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1.  Maternal Clinical Diagnoses and Hospital Variation in the Risk of Cesarean Delivery: Analyses of a National US Hospital Discharge Database 
PLoS Medicine  2014;11(10):e1001745.
Katy Kozhimannil and colleagues use a national database to examine the extent to which variability in cesarean section rates across the US from 2009–2010 was attributable to individual women's clinical diagnoses.
Please see later in the article for the Editors' Summary
Cesarean delivery is the most common inpatient surgery in the United States, where 1.3 million cesarean sections occur annually, and rates vary widely by hospital. Identifying sources of variation in cesarean use is crucial to improving the consistency and quality of obstetric care. We used hospital discharge records to examine the extent to which variability in the likelihood of cesarean section across US hospitals was attributable to individual women's clinical diagnoses.
Methods and Findings
Using data from the 2009 and 2010 Nationwide Inpatient Sample from the Healthcare Cost and Utilization Project—a 20% sample of US hospitals—we analyzed data for 1,475,457 births in 1,373 hospitals. We fitted multilevel logistic regression models (patients nested in hospitals). The outcome was cesarean (versus vaginal) delivery. Covariates included diagnosis of diabetes in pregnancy, hypertension in pregnancy, hemorrhage during pregnancy or placental complications, fetal distress, and fetal disproportion or obstructed labor; maternal age, race/ethnicity, and insurance status; and hospital size and location/teaching status.
The cesarean section prevalence was 22.0% (95% confidence interval 22.0% to 22.1%) among women with no prior cesareans. In unadjusted models, the between-hospital variation in the individual risk of primary cesarean section was 0.14 (95% credible interval 0.12 to 0.15). The difference in the probability of having a cesarean delivery between hospitals was 25 percentage points. Hospital variability did not decrease after adjusting for patient diagnoses, socio-demographics, and hospital characteristics (0.16 [95% credible interval 0.14 to 0.18]). A limitation is that these data, while nationally representative, did not contain information on parity or gestational age.
Variability across hospitals in the individual risk of cesarean section is not decreased by accounting for differences in maternal diagnoses. These findings highlight the need for more comprehensive or linked data including parity and gestational age as well as examination of other factors—such as hospital policies, practices, and culture—in determining cesarean section use.
Please see later in the article for the Editors' Summary
Editors' Summary
In an ideal world, all babies would be delivered safely and naturally through their mother's vagina. However, increasing numbers of babies are being delivered by cesarean section, a surgical operation in which the baby is delivered through a cut made in the mother's abdomen and womb. In the US, a third of all babies (about 1.3 million babies in 2011) are delivered this way. A cesarean section is usually performed when a vaginal birth would endanger the life of the mother or her unborn child because, for example, the baby is in the wrong position or the labor is not progressing normally. Some cesarean sections are performed as emergency procedures, but others are planned in advance when the need for the operation becomes clear during pregnancy. Although cesarean sections can save lives, women who deliver this way have higher rates of infection, pain, and complications in future pregnancies than women who deliver vaginally, and their babies can have breathing problems.
Why Was This Study Done?
Currently, cesarean section rates vary widely from country to country and from hospital to hospital within countries. Careful assessment of the risks and benefits of cesarean delivery in individual patients can help to ensure that cesarean sections are used only when necessary, but changes to clinical and policy guidelines are also needed to ensure that cesarean delivery is neither overused nor underused. To guide these changes, we need to know whether cesarean section rates vary among hospitals because of case-mix differences (some hospitals may have high rates because they admit many women with complicated pregnancies, for example) or because of differences in modifiable nonclinical factors such as hospital policies and practices. In this retrospective multilevel analysis, the researchers examine whether the current wide variation in cesarean section rates across US hospitals is attributable to differences in maternal clinical diagnoses and patient characteristics or to hospital-level differences in the use of cesarean delivery.
What Did the Researchers Do and Find?
For their study, the researchers used hospital discharge data on nearly 1.5 million births in 1,373 hospitals collected by the 2009 and 2010 US Nationwide Inpatient Sample database, which captures administrative data (for example, length of stay in hospital and clinical complications) from a representative sample of 20% of US hospitals. To assess the chances of cesarean delivery based on hospital and patient characteristics, researchers fitted these data to multilevel logistic regression statistical models. Among women with no prior cesarean deliveries, the (primary) cesarean section rate was 22%, whereas among the whole study population, it was 33% (women who have one cesarean delivery often have a cesarean section for subsequent deliveries). In unadjusted models that compared cesarean section rates between hospitals without considering patient characteristics, the between-hospital variance for primary cesarean section rate was 0.14. Put another way, the likelihood of an individual having a first cesarean delivery varied between 11% and 36% across the hospitals considered. After adjustment for maternal clinical diagnoses, maternal age and other socio-demographic factors, and hospital characteristics such as size, the between-hospital variance for the primary cesarean section rate was 0.16.
What Do These Findings Mean?
The finding that the between-hospital variance for primary cesarean section rate did not decrease after adjusting for maternal characteristics (and other findings presented by the researchers) suggests that differences in case mix or pregnancy complexity may not drive the wide variability in cesarean section rates across US hospitals. However, the lack of information in the US Nationwide Inpatient Sample database on parity (the number of babies a woman has had) or gestational age (the length of time the baby has spent developing inside its mother) limits the strength of this conclusion. Both parity and gestational age strongly predict a woman's risk of a cesarean delivery. Thus, unmeasured differences in the parity of women admitted to different hospitals and/or the gestational age of their babies may be driving some of the variability in cesarean section rates across US hospitals. The lack of hospital-level information on obstetric care policies in the database also means that the many possible administrative explanations for variations across hospitals cannot be assessed. These findings therefore highlight the need for more comprehensive patient data to be collected (including information on parity and gestational age) and on hospital policies, practices, and culture before the variation in cesarean section rate across US hospitals can be fully understood and the use of cesarean delivery can be optimized.
Additional Information
Please access these websites via the online version of this summary at
This study is further discussed in a PLOS Medicine Perspective by Gordon C. S. Smith
The American College of Obstetricians and Gynecologists provides a fact sheet for patients on cesarean birth
The American College of Nurse-Midwives provides a fact sheet for pregnant women on preventing cesarean birth
The US-based Childbirth Connection Project of the non-profit National Partnership for Women and Families has a booklet called “What Every Woman Should Know about Cesarean Section”
The US-based non-profit Nemours Foundation provides detailed information about cesarean sections (in English and Spanish)
The UK National Health Service Choices website provides information for patients about delivery by cesarean section
MedlinePlus provides links to additional resources about cesarean section (in English and Spanish)
The UK non-profit organization Healthtalkonline provides personal stories about women's experiences of cesarean delivery
Information about the US Nationwide Inpatient Sample database is available
PMCID: PMC4205118  PMID: 25333943
2.  Implementing the 2009 Institute of Medicine recommendations on resident physician work hours, supervision, and safety 
Long working hours and sleep deprivation have been a facet of physician training in the US since the advent of the modern residency system. However, the scientific evidence linking fatigue with deficits in human performance, accidents and errors in industries from aeronautics to medicine, nuclear power, and transportation has mounted over the last 40 years. This evidence has also spawned regulations to help ensure public safety across safety-sensitive industries, with the notable exception of medicine.
In late 2007, at the behest of the US Congress, the Institute of Medicine embarked on a year-long examination of the scientific evidence linking resident physician sleep deprivation with clinical performance deficits and medical errors. The Institute of Medicine’s report, entitled “Resident duty hours: Enhancing sleep, supervision and safety”, published in January 2009, recommended new limits on resident physician work hours and workload, increased supervision, a heightened focus on resident physician safety, training in structured handovers and quality improvement, more rigorous external oversight of work hours and other aspects of residency training, and the identification of expanded funding sources necessary to implement the recommended reforms successfully and protect the public and resident physicians themselves from preventable harm.
Given that resident physicians comprise almost a quarter of all physicians who work in hospitals, and that taxpayers, through Medicare and Medicaid, fund graduate medical education, the public has a deep investment in physician training. Patients expect to receive safe, high-quality care in the nation’s teaching hospitals. Because it is their safety that is at issue, their voices should be central in policy decisions affecting patient safety. It is likewise important to integrate the perspectives of resident physicians, policy makers, and other constituencies in designing new policies. However, since its release, discussion of the Institute of Medicine report has been largely confined to the medical education community, led by the Accreditation Council for Graduate Medical Education (ACGME).
To begin gathering these perspectives and developing a plan to implement safer work hours for resident physicians, a conference entitled “Enhancing sleep, supervision and safety: What will it take to implement the Institute of Medicine recommendations?” was held at Harvard Medical School on June 17–18, 2010. This White Paper is a product of a diverse group of 26 representative stakeholders bringing relevant new information and innovative practices to bear on a critical patient safety problem. Given that our conference included experts from across disciplines with diverse perspectives and interests, not every recommendation was endorsed by each invited conference participant. However, every recommendation made here was endorsed by the majority of the group, and many were endorsed unanimously. Conference members participated in the process, reviewed the final product, and provided input before publication. Participants provided their individual perspectives, which do not necessarily represent the formal views of any organization.
In September 2010 the ACGME issued new rules to go into effect on July 1, 2011. Unfortunately, they stop considerably short of the Institute of Medicine’s recommendations and those endorsed by this conference. In particular, the ACGME only applied the limitation of 16 hours to first-year resident physicans. Thus, it is clear that policymakers, hospital administrators, and residency program directors who wish to implement safer health care systems must go far beyond what the ACGME will require. We hope this White Paper will serve as a guide and provide encouragement for that effort.
Resident physician workload and supervision
By the end of training, a resident physician should be able to practice independently. Yet much of resident physicians’ time is dominated by tasks with little educational value. The caseload can be so great that inadequate reflective time is left for learning based on clinical experiences. In addition, supervision is often vaguely defined and discontinuous. Medical malpractice data indicate that resident physicians are frequently named in lawsuits, most often for lack of supervision. The recommendations are: The ACGME should adjust resident physicians workload requirements to optimize educational value. Resident physicians as well as faculty should be involved in work redesign that eliminates nonessential and noneducational activity from resident physician dutiesMechanisms should be developed for identifying in real time when a resident physician’s workload is excessive, and processes developed to activate additional providersTeamwork should be actively encouraged in delivery of patient care. Historically, much of medical training has focused on individual knowledge, skills, and responsibility. As health care delivery has become more complex, it will be essential to train resident and attending physicians in effective teamwork that emphasizes collective responsibility for patient care and recognizes the signs, both individual and systemic, of a schedule and working conditions that are too demanding to be safeHospitals should embrace the opportunities that resident physician training redesign offers. Hospitals should recognize and act on the potential benefits of work redesign, eg, increased efficiency, reduced costs, improved quality of care, and resident physician and attending job satisfactionAttending physicians should supervise all hospital admissions. Resident physicians should directly discuss all admissions with attending physicians. Attending physicians should be both cognizant of and have input into the care patients are to receive upon admission to the hospitalInhouse supervision should be required for all critical care services, including emergency rooms, intensive care units, and trauma services. Resident physicians should not be left unsupervised to care for critically ill patients. In settings in which the acuity is high, physicians who have completed residency should provide direct supervision for resident physicians. Supervising physicians should always be physically in the hospital for supervision of resident physicians who care for critically ill patientsThe ACGME should explicitly define “good” supervision by specialty and by year of training. Explicit requirements for intensity and level of training for supervision of specific clinical scenarios should be providedCenters for Medicare and Medicaid Services (CMS) should use graduate medical education funding to provide incentives to programs with proven, effective levels of supervision. Although this action would require federal legislation, reimbursement rules would help to ensure that hospitals pay attention to the importance of good supervision and require it from their training programs
Resident physician work hours
Although the IOM “Sleep, supervision and safety” report provides a comprehensive review and discussion of all aspects of graduate medical education training, the report’s focal point is its recommendations regarding the hours that resident physicians are currently required to work. A considerable body of scientific evidence, much of it cited by the Institute of Medicine report, describes deteriorating performance in fatigued humans, as well as specific studies on resident physician fatigue and preventable medical errors.
The question before this conference was what work redesign and cultural changes are needed to reform work hours as recommended by the Institute of Medicine’s evidence-based report? Extensive scientific data demonstrate that shifts exceeding 12–16 hours without sleep are unsafe. Several principles should be followed in efforts to reduce consecutive hours below this level and achieve safer work schedules. The recommendations are: Limit resident physician work hours to 12–16 hour maximum shiftsA minimum of 10 hours off duty should be scheduled between shiftsResident physician input into work redesign should be actively solicitedSchedules should be designed that adhere to principles of sleep and circadian science; this includes careful consideration of the effects of multiple consecutive night shifts, and provision of adequate time off after night work, as specified in the IOM reportResident physicians should not be scheduled up to the maximum permissible limits; emergencies frequently occur that require resident physicians to stay longer than their scheduled shifts, and this should be anticipated in scheduling resident physicians’ work shiftsHospitals should anticipate the need for iterative improvement as new schedules are initiated; be prepared to learn from the initial phase-in, and change the plan as neededAs resident physician work hours are redesigned, attending physicians should also be considered; a potential consequence of resident physician work hour reduction and increased supervisory requirements may be an increase in work for attending physicians; this should be carefully monitored, and adjustments to attending physician work schedules made as needed to prevent unsafe work hours or working conditions for this group“Home call” should be brought under the overall limits of working hours; work load and hours should be monitored in each residency program to ensure that resident physicians and fellows on home call are getting sufficient sleepMedicare funding for graduate medical education in each hospital should be linked with adherence to the Institute of Medicine limits on resident physician work hours
Moonlighting by resident physicians
The Institute of Medicine report recommended including external as well as internal moonlighting in working hour limits. The recommendation is: All moonlighting work hours should be included in the ACGME working hour limits and actively monitored. Hospitals should formalize a moonlighting policy and establish systems for actively monitoring resident physician moonlighting
Safety of resident physicians
The “Sleep, supervision and safety” report also addresses fatigue-related harm done to resident physicians themselves. The report focuses on two main sources of physical injury to resident physicians impaired by fatigue, ie, needle-stick exposure to blood-borne pathogens and motor vehicle crashes. Providing safe transportation home for resident physicians is a logistical and financial challenge for hospitals. Educating physicians at all levels on the dangers of fatigue is clearly required to change driving behavior so that safe hospital-funded transport home is used effectively. Fatigue-related injury prevention (including not driving while drowsy) should be taught in medical school and during residency, and reinforced with attending physicians; hospitals and residency programs must be informed that resident physicians’ ability to judge their own level of impairment is impaired when they are sleep deprived; hence, leaving decisions about the capacity to drive to impaired resident physicians is not recommendedHospitals should provide transportation to all resident physicians who report feeling too tired to drive safely; in addition, although consecutive work should not exceed 16 hours, hospitals should provide transportation for all resident physicians who, because of unforeseen reasons or emergencies, work for longer than consecutive 24 hours; transportation under these circumstances should be automatically provided to house staff, and should not rely on self-identification or request
Training in effective handovers and quality improvement
Handover practice for resident physicians, attendings, and other health care providers has long been identified as a weak link in patient safety throughout health care settings. Policies to improve handovers of care must be tailored to fit the appropriate clinical scenario, recognizing that information overload can also be a problem. At the heart of improving handovers is the organizational effort to improve quality, an effort in which resident physicians have typically been insufficiently engaged. The recommendations are: Hospitals should train attending and resident physicians in effective handovers of careHospitals should create uniform processes for handovers that are tailored to meet each clinical setting; all handovers should be done verbally and face-to-face, but should also utilize written toolsWhen possible, hospitals should integrate hand-over tools into their electronic medical records (EMR) systems; these systems should be standardized to the extent possible across residency programs in a hospital, but may be tailