary care settings. Key components of the effectiveness of the model include contextual analysis, strong professional support, clear recommendations based on robust evidence, simplicity of adoption, good communication, and use of established networks and opinion leaders.
doi:10.1136/qshc.2005.014704
PMCID: PMC2564006  PMID: 16456203
quality improvement report; stroke prevention; clinical guidelines; transient ischaemic attacks; implementation of change
5.  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
6.  Facilitators of health systems change for tobacco dependence treatment: a qualitative study of stakeholders’ perceptions 
Background
Health systems play key roles in identifying tobacco users and providing evidence-based care to help them quit. Health systems change – changes to health care processes, policies and financing – has potential to build capacity within these systems to address tobacco use. In 2010, ClearWay MinnesotaSM piloted a health systems change funding initiative, providing resources and technical assistance to four health care systems. This paper presents findings from a process evaluation, describing key stakeholders’ views on whether changes to how health systems treat tobacco use resulted from this initiative and what may have facilitated those changes.
Methods
A process evaluation was conducted by an independent evaluation firm. A qualitative case study approach provided understanding of systems change efforts. Interviews were conducted with key informants representing the health systems, funder and technical assistance providers. Core documents were reviewed and compared to thematic analysis from the interviews. Results were triangulated with existing literature to check for convergence or divergence. A cross-case analysis of the findings was conducted in which themes were compared and contrasted.
Results
All systems created and implemented well-defined written tobacco use screening, documentation and treatment referral protocols for every patient at every visit. Three implemented systematic follow-up procedures for patients referred to treatment, and three also implemented changes to electronic health records systems to facilitate screening, referral and reporting. Fax referral to quitline services was implemented or enhanced by two systems. Elements that facilitated successful systems changes included capitalizing on environmental changes, ensuring participation and support at all organizational levels, using technology, establishing ongoing training and continuous quality improvement mechanisms and leveraging external funding and technical assistance.
Conclusions
This evaluation demonstrates that health systems can implement substantial changes to facilitate routine treatment of tobacco dependence in a relatively short timeframe. Implementing best practices like these, including increased emphasis on the implementation and use of electronic health record systems and healthcare quality measures, is increasingly important given the changing health care environment. Lessons learned from this project can be resources for states and health systems likely to implement similar systems changes.
doi:10.1186/s12913-014-0575-4
PMCID: PMC4240875  PMID: 25407920
Tobacco; Systems change; Quality improvement; Electronic health records; Process evaluation
7.  Introduction of Electronic Referral from Community Associated with More Timely Review by Secondary Services 
Applied Clinical Informatics  2011;2(4):546-564.
Background
Electronic referral (eReferral) from community into public secondary healthcare services was introduced to 30 referring general medical practices and 28 hospital based services in late 2007.
Objectives
To measure the extent of uptake of eReferral and its association with changes in referral processing.
Methods
Analysis of transactional data from the eReferral message service and the patient information management system of the affected hospital; interview of clinical, operational and management stakeholders.
Results
eReferral use rose steadily to 1000 transactions per month in 2008, thereafter showing moderate growth to 1200 per month in 2010. Rate of eReferral from the community in 2010 is estimated at 56% of total referrals to the hospital from general practice, and as 71% of referrals from those having done at least one referral electronically. Referral latency from letter date to hospital triage improves significantly from 2007 to 2009 (p<0.001), from a paper referral median of 8 days (inter-quartile range, IQR: 4–14) in 2007 to an eReferral median of 5 days (IQR: 2–9) and paper referral median of 6 days (IQR: 2–12) in 2009. Specialists upgrade the referrer-assigned eReferral priority in 19.2% of cases and downgrade it 18.6% of the time. Clinical users appreciate improvement of referral visibility (status and content access); however, both general practitioners and specialists point out system usability issues.
Discussion
With eReferrals, a referral’s status can be checked, and its content read, by any authorized user at any time. The period of eReferral uptake was associated with significant speed-up in referral processing without changes in staffing levels. The eReferral system provides a foundation for further innovation in the community-secondary interface, such as electronic decision support and shared care planning systems.
Conclusions
We observed substantial rapid voluntary uptake of eReferrals associated with faster, more reliable and more transparent referral processing.
doi:10.4338/ACI-2011-06-RA-0039
PMCID: PMC3613003  PMID: 23616895
User acceptance and resistance; provider-provider communications; process improvement
8.  Recommendations for Syndromic Surveillance Using Inpatient and Ambulatory EHR Data 
Objective
To develop national Stage 2 Meaningful Use (MUse) recommendations for syndromic surveillance using hospital inpatient and ambulatory clinical care electronic health record (EHR) data.
Introduction
MUse will make EHR data increasingly available for public health surveillance. For Stage 2, the Centers for Medicare & Medicaid Services (CMS) regulations will require hospitals and offer an option for eligible professionals to provide electronic syndromic surveillance data to public health. Together, these data can strengthen public health surveillance capabilities and population health outcomes (Figure 1).
To facilitate the adoption and effective use of these data to advance population health, public health priorities and system capabilities must shape standards for data exchange. Input from all stakeholders is critical to ensure the feasibility, practicality, and, hence, adoption of any recommendations and data use guidelines.
Methods
ISDS, in collaboration with the Division of Informatics Solutions and Operations at the Centers for Disease Control and Prevention (CDC), and HLN Consulting, convened a multi-stakeholder Work-group of clinicians, technologists, epidemiologists, and public health officials with expertise in syndromic surveillance. Recommended MUse guidelines were developed by performing an environmental scan of current practice and by using an iterative, expert and community input-driven process. The Workgroup developed initial guidelines and then solicited and received feedback from the stakeholder community via interview, e-mail, and structured surveys. Stakeholder feedback was analyzed using quantitative and qualitative methods and used to revise the recommendations.
Results
The MUse Workgroup defined electronic syndromic surveillance (ESS) characteristics. Specifically, data are characterized by their timeliness, sensitivity rather than specificity, population focus, limited personally identifiable information, and inclusion of all patient encounters within a specific healthcare setting (e.g., emergency department, inpatient, outpatient). Based on stakeholder input (n=125) and Workgroup expertise, the guidelines identify priority syndromic surveillance uses that can assist with: Monitoring population health;Informing public health services; andInforming interventions, health education, and policy by characterizing the burden of chronic disease and health disparities.
Similarly, the Workgroup identified data elements to support these uses in the hospital inpatient setting and possibly in the ambulatory care setting. They were aligned to previously identified emergency department and urgent care center data elements and Stage 1–2 clinical MUse objectives. Core data elements (required for certification) cover treating facility; patient demographics; subjective and objective clinical findings, including chief complaint, body mass index, smoking history, diagnoses; and outcomes. Other data elements were designated as extended (not required for certification) or future (for future consideration). The data elements and their specifications are subject to change based on applicable state and local laws and practices.
Based on their findings and recommended guidelines detailed in the report, the Workgroup also identified community activities and additional investments that would best support public health agencies in using EHR technology with syndromic surveillance methodologies.
Conclusions
The widespread adoption of EHRs, catalyzed by MUse, has the potential to improve population health. By identifying and describing potential ESS uses of new sources of EHR data and associated data elements with the greatest utility for public health, the recommendations set forth by the ISDS MUse Workgroup will serve to facilitate the adoption of MUse policy by both healthcare and public health agencies.
PMCID: PMC3692899
EHR; syndromic surveillance; Meaningful Use; inpatient; ambulatory
9.  Towards successful coordination of electronic health record based-referrals: a qualitative analysis 
Background
Successful subspecialty referrals require considerable coordination and interactive communication among the primary care provider (PCP), the subspecialist, and the patient, which may be challenging in the outpatient setting. Even when referrals are facilitated by electronic health records (EHRs) (i.e., e-referrals), lapses in patient follow-up might occur. Although compelling reasons exist why referral coordination should be improved, little is known about which elements of the complex referral coordination process should be targeted for improvement. Using Okhuysen & Bechky's coordination framework, this paper aims to understand the barriers, facilitators, and suggestions for improving communication and coordination of EHR-based referrals in an integrated healthcare system.
Methods
We conducted a qualitative study to understand coordination breakdowns related to e-referrals in an integrated healthcare system and examined work-system factors that affect the timely receipt of subspecialty care. We conducted interviews with seven subject matter experts and six focus groups with a total of 30 PCPs and subspecialists at two tertiary care Department of Veterans Affairs (VA) medical centers. Using techniques from grounded theory and content analysis, we identified organizational themes that affected the referral process.
Results
Four themes emerged: lack of an institutional referral policy, lack of standardization in certain referral procedures, ambiguity in roles and responsibilities, and inadequate resources to adapt and respond to referral requests effectively. Marked differences in PCPs' and subspecialists' communication styles and individual mental models of the referral processes likely precluded the development of a shared mental model to facilitate coordination and successful referral completion. Notably, very few barriers related to the EHR were reported.
Conclusions
Despite facilitating information transfer between PCPs and subspecialists, e-referrals remain prone to coordination breakdowns. Clear referral policies, well-defined roles and responsibilities for key personnel, standardized procedures and communication protocols, and adequate human resources must be in place before implementing an EHR to facilitate referrals.
doi:10.1186/1748-5908-6-84
PMCID: PMC3199858  PMID: 21794109
10.  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
11.  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
12.  Implementing nursing best practice guidelines: Impact on patient referrals 
BMC Nursing  2007;6:4.
Background
Although referring patients to community services is important for optimum continuity of care, referrals between hospital and community sectors are often problematic. Nurses are well positioned to inform patients about referral resources. The objective of this study is to describe the impact of implementing six nursing best practice guidelines (BPGs) on nurses' familiarity with patient referral resources and referral practices.
Methods
A prospective before and after design was used. For each BPG topic, referral resources were identified. Information about these resources was presented at education sessions for nurses. Pre- and post-questionnaires were completed by a random sample of 257 nurses at 7 hospitals, 2 home visiting nursing services and 1 public health unit. Average response rates for pre- and post-implementation questionnaires were 71% and 54.2%, respectively. Chart audits were completed for three BPGs (n = 421 pre- and 332 post-implementation). Post-hospital discharge patient interviews were conducted for four BPGs (n = 152 pre- and 124 post-implementation).
Results
There were statistically significant increases in nurses' familiarity with resources for all BPGs, and self-reported referrals to specific services for three guidelines. Higher rates of referrals were observed for services that were part of the organization where the nurses worked. There was almost a complete lack of referrals to Internet sources. No significant differences between pre- and post-implementation referrals rates were observed in the chart documentation or in patients' reports of referrals.
Conclusion
Implementing nursing BPGs, which included recommendations on patient referrals produced mixed results. Nurses' familiarity with referral resources does not necessarily change their referral practices. Nurses can play a vital role in initiating and supporting appropriate patient referrals. BPGs should include specific recommendations on effective referral processes and this information should be tailored to the community setting where implementation is taking place.
doi:10.1186/1472-6955-6-4
PMCID: PMC1947981  PMID: 17598917
13.  Implementation and adoption of nationwide electronic health records in secondary care in England: qualitative analysis of interim results from a prospective national evaluation 
Objectives To describe and evaluate the implementation and adoption of detailed electronic health records in secondary care in England and thereby provide early feedback for the ongoing local and national rollout of the NHS Care Records Service.
Design A mixed methods, longitudinal, multisite, socio-technical case study.
Setting Five NHS acute hospital and mental health trusts that have been the focus of early implementation efforts and at which interim data collection and analysis are complete.
Data sources and analysis Dataset for the evaluation consists of semi-structured interviews, documents and field notes, observations, and quantitative data. Qualitative data were analysed thematically with a socio-technical coding matrix, combined with additional themes that emerged from the data.
Main results Hospital electronic health record applications are being developed and implemented far more slowly than was originally envisioned; the top-down, standardised approach has needed to evolve to admit more variation and greater local choice, which hospital trusts want in order to support local activity. Despite considerable delays and frustrations, support for electronic health records remains strong, including from NHS clinicians. Political and financial factors are now perceived to threaten nationwide implementation of electronic health records. Interviewees identified a range of consequences of long term, centrally negotiated contracts to deliver the NHS Care Records Service in secondary care, particularly as NHS trusts themselves are not party to these contracts. These include convoluted communication channels between different stakeholders, unrealistic deployment timelines, delays, and applications that could not quickly respond to changing national and local NHS priorities. Our data suggest support for a “middle-out” approach to implementing hospital electronic health records, combining government direction with increased local autonomy, and for restricting detailed electronic health record sharing to local health communities.
Conclusions Experiences from the early implementation sites, which have received considerable attention, financial investment and support, indicate that delivering improved healthcare through nationwide electronic health records will be a long, complex, and iterative process requiring flexibility and local adaptability both with respect to the systems and the implementation strategy. The more tailored, responsive approach that is emerging is becoming better aligned with NHS organisations’ perceived needs and is, if pursued, likely to deliver clinically useful electronic health record systems.
doi:10.1136/bmj.c4564
PMCID: PMC2933355  PMID: 20813822
14.  A knowledge-based taxonomy of critical factors for adopting electronic health record systems by physicians: a systematic literature review 
Background
The health care sector is an area of social and economic interest in several countries; therefore, there have been lots of efforts in the use of electronic health records. Nevertheless, there is evidence suggesting that these systems have not been adopted as it was expected, and although there are some proposals to support their adoption, the proposed support is not by means of information and communication technology which can provide automatic tools of support. The aim of this study is to identify the critical adoption factors for electronic health records by physicians and to use them as a guide to support their adoption process automatically.
Methods
This paper presents, based on the PRISMA statement, a systematic literature review in electronic databases with adoption studies of electronic health records published in English. Software applications that manage and process the data in the electronic health record have been considered, i.e.: computerized physician prescription, electronic medical records, and electronic capture of clinical data. Our review was conducted with the purpose of obtaining a taxonomy of the physicians main barriers for adopting electronic health records, that can be addressed by means of information and communication technology; in particular with the information technology roles of the knowledge management processes. Which take us to the question that we want to address in this work: "What are the critical adoption factors of electronic health records that can be supported by information and communication technology?". Reports from eight databases covering electronic health records adoption studies in the medical domain, in particular those focused on physicians, were analyzed.
Results
The review identifies two main issues: 1) a knowledge-based classification of critical factors for adopting electronic health records by physicians; and 2) the definition of a base for the design of a conceptual framework for supporting the design of knowledge-based systems, to assist the adoption process of electronic health records in an automatic fashion. From our review, six critical adoption factors have been identified: user attitude towards information systems, workflow impact, interoperability, technical support, communication among users, and expert support. The main limitation of the taxonomy is the different impact of the adoption factors of electronic health records reported by some studies depending on the type of practice, setting, or attention level; however, these features are a determinant aspect with regard to the adoption rate for the latter rather than the presence of a specific critical adoption factor.
Conclusions
The critical adoption factors established here provide a sound theoretical basis for research to understand, support, and facilitate the adoption of electronic health records to physicians in benefit of patients.
doi:10.1186/1472-6947-10-60
PMCID: PMC2970582  PMID: 20950458
15.  e-Health, m-Health and healthier social media reform: the big scale view 
Introduction
In the upcoming decade, digital platforms will be the backbone of a strategic revolution in the way medical services are provided, affecting both healthcare providers and patients. Digital-based patient-centered healthcare services allow patients to actively participate in managing their own care, in times of health as well as illness, using personally tailored interactive tools. Such empowerment is expected to increase patients’ willingness to adopt actions and lifestyles that promote health as well as improve follow-up and compliance with treatment in cases of chronic illness. Clalit Health Services (CHS) is the largest HMO in Israel and second largest world-wide. Through its 14 hospitals, 1300 primary and specialized clinics, and 650 pharmacies, CHS provides comprehensive medical care to the majority of Israel’s population (above 4 million members). CHS e-Health wing focuses on deepening patient involvement in managing health, through personalized digital interactive tools. Currently, CHS e-Health wing provides e-health services for 1.56 million unique patients monthly with 2.4 million interactions every month (August 2011). Successful implementation of e-Health solutions is not a sum of technology, innovation and health; rather it’s the expertise of tailoring knowledge and leadership capabilities in multidisciplinary areas: clinical, ethical, psychological, legal, comprehension of patient and medical team engagement etc. The Google Health case excellently demonstrates this point. On the other hand, our success with CHS is a demonstration that e-Health can be enrolled effectively and fast with huge benefits for both patients and medical teams, and with a robust business model.
CHS e-Health core components
They include:
1. The personal health record layer (what the patient can see) presents patients with their own medical history as well as the medical history of their preadult children, including diagnoses, allergies, vaccinations, laboratory results with interpretations in layman’s terms, medications with clear, straightforward explanations regarding dosing instructions, important side effects, contraindications, such as lactation etc., and other important medical information. All personal e-Health services require identification and authorization.
2. The personal knowledge layer (what the patient should know) presents patients with personally tailored recommendations for preventative medicine and health promotion. For example, diabetic patients are push notified regarding their yearly eye exam. The various health recommendations include: occult blood testing, mammography, lipid profile etc. Each recommendation contains textual, visual and interactive content components in order to promote engagement and motivate the patient to actually change his health behaviour.
3. The personal health services layer (what the patient can do) enables patients to schedule clinic visits, order chronic prescriptions, e-consult their physician via secured e-mail, set SMS medication reminders, e-consult a pharmacist regarding personal medications. Consultants’ answers are sent securely to the patients’ personal mobile device.
On December 2009 CHS launched secured, web based, synchronous medical consultation via video conference. Currently 11,780 e-visits are performed monthly (May 2011). The medical encounter includes e-prescription and referral capabilities which are biometrically signed by the physician. On December 2010 CHS launched a unique mobile health platform, which is one of the most comprehensive personal m-Health applications world-wide. An essential advantage of mobile devices is their potential to bridge the digital divide. Currently, CHS m-Health platform is used by more than 45,000 unique users, with 75,000 laboratory results views/month, 1100 m-consultations/month and 9000 physician visit scheduling/month.
4. The Bio-Sensing layer (what physiological data the patient can populate) includes diagnostic means that allow remote physical examination, bio-sensors that broadcast various physiological measurements, and smart homecare devices, such as e-Pill boxes that gives seniors, patients and their caregivers the ability to stay at home and live life to its fullest. Monitored data is automatically transmitted to the patient’s Personal Health Record and to relevant medical personnel.
The monitoring layer is embedded in the chronic disease management platform, and in the interactive health promotion and wellness platform. It includes tailoring of consumer-oriented medical devices and service provided by various professional personnel—physicians, nurses, pharmacists, dieticians and more.
5. The Social layer (what the patient can share). Social media networks triggered an essential change at the humanity ‘genome’ level, yet to be further defined in the upcoming years. Social media has huge potential in promoting health as it combines fun, simple yet extraordinary user experience, and bio-social-feedback. There are two major challenges in leveraging health care through social networks:
a. Our personal health information is the cornerstone for personalizing healthier lifestyle, disease management and preventative medicine. We naturally see our personal health data as a super-private territory. So, how do we bring the power of our private health information, currently locked within our Personal Health Record, into social media networks without offending basic privacy issues?
b. Disease management and preventive medicine are currently neither considered ‘cool’ nor ‘fun’ or ‘potentially highly viral’ activities; yet, health is a major issue of everybody’s life. It seems like we are missing a crucial element with a huge potential in health behavioural change—the Fun Theory. Social media platforms comprehends user experience tools that potentially could break current misconception, and engage people in the daily task of taking better care of themselves.
CHS e-Health innovation team characterized several break-through applications in this unexplored territory within social media networks, fusing personal health and social media platforms without offending privacy. One of the most crucial issues regarding adoption of e-health and m-health platforms is change management. Being a ‘hot’ innovative ‘gadget’ is far from sufficient for changing health behaviours at the individual and population levels.
CHS health behaviour change management methodology includes 4 core elements:
1. Engaging two completely different populations: patients, and medical teams. e-Health applications must present true added value for both medical teams and patients, engaging them through understanding and assimilating “what’s really in it for me”. Medical teams are further subdivided into physicians, nurses, pharmacists and administrative personnel—each with their own driving incentive. Resistance to change is an obstacle in many fields but it is particularly true in the conservative health industry. To successfully manage a large scale persuasive process, we treat intra-organizational human resources as “Change Agents”. Harnessing the persuasive power of ~40,000 employees requires engaging them as the primary target group. Successful recruitment has the potential of converting each patient-medical team interaction into an exposure opportunity to the new era of participatory medicine via e-health and m-health channels.
2. Implementation waves: every group of digital health products that are released at the same time are seen as one project. Each implementation wave leverages the focus of the organization and target populations to a defined time span. There are three major and three minor implementation waves a year.
3. Change-Support Arrow: a structured infrastructure for every implementation wave. The sub-stages in this strategy include:
Cross organizational mapping and identification of early adopters and stakeholders relevant to the implementation wave
Mapping positive or negative perceptions and designing specific marketing approaches for the distinct target groups
Intra and extra organizational marketing
Conducting intensive training and presentation sessions for groups of implementers
Running conflict-prevention activities, such as advanced tackling of potential union resistance
Training change-agents with resistance-management behavioural techniques, focused intervention for specific incidents and for key opinion leaders
Extensive presence in the clinics during the launch period, etc.
The entire process is monitored and managed continuously by a review team.
4. Closing Phase: each wave is analyzed and a “lessons-learned” session concludes the changes required in the modus operandi of the e-health project team.
PMCID: PMC3571141
e-Health; mobile health; personal health record; online visit; patient empowerment; knowledge prescription
16.  Co-Creation With TickiT: Designing and Evaluating a Clinical eHealth Platform for Youth 
JMIR Research Protocols  2013;2(2):e42.
Background
All youth are susceptible to mental health issues and engaging in risky behavior, and for youth with chronic health conditions, the consequences can be more significant than in their healthy peers. Standardized paper-based questionnaires are recommended by the American Academy of Pediatrics in community practice to screen for health risks. In hospitals, psychosocial screening is traditionally undertaken using the Home Education, Eating, Activities, Drugs, Depression, Sex, Safety (HEEADDSS) interview. However, time constraints and patient/provider discomfort reduce implementation. We report findings from an eHealth initiative undertaken to improve uptake of psychosocial screening among youth.
Objective
Youth are sophisticated “technology natives.” Our objective was to leverage youth’s comfort with technology, creating a youth-friendly interactive mobile eHealth psychosocial screening tool, TickiT. Patients enter data into the mobile application prior to a clinician visit. Response data is recorded in a report, which generates alerts for clinicians, shifting the clinical focus from collecting information to focused management. Design goals included improving the patient experience, improving efficiency through electronic patient based data entry, and supporting the collection of aggregated data for research.
Methods
This paper describes the iterative design and evaluation processes undertaken to develop TickiT including co-creation processes, and a pilot study utilizing mixed qualitative and quantitative methods. A collaborative industry/academic partnership engaged stakeholders (youth, health care providers, and administrators) in the co-creation development process. An independent descriptive study conducted in 2 Canadian pediatric teaching hospitals evaluated the feasibility of the platform in both inpatient and ambulatory clinical settings, evaluating both providers and patient responses to the platform.
Results
The independent pilot feasibility study included 80 adolescents, 12-18 years, and 38 medical staff-residents, inpatient and outpatient pediatricians, and surgeons. Youth uptake was 99% (79/80), and survey completion 99% (78/79; 90 questions). Youth found it easy to understand (92%, 72/78), easy to use (92%, 72/78), and efficient (80%, 63/79 with completion rate < 10 minutes). Residents were most positive about the application and surgeons were least positive. All inpatient providers obtained new patient information.
Conclusions
Co-creative design methodology with stakeholders was effective for informing design and development processes to leverage effective eHealth opportunities. Continuing stakeholder engagement has further fostered platform development. The platform has the potential to meet IHI Triple Aim goals. Clinical adaptation requires planning, training, and support for health care providers to adjust their practices.
doi:10.2196/resprot.2865
PMCID: PMC3806391  PMID: 24140595
adolescent; adolescent health services; youth; eHealth; information technology; health surveys; delivery of health care; communication; chronic illness; mobile technology; questionnaires
17.  Internet-Based Device-Assisted Remote Monitoring of Cardiovascular Implantable Electronic Devices 
Executive Summary
Objective
The objective of this Medical Advisory Secretariat (MAS) report was to conduct a systematic review of the available published evidence on the safety, effectiveness, and cost-effectiveness of Internet-based device-assisted remote monitoring systems (RMSs) for therapeutic cardiac implantable electronic devices (CIEDs) such as pacemakers (PMs), implantable cardioverter-defibrillators (ICDs), and cardiac resynchronization therapy (CRT) devices. The MAS evidence-based review was performed to support public financing decisions.
Clinical Need: Condition and Target Population
Sudden cardiac death (SCD) is a major cause of fatalities in developed countries. In the United States almost half a million people die of SCD annually, resulting in more deaths than stroke, lung cancer, breast cancer, and AIDS combined. In Canada each year more than 40,000 people die from a cardiovascular related cause; approximately half of these deaths are attributable to SCD.
Most cases of SCD occur in the general population typically in those without a known history of heart disease. Most SCDs are caused by cardiac arrhythmia, an abnormal heart rhythm caused by malfunctions of the heart’s electrical system. Up to half of patients with significant heart failure (HF) also have advanced conduction abnormalities.
Cardiac arrhythmias are managed by a variety of drugs, ablative procedures, and therapeutic CIEDs. The range of CIEDs includes pacemakers (PMs), implantable cardioverter-defibrillators (ICDs), and cardiac resynchronization therapy (CRT) devices. Bradycardia is the main indication for PMs and individuals at high risk for SCD are often treated by ICDs.
Heart failure (HF) is also a significant health problem and is the most frequent cause of hospitalization in those over 65 years of age. Patients with moderate to severe HF may also have cardiac arrhythmias, although the cause may be related more to heart pump or haemodynamic failure. The presence of HF, however, increases the risk of SCD five-fold, regardless of aetiology. Patients with HF who remain highly symptomatic despite optimal drug therapy are sometimes also treated with CRT devices.
With an increasing prevalence of age-related conditions such as chronic HF and the expanding indications for ICD therapy, the rate of ICD placement has been dramatically increasing. The appropriate indications for ICD placement, as well as the rate of ICD placement, are increasingly an issue. In the United States, after the introduction of expanded coverage of ICDs, a national ICD registry was created in 2005 to track these devices. A recent survey based on this national ICD registry reported that 22.5% (25,145) of patients had received a non-evidence based ICD and that these patients experienced significantly higher in-hospital mortality and post-procedural complications.
In addition to the increased ICD device placement and the upfront device costs, there is the need for lifelong follow-up or surveillance, placing a significant burden on patients and device clinics. In 2007, over 1.6 million CIEDs were implanted in Europe and the United States, which translates to over 5.5 million patient encounters per year if the recommended follow-up practices are considered. A safe and effective RMS could potentially improve the efficiency of long-term follow-up of patients and their CIEDs.
Technology
In addition to being therapeutic devices, CIEDs have extensive diagnostic abilities. All CIEDs can be interrogated and reprogrammed during an in-clinic visit using an inductive programming wand. Remote monitoring would allow patients to transmit information recorded in their devices from the comfort of their own homes. Currently most ICD devices also have the potential to be remotely monitored. Remote monitoring (RM) can be used to check system integrity, to alert on arrhythmic episodes, and to potentially replace in-clinic follow-ups and manage disease remotely. They do not currently have the capability of being reprogrammed remotely, although this feature is being tested in pilot settings.
Every RMS is specifically designed by a manufacturer for their cardiac implant devices. For Internet-based device-assisted RMSs, this customization includes details such as web application, multiplatform sensors, custom algorithms, programming information, and types and methods of alerting patients and/or physicians. The addition of peripherals for monitoring weight and pressure or communicating with patients through the onsite communicators also varies by manufacturer. Internet-based device-assisted RMSs for CIEDs are intended to function as a surveillance system rather than an emergency system.
Health care providers therefore need to learn each application, and as more than one application may be used at one site, multiple applications may need to be reviewed for alarms. All RMSs deliver system integrity alerting; however, some systems seem to be better geared to fast arrhythmic alerting, whereas other systems appear to be more intended for remote follow-up or supplemental remote disease management. The different RMSs may therefore have different impacts on workflow organization because of their varying frequency of interrogation and methods of alerts. The integration of these proprietary RM web-based registry systems with hospital-based electronic health record systems has so far not been commonly implemented.
Currently there are 2 general types of RMSs: those that transmit device diagnostic information automatically and without patient assistance to secure Internet-based registry systems, and those that require patient assistance to transmit information. Both systems employ the use of preprogrammed alerts that are either transmitted automatically or at regular scheduled intervals to patients and/or physicians.
The current web applications, programming, and registry systems differ greatly between the manufacturers of transmitting cardiac devices. In Canada there are currently 4 manufacturers—Medtronic Inc., Biotronik, Boston Scientific Corp., and St Jude Medical Inc.—which have regulatory approval for remote transmitting CIEDs. Remote monitoring systems are proprietary to the manufacturer of the implant device. An RMS for one device will not work with another device, and the RMS may not work with all versions of the manufacturer’s devices.
All Internet-based device-assisted RMSs have common components. The implanted device is equipped with a micro-antenna that communicates with a small external device (at bedside or wearable) commonly known as the transmitter. Transmitters are able to interrogate programmed parameters and diagnostic data stored in the patients’ implant device. The information transfer to the communicator can occur at preset time intervals with the participation of the patient (waving a wand over the device) or it can be sent automatically (wirelessly) without their participation. The encrypted data are then uploaded to an Internet-based database on a secure central server. The data processing facilities at the central database, depending on the clinical urgency, can trigger an alert for the physician(s) that can be sent via email, fax, text message, or phone. The details are also posted on the secure website for viewing by the physician (or their delegate) at their convenience.
Research Questions
The research directions and specific research questions for this evidence review were as follows:
To identify the Internet-based device-assisted RMSs available for follow-up of patients with therapeutic CIEDs such as PMs, ICDs, and CRT devices.
To identify the potential risks, operational issues, or organizational issues related to Internet-based device-assisted RM for CIEDs.
To evaluate the safety, acceptability, and effectiveness of Internet-based device-assisted RMSs for CIEDs such as PMs, ICDs, and CRT devices.
To evaluate the safety, effectiveness, and cost-effectiveness of Internet-based device-assisted RMSs for CIEDs compared to usual outpatient in-office monitoring strategies.
To evaluate the resource implications or budget impact of RMSs for CIEDs in Ontario, Canada.
Research Methods
Literature Search
The review included a systematic review of published scientific literature and consultations with experts and manufacturers of all 4 approved RMSs for CIEDs in Canada. Information on CIED cardiac implant clinics was also obtained from Provincial Programs, a division within the Ministry of Health and Long-Term Care with a mandate for cardiac implant specialty care. Various administrative databases and registries were used to outline the current clinical follow-up burden of CIEDs in Ontario. The provincial population-based ICD database developed and maintained by the Institute for Clinical Evaluative Sciences (ICES) was used to review the current follow-up practices with Ontario patients implanted with ICD devices.
Search Strategy
A literature search was performed on September 21, 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 1950 to September 2010. Search alerts were generated and reviewed for additional relevant literature until December 31, 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.
Inclusion Criteria
published between 1950 and September 2010;
English language full-reports and human studies;
original reports including clinical evaluations of Internet-based device-assisted RMSs for CIEDs in clinical settings;
reports including standardized measurements on outcome events such as technical success, safety, effectiveness, cost, measures of health care utilization, morbidity, mortality, quality of life or patient satisfaction;
randomized controlled trials (RCTs), systematic reviews and meta-analyses, cohort and controlled clinical studies.
Exclusion Criteria
non-systematic reviews, letters, comments and editorials;
reports not involving standardized outcome events;
clinical reports not involving Internet-based device assisted RM systems for CIEDs in clinical settings;
reports involving studies testing or validating algorithms without RM;
studies with small samples (<10 subjects).
Outcomes of Interest
The outcomes of interest included: technical outcomes, emergency department visits, complications, major adverse events, symptoms, hospital admissions, clinic visits (scheduled and/or unscheduled), survival, morbidity (disease progression, stroke, etc.), patient satisfaction, and quality of life.
Summary of Findings
The MAS evidence review was performed to review available evidence on Internet-based device-assisted RMSs for CIEDs published until September 2010. The search identified 6 systematic reviews, 7 randomized controlled trials, and 19 reports for 16 cohort studies—3 of these being registry-based and 4 being multi-centered. The evidence is summarized in the 3 sections that follow.
1. Effectiveness of Remote Monitoring Systems of CIEDs for Cardiac Arrhythmia and Device Functioning
In total, 15 reports on 13 cohort studies involving investigations with 4 different RMSs for CIEDs in cardiology implant clinic groups were identified in the review. The 4 RMSs were: Care Link Network® (Medtronic Inc,, Minneapolis, MN, USA); Home Monitoring® (Biotronic, Berlin, Germany); House Call 11® (St Jude Medical Inc., St Pauls, MN, USA); and a manufacturer-independent RMS. Eight of these reports were with the Home Monitoring® RMS (12,949 patients), 3 were with the Care Link® RMS (167 patients), 1 was with the House Call 11® RMS (124 patients), and 1 was with a manufacturer-independent RMS (44 patients). All of the studies, except for 2 in the United States, (1 with Home Monitoring® and 1 with House Call 11®), were performed in European countries.
The RMSs in the studies were evaluated with different cardiac implant device populations: ICDs only (6 studies), ICD and CRT devices (3 studies), PM and ICD and CRT devices (4 studies), and PMs only (2 studies). The patient populations were predominately male (range, 52%–87%) in all studies, with mean ages ranging from 58 to 76 years. One study population was unique in that RMSs were evaluated for ICDs implanted solely for primary prevention in young patients (mean age, 44 years) with Brugada syndrome, which carries an inherited increased genetic risk for sudden heart attack in young adults.
Most of the cohort studies reported on the feasibility of RMSs in clinical settings with limited follow-up. In the short follow-up periods of the studies, the majority of the events were related to detection of medical events rather than system configuration or device abnormalities. The results of the studies are summarized below:
The interrogation of devices on the web platform, both for continuous and scheduled transmissions, was significantly quicker with remote follow-up, both for nurses and physicians.
In a case-control study focusing on a Brugada population–based registry with patients followed-up remotely, there were significantly fewer outpatient visits and greater detection of inappropriate shocks. One death occurred in the control group not followed remotely and post-mortem analysis indicated early signs of lead failure prior to the event.
Two studies examined the role of RMSs in following ICD leads under regulatory advisory in a European clinical setting and noted:
– Fewer inappropriate shocks were administered in the RM group.
– Urgent in-office interrogations and surgical revisions were performed within 12 days of remote alerts.
– No signs of lead fracture were detected at in-office follow-up; all were detected at remote follow-up.
Only 1 study reported evaluating quality of life in patients followed up remotely at 3 and 6 months; no values were reported.
Patient satisfaction was evaluated in 5 cohort studies, all in short term follow-up: 1 for the Home Monitoring® RMS, 3 for the Care Link® RMS, and 1 for the House Call 11® RMS.
– Patients reported receiving a sense of security from the transmitter, a good relationship with nurses and physicians, positive implications for their health, and satisfaction with RM and organization of services.
– Although patients reported that the system was easy to implement and required less than 10 minutes to transmit information, a variable proportion of patients (range, 9% 39%) reported that they needed the assistance of a caregiver for their transmission.
– The majority of patients would recommend RM to other ICD patients.
– Patients with hearing or other physical or mental conditions hindering the use of the system were excluded from studies, but the frequency of this was not reported.
Physician satisfaction was evaluated in 3 studies, all with the Care Link® RMS:
– Physicians reported an ease of use and high satisfaction with a generally short-term use of the RMS.
– Physicians reported being able to address the problems in unscheduled patient transmissions or physician initiated transmissions remotely, and were able to handle the majority of the troubleshooting calls remotely.
– Both nurses and physicians reported a high level of satisfaction with the web registry system.
2. Effectiveness of Remote Monitoring Systems in Heart Failure Patients for Cardiac Arrhythmia and Heart Failure Episodes
Remote follow-up of HF patients implanted with ICD or CRT devices, generally managed in specialized HF clinics, was evaluated in 3 cohort studies: 1 involved the Home Monitoring® RMS and 2 involved the Care Link® RMS. In these RMSs, in addition to the standard diagnostic features, the cardiac devices continuously assess other variables such as patient activity, mean heart rate, and heart rate variability. Intra-thoracic impedance, a proxy measure for lung fluid overload, was also measured in the Care Link® studies. The overall diagnostic performance of these measures cannot be evaluated, as the information was not reported for patients who did not experience intra-thoracic impedance threshold crossings or did not undergo interventions. The trial results involved descriptive information on transmissions and alerts in patients experiencing high morbidity and hospitalization in the short study periods.
3. Comparative Effectiveness of Remote Monitoring Systems for CIEDs
Seven RCTs were identified evaluating RMSs for CIEDs: 2 were for PMs (1276 patients) and 5 were for ICD/CRT devices (3733 patients). Studies performed in the clinical setting in the United States involved both the Care Link® RMS and the Home Monitoring® RMS, whereas all studies performed in European countries involved only the Home Monitoring® RMS.
3A. Randomized Controlled Trials of Remote Monitoring Systems for Pacemakers
Two trials, both multicenter RCTs, were conducted in different countries with different RMSs and study objectives. The PREFER trial was a large trial (897 patients) performed in the United States examining the ability of Care Link®, an Internet-based remote PM interrogation system, to detect clinically actionable events (CAEs) sooner than the current in-office follow-up supplemented with transtelephonic monitoring transmissions, a limited form of remote device interrogation. The trial results are summarized below:
In the 375-day mean follow-up, 382 patients were identified with at least 1 CAE—111 patients in the control arm and 271 in the remote arm.
The event rate detected per patient for every type of CAE, except for loss of atrial capture, was higher in the remote arm than the control arm.
The median time to first detection of CAEs (4.9 vs. 6.3 months) was significantly shorter in the RMS group compared to the control group (P < 0.0001).
Additionally, only 2% (3/190) of the CAEs in the control arm were detected during a transtelephonic monitoring transmission (the rest were detected at in-office follow-ups), whereas 66% (446/676) of the CAEs were detected during remote interrogation.
The second study, the OEDIPE trial, was a smaller trial (379 patients) performed in France evaluating the ability of the Home Monitoring® RMS to shorten PM post-operative hospitalization while preserving the safety of conventional management of longer hospital stays.
Implementation and operationalization of the RMS was reported to be successful in 91% (346/379) of the patients and represented 8144 transmissions.
In the RM group 6.5% of patients failed to send messages (10 due to improper use of the transmitter, 2 with unmanageable stress). Of the 172 patients transmitting, 108 patients sent a total of 167 warnings during the trial, with a greater proportion of warnings being attributed to medical rather than technical causes.
Forty percent had no warning message transmission and among these, 6 patients experienced a major adverse event and 1 patient experienced a non-major adverse event. Of the 6 patients having a major adverse event, 5 contacted their physician.
The mean medical reaction time was faster in the RM group (6.5 ± 7.6 days vs. 11.4 ± 11.6 days).
The mean duration of hospitalization was significantly shorter (P < 0.001) for the RM group than the control group (3.2 ± 3.2 days vs. 4.8 ± 3.7 days).
Quality of life estimates by the SF-36 questionnaire were similar for the 2 groups at 1-month follow-up.
3B. Randomized Controlled Trials Evaluating Remote Monitoring Systems for ICD or CRT Devices
The 5 studies evaluating the impact of RMSs with ICD/CRT devices were conducted in the United States and in European countries and involved 2 RMSs—Care Link® and Home Monitoring ®. The objectives of the trials varied and 3 of the trials were smaller pilot investigations.
The first of the smaller studies (151 patients) evaluated patient satisfaction, achievement of patient outcomes, and the cost-effectiveness of the Care Link® RMS compared to quarterly in-office device interrogations with 1-year follow-up.
Individual outcomes such as hospitalizations, emergency department visits, and unscheduled clinic visits were not significantly different between the study groups.
Except for a significantly higher detection of atrial fibrillation in the RM group, data on ICD detection and therapy were similar in the study groups.
Health-related quality of life evaluated by the EuroQoL at 6-month or 12-month follow-up was not different between study groups.
Patients were more satisfied with their ICD care in the clinic follow-up group than in the remote follow-up group at 6-month follow-up, but were equally satisfied at 12- month follow-up.
The second small pilot trial (20 patients) examined the impact of RM follow-up with the House Call 11® system on work schedules and cost savings in patients randomized to 2 study arms varying in the degree of remote follow-up.
The total time including device interrogation, transmission time, data analysis, and physician time required was significantly shorter for the RM follow-up group.
The in-clinic waiting time was eliminated for patients in the RM follow-up group.
The physician talk time was significantly reduced in the RM follow-up group (P < 0.05).
The time for the actual device interrogation did not differ in the study groups.
The third small trial (115 patients) examined the impact of RM with the Home Monitoring® system compared to scheduled trimonthly in-clinic visits on the number of unplanned visits, total costs, health-related quality of life (SF-36), and overall mortality.
There was a 63.2% reduction in in-office visits in the RM group.
Hospitalizations or overall mortality (values not stated) were not significantly different between the study groups.
Patient-induced visits were higher in the RM group than the in-clinic follow-up group.
The TRUST Trial
The TRUST trial was a large multicenter RCT conducted at 102 centers in the United States involving the Home Monitoring® RMS for ICD devices for 1450 patients. The primary objectives of the trial were to determine if remote follow-up could be safely substituted for in-office clinic follow-up (3 in-office visits replaced) and still enable earlier physician detection of clinically actionable events.
Adherence to the protocol follow-up schedule was significantly higher in the RM group than the in-office follow-up group (93.5% vs. 88.7%, P < 0.001).
Actionability of trimonthly scheduled checks was low (6.6%) in both study groups. Overall, actionable causes were reprogramming (76.2%), medication changes (24.8%), and lead/system revisions (4%), and these were not different between the 2 study groups.
The overall mean number of in-clinic and hospital visits was significantly lower in the RM group than the in-office follow-up group (2.1 per patient-year vs. 3.8 per patient-year, P < 0.001), representing a 45% visit reduction at 12 months.
The median time from onset of first arrhythmia to physician evaluation was significantly shorter (P < 0.001) in the RM group than in the in-office follow-up group for all arrhythmias (1 day vs. 35.5 days).
The median time to detect clinically asymptomatic arrhythmia events—atrial fibrillation (AF), ventricular fibrillation (VF), ventricular tachycardia (VT), and supra-ventricular tachycardia (SVT)—was also significantly shorter (P < 0.001) in the RM group compared to the in-office follow-up group (1 day vs. 41.5 days) and was significantly quicker for each of the clinical arrhythmia events—AF (5.5 days vs. 40 days), VT (1 day vs. 28 days), VF (1 day vs. 36 days), and SVT (2 days vs. 39 days).
System-related problems occurred infrequently in both groups—in 1.5% of patients (14/908) in the RM group and in 0.7% of patients (3/432) in the in-office follow-up group.
The overall adverse event rate over 12 months was not significantly different between the 2 groups and individual adverse events were also not significantly different between the RM group and the in-office follow-up group: death (3.4% vs. 4.9%), stroke (0.3% vs. 1.2%), and surgical intervention (6.6% vs. 4.9%), respectively.
The 12-month cumulative survival was 96.4% (95% confidence interval [CI], 95.5%–97.6%) in the RM group and 94.2% (95% confidence interval [CI], 91.8%–96.6%) in the in-office follow-up group, and was not significantly different between the 2 groups (P = 0.174).
The CONNECT Trial
The CONNECT trial, another major multicenter RCT, involved the Care Link® RMS for ICD/CRT devices in a15-month follow-up study of 1,997 patients at 133 sites in the United States. The primary objective of the trial was to determine whether automatically transmitted physician alerts decreased the time from the occurrence of clinically relevant events to medical decisions. The trial results are summarized below:
Of the 575 clinical alerts sent in the study, 246 did not trigger an automatic physician alert. Transmission failures were related to technical issues such as the alert not being programmed or not being reset, and/or a variety of patient factors such as not being at home and the monitor not being plugged in or set up.
The overall mean time from the clinically relevant event to the clinical decision was significantly shorter (P < 0.001) by 17.4 days in the remote follow-up group (4.6 days for 172 patients) than the in-office follow-up group (22 days for 145 patients).
– The median time to a clinical decision was shorter in the remote follow-up group than in the in-office follow-up group for an AT/AF burden greater than or equal to 12 hours (3 days vs. 24 days) and a fast VF rate greater than or equal to 120 beats per minute (4 days vs. 23 days).
Although infrequent, similar low numbers of events involving low battery and VF detection/therapy turned off were noted in both groups. More alerts, however, were noted for out-of-range lead impedance in the RM group (18 vs. 6 patients), and the time to detect these critical events was significantly shorter in the RM group (same day vs. 17 days).
Total in-office clinic visits were reduced by 38% from 6.27 visits per patient-year in the in-office follow-up group to 3.29 visits per patient-year in the remote follow-up group.
Health care utilization visits (N = 6,227) that included cardiovascular-related hospitalization, emergency department visits, and unscheduled clinic visits were not significantly higher in the remote follow-up group.
The overall mean length of hospitalization was significantly shorter (P = 0.002) for those in the remote follow-up group (3.3 days vs. 4.0 days) and was shorter both for patients with ICD (3.0 days vs. 3.6 days) and CRT (3.8 days vs. 4.7 days) implants.
The mortality rate between the study arms was not significantly different between the follow-up groups for the ICDs (P = 0.31) or the CRT devices with defribillator (P = 0.46).
Conclusions
There is limited clinical trial information on the effectiveness of RMSs for PMs. However, for RMSs for ICD devices, multiple cohort studies and 2 large multicenter RCTs demonstrated feasibility and significant reductions in in-office clinic follow-ups with RMSs in the first year post implantation. The detection rates of clinically significant events (and asymptomatic events) were higher, and the time to a clinical decision for these events was significantly shorter, in the remote follow-up groups than in the in-office follow-up groups. The earlier detection of clinical events in the remote follow-up groups, however, was not associated with lower morbidity or mortality rates in the 1-year follow-up. The substitution of almost all the first year in-office clinic follow-ups with RM was also not associated with an increased health care utilization such as emergency department visits or hospitalizations.
The follow-up in the trials was generally short-term, up to 1 year, and was a more limited assessment of potential longer term device/lead integrity complications or issues. None of the studies compared the different RMSs, particularly the different RMSs involving patient-scheduled transmissions or automatic transmissions. Patients’ acceptance of and satisfaction with RM were reported to be high, but the impact of RM on patients’ health-related quality of life, particularly the psychological aspects, was not evaluated thoroughly. Patients who are not technologically competent, having hearing or other physical/mental impairments, were identified as potentially disadvantaged with remote surveillance. Cohort studies consistently identified subgroups of patients who preferred in-office follow-up. The evaluation of costs and workflow impact to the health care system were evaluated in European or American clinical settings, and only in a limited way.
Internet-based device-assisted RMSs involve a new approach to monitoring patients, their disease progression, and their CIEDs. Remote monitoring also has the potential to improve the current postmarket surveillance systems of evolving CIEDs and their ongoing hardware and software modifications. At this point, however, there is insufficient information to evaluate the overall impact to the health care system, although the time saving and convenience to patients and physicians associated with a substitution of in-office follow-up by RM is more certain. The broader issues surrounding infrastructure, impacts on existing clinical care systems, and regulatory concerns need to be considered for the implementation of Internet-based RMSs in jurisdictions involving different clinical practices.
PMCID: PMC3377571  PMID: 23074419
18.  Introduction of mobile phones for use by volunteer community health workers in support of integrated community case management in Bushenyi District, Uganda: development and implementation process 
BMC Health Services Research  2014;14(Suppl 1):S2.
Background
A substantial literature suggests that mobile phones have great potential to improve management and survival of acutely ill children in rural Africa. The national strategy of the Ugandan Ministry of Health calls for employment of volunteer community health workers (CHWs) in implementation of Integrated Community Case Management (iCCM) of common illnesses (diarrhea, acute respiratory infection, pneumonia, fever/malaria) affecting children under five years of age. A mobile phone enabled system was developed within iCCM aiming to improve access by CHWs to medical advice and to strengthen reporting of data on danger signs and symptoms for acutely ill children under five years of age. Herein critical steps in development, implementation, and integration of mobile phone technology within iCCM are described.
Methods
Mechanisms to improve diagnosis, treatment and referral of sick children under five were defined. Treatment algorithms were developed by the project technical team and mounted and piloted on the mobile phones, using an iterative process involving technical support personnel, health care providers, and academic support. Using a purposefully developed mobile phone training manual, CHWs were trained over an intensive five-day course to make timely diagnoses, recognize clinical danger signs, communicate about referrals and initiate treatment with appropriate essential drugs. Performance by CHWs and the accuracy and completeness of their submitted data was closely monitored post training test period and during the subsequent nine month community trial. In the full trial, the number of referrals and correctly treated children, based on the agreed treatment algorithms, was recorded. Births, deaths, and medication stocks were also tracked.
Results and Discussion
Seven distinct phases were required to develop a robust mobile phone enabled system in support of the iCCM program. Over a nine month period, 96 CHWs were trained to use mobile phones and their competence to initiate a community trial was established through performance monitoring.
Conclusion
Local information/communication consultants, working in concert with a university based department of pediatrics, can design and implement a robust mobile phone based system that may be anticipated to contribute to efficient delivery of iCCM by trained volunteer CHWs in rural settings in Uganda.
doi:10.1186/1472-6963-14-S1-S2
PMCID: PMC4108866  PMID: 25079241
mobile phone; child health; pediatric therapeutics; integrated community case management; community health worker; Uganda; téléphone mobile; santé des enfants; thérapeutique pédiatrique; gestion communautaire intégrée des cas; travailleur en santé communautaire; Ouganda
19.  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
20.  Pragmatic randomised controlled trial to evaluate guidelines for the management of infertility across the primary care-secondary care interface 
BMJ : British Medical Journal  2001;322(7297):1282.
Objective
To investigate the effect of clinical guidelines on the management of infertility across the primary care-secondary care interface.
Design
Cluster randomised controlled trial.
Setting
General practices and NHS hospitals accepting referrals for infertility in the Greater Glasgow Health Board area.
Participants
All 221 general practices in Glasgow; 214 completed the trial.
Intervention
General practices in the intervention arm received clinical guidelines developed locally. Control practices received them one year later. Dissemination of the guidelines included educational meetings.
Main outcome measures
The time from presentation to referral, investigations completed in general practice, the number and content of visits as a hospital outpatient, the time to reach a management plan, and costs for referrals from the two groups.
Results
Data on 689 referrals were collected. No significant difference was found in referral rates for infertility. Fewer than 1% of couples were referred inappropriately early. Referrals from intervention practices were significantly more likely to have all relevant investigations carried out (odds ratio 1.32, 95% confidence interval 1.00 to 1.75, P=0.025). 70% of measurements of serum progesterone concentrations during the midluteal phase and 34% of semen analyses were repeated at least once in hospital, despite having been recorded as normal when checked in general practice. No difference was found in the proportion of referrals in which a management plan was reached within one year or in the mean duration between first appointment and date of management plan. NHS costs were not significantly affected.
Conclusions
Dissemination of infertility guidelines by commonly used methods results in a modest increase in referrals having recommended investigations completed in general practice, but there are no detectable differences in outcome for patients or reduction in costs. Clinicians in secondary care tended to fail to respond to changes in referral practice by doctors. Guidelines that aim to improve the referral process need to be disseminated and implemented so as to lead to changes in both primary care and secondary care.
What is already known on this topicMost previous research into clinical guidelines has focused on their development and implementationEvidence is lacking about the outcomes and costs associated with the use of clinical guidelinesWhat this study addsClinical guidelines that may alter the balance of care between general practice and hospital settings require more intensive implementation than guidelines aimed at either setting on its ownThe cost effectiveness of clinical guidelines should not be assumed
PMCID: PMC31924  PMID: 11375232
21.  Methodological reflections on the evaluation of the implementation and adoption of national electronic health record systems 
Introduction/purpose of presentation
Far-reaching policy commitments to information technology-centered transformations of healthcare systems have now been made in many countries. There is as yet little empirical evidence to justify such decisions, hence the need for rigorous independent evaluation of current implementation efforts. Such evaluations however pose a number of important challenges. This presentation has been designed as a part of a Panel based on our experience of evaluating the National Health Service’s (NHS) implementation of electronic health records (EHR) systems in hospitals throughout England. We discuss the methodological challenges encountered in planning and undertaking an evaluation of a program of this scale and reflect on why and how we adapted our evaluation approach—both conceptually and methodologically—in response to these challenges.
Study design/population studied
Critical reflections on a multi-disciplinary and multi-facet independent evaluation of a national program to implement electronic health record systems into 12 ‘early wave’ NHS hospitals in England.
Findings
Our initial plan was to employ a mixed methods longitudinal ‘before-during-after’ study design. We however found this unsustainable in the light of fluxes in policy, contractual issues and over-optimistic schedules for EHR deployments. More importantly, this research design failed adequately to address the core of multi-faceted evolving EHRs as understood by key stakeholders and as worked out in their distinct work settings. Thus conventional outcomes-centric evaluations may not easily scale-up when evaluating transformational programs and may indeed prove misleading. New assumptions concerning the implementation process of EHR need to be developed that recognize the constantly changing milieu of policy, product, projects and professions that are inherent to such national implementations. The approaches we subsequently developed substitute the positivist view that EHR initiatives are self-evident and self-contained interventions, which are amenable to traditional quantitative evaluations, to one that focuses on how they are understood by various stakeholders and made to work in specific contexts. These assumptions recast the role of evaluation towards an approach that explores and interprets processes of socio-technical change that surround EHR implementation and adoption as seen by multiple stakeholders.
Conclusions and policy implications
There is likely to be an increase in politically-driven national programs of reform of healthcare based on information and communication technologies. Programs on such a scale are inherently complex with extended temporalities and extensive and dynamic sets of stakeholders. They are, in short, different and pose new evaluation challenges that previously formulated evaluation methods for health information systems cannot easily address. This calls for methodological innovation amongst research teams and their supporting bodies. We argue that evaluation of such system-wide transformation programs are likely to demand both breadth and depth of experience within a multidisciplinary research team, constant questioning of what is and what can be evaluated and how, and a particular way of working that emphasizes continuous dialogue and reflexivity. Making this transition is essential to enable evaluations that can usefully inform policy-making. Health policy experts urgently need to reassess the evaluation strategies they employ as they come to address national policies for system-wide transformation based on new electronic health infrastructures.
PMCID: PMC3571157
electronic health record; evaluation; methodology; socio-technical changing
22.  SMART Platforms: Building the App Store for Biosurveillance 
Objective
To enable public health departments to develop “apps” to run on electronic health records (EHRs) for (1) biosurveillance and case reporting and (2) delivering alerts to the point of care. We describe a novel health information technology platform with substitutable apps constructed around core services enabling EHRs to function as iPhone-like platforms.
Introduction
Health care information is a fundamental source of data for biosurveillance, yet configuring EHRs to report relevant data to health departments is technically challenging, labor intensive, and often requires custom solutions for each installation. Public health agencies wishing to deliver alerts to clinicians also must engage in an endless array of one-off systems integrations.
Despite a $48B investment in HIT, and meaningful use criteria requiring reporting to biosurveillance systems, most vendor electronic health records are architected monolithically, making modification difficult for hospitals and physician practices. An alternative approach is to reimagine EHRs as iPhone-like platforms supporting substitutable apps-based functionality. Substitutability is the capability inherent in a system of replacing one application with another of similar functionality.
Methods
Substitutability requires that the purchaser of an app can replace one application with another without being technically expert, without requiring re-engineering other applications that they are using, and without having to consult or require assistance of any of the vendors of previously installed or currently installed applications. Apps necessarily compete with each other promoting progress and adaptability.
The Substitutable Medical Applications, Reusable Technologies (SMART) Platforms project is funded by a $15M grant from Office of the National Coordinator of Health Information Technology’s Strategic Health IT Advanced Research Projects (SHARP) Program. All SMART standards are open and the core software is open source.
The SMART project promotes substitutability through an application programming interface (API) that can be adopted as part of a “container” built around by a wide variety of HIT, providing readonly access to the underlying data model and a software development toolkit to readily create apps. SMART containers are HIT systems, that have implemented the SMART API or a portion of it. Containers marshal data sources and present them consistently across the SMART API. SMART applications consume the API and are substitutable.
Results
SMART provides a common platform supporting an “app store for biosurveillance” as an approach to enabling one stop shopping for public health departments—to create an app once, and distribute it everywhere.
Further, such apps can be readily updated or created—for example, in the case of an emerging infection, an app may be designed to collect additional data at emergency department triage. Or a public health department may widely distribute an app, interoperable with any SMART-enabled EMR, that delivers contextualized alerts when patient electronic records are opened, or through background processes.
SMART has sparked an ecosystem of apps developers and attracted existing health information technology platforms to adopt the SMART API—including, traditional, open source, and next generation EHRs, patient-facing platforms and health information exchanges. SMART-enabled platforms to date include the Cerner EMR, the WorldVista EHR, the OpenMRS EHR, the i2b2 analytic platform, and the Indivo X personal health record. The SMART team is working with the Mirth Corporation, to SMART-enable the HealthBridge and Redwood MedNet Health Information Exchanges. We have demonstrated that a single SMART app can run, unmodified, in all of these environments, as long as the underlying platform collects the required data types. Major EHR vendors are currently adapting the SMART API for their products.
Conclusions
The SMART system enables nimble customization of any electronic health record system to create either a reporting function (outgoing communication) or an alerting function (incoming communication) establishing a technology for a robust linkage between public health and clinical environments.
PMCID: PMC3692876
Electronic health records; Biosurveillance; Informatics; Application Programming Interfaces
23.  Evaluating Electronic Referrals for Specialty Care at a Public Hospital 
Journal of General Internal Medicine  2010;25(10):1123-1128.
BACKGROUND
Poor communication between referring clinicians and specialists may lead to inefficient use of specialist services. San Francisco General Hospital implemented an electronic referral system (eReferral) that facilitates iterative pre-visit communication between referring and specialty clinicians to improve the referral process.
OBJECTIVE
The purpose of the study was to determine the impact of eReferral (compared with paper-based referrals) on specialty referrals.
DESIGN
The study was based on a visit-based questionnaire appended to new patient charts at randomly selected specialist clinic sessions before and after the implementation of eReferral.
PARTICIPANTS
Specialty clinicians.
MAIN MEASURES
The questionnaire focused on the self-reported difficulty in identifying referral question, referral appropriateness, need for and avoidability of follow-up visits.
KEY RESULTS
We collected 505 questionnaires from speciality clinicians. It was difficult to identify the reason for referral in 19.8% of medical and 38.0% of surgical visits using paper-based methods vs. 11.0% and 9.5% of those using eReferral (p-value 0.03 and <0.001). Of those using eReferral, 6.4% and 9.8% of medical and surgical referrals using paper methods vs. 2.6% and 2.1% were deemed not completely appropriate (p-value 0.21 and 0.03). Follow-up was requested for 82.4% and 76.2% of medical and surgical patients with paper-based referrals vs. 90.1% and 58.1% of eReferrals (p-value 0.06 and 0.01). Follow-up was considered avoidable for 32.4% and 44.7% of medical and surgical follow-ups with paper-based methods vs. 27.5% and 13.5% with eReferral (0.41 and <0.001).
CONCLUSION
Use of technology to promote standardized referral processes and iterative communication between referring clinicians and specialists has the potential to improve communication between primary care providers and specialists and to increase the effectiveness of specialty referrals.
doi:10.1007/s11606-010-1402-1
PMCID: PMC2955477  PMID: 20512531
access to care; communication; specialty care
24.  Systems architecture for integrated care 
Introduction
Telehealth and telecare projects do not always pay enough attention to the wider information systems architecture required to deliver integrated care. They often focus on technologies to support specific diseases or social care problems which can result in information silos that impede integrated care of the patient. While these technologies can deliver discrete benefits, they could potentially generate unintended disbenefits in terms of creating data silos which may cause patient harm or at least impede the ability of the clinician, carer or even patient to treat the patient in an integrated fashion. For instance, if clinical data (vital signs, assessments, medications, allergies) are captured in a telehealth or telecare system, but not integrated with the patient record in the GP or hospital system (or vice versa), then drug or treatment contra-indications could be missed and the patient put at risk.
Architectures
Telehealth and telecare technologies need to be designed and developed within information systems architectures that support the wider objectives of integrated care. Such architectures should be clear about the integration trade-offs implicit in the technology designs between: practical and earlier delivery of benefits in the short-term versus the ability of the care team in the longer-term to treat the whole patient in a patient-centred and fully integrated manner.
Kaiser
There are several types of integrated information systems architectures. One of these is the one deployed by Kaiser Permanente in the US. Kaiser’s information systems architecture contains the following elements: (a) a fully integrated electronic patient record at its core; (b) operation across care settings; (c) patients’ electronic access to their doctor and health record; (d) population care with whole patient chronic care management (for diabetes, COPD, congestive heart failure, asthma, etc.) with a consolidated disease register; (e) development and real-time deployment of embedded clinical protocols; (f) secure access by remote health facilities; (g) centralised technical standards and architecture alongside local developments (“think globally, act locally”); and (i) analytic tools for high volume, complex data.
Integration
Integration architectures range from full functional integration to data interoperability. In full functional integration architectures, the electronic patient record is at the core. This patient record is the detailed (not summary) record and reflects a complex information system supporting the entire clinical process including: review of clinical data (results, images, documents), assessments, documentation and correspondence, requesting tests, prescribing and administering drugs, clinical decision support with real-time alerts, multi-resource scheduling, care plans and integrated care pathways, research and patient access to his/her record.
The fully integrated healthcare systems architecture applies to, and operates across, patients, clinicians, clinical teams, carers, social workers, GPs, community units and hospitals within the geographical community in which the patient lives and receives care.
Conclusion
The recommended actions for UK telehealth and telecare projects are (a) define your systems architecture and its integration road map; (b) deploy road map and revise systems architecture; and (c) repeat to continuously improve information systems support for integrated care.
PMCID: PMC3571169
telehealth; telecare; systems architecture; integrated health care
25.  Relationship style between GPs and community mental health teams affects referral rates. 
BACKGROUND: Community mental health teams (CMHTs) are the established model for supporting patients with serious mental illness in the community. However, up to 25% of those with psychotic disorders are managed solely by primary care teams. Effective management depends upon locally negotiated referral and shared care arrangements between CMHTs and primary care. AIM: To examine whether the style of working relationship between general practices and CMHTs affects the numbers and types of referrals from general practices to CMHTs, taking into account population and practice factors and provision of other mental health services which may influence referral rates. DESIGN OF STUDY: Cross-sectional study. SETTING: All 161 general practices in East London and the City Health Authority. METHOD: Questionnaire survey to all general practices to identify style of relationship. Collection of routinely available referral data to all statutory mental health services over a two-year period. Main outcome measures were number and types of referrals from general practices to CMHTs. RESULTS: The average annual referral rate to the eleven CMHTs in east London is 10 per 1000 adult population annually. The teams show a sixfold variation in rates of referral from all sources. Where good working relationships (a consultation-liaison style) exist between CMHTs and general practice, there are greater numbers of referrals requiring both long and short-term work by CMHTs. Two-stage multivariate models explained 47% of the referral variation between practices. Where primary care-based psychologists work with practices there are greater numbers of CMHT referrals, but less use of psychiatric services. CONCLUSION: Shifting to a consultation-liaison relationship should increase rates of referral of patients with serious mental illness, including those who can most benefit from the skills of CMHTs. Increasing the provision of primary care-based psychology might improve practice use of mental health services, reducing avoidable outpatient psychiatric referrals.
PMCID: PMC1314216  PMID: 11885819

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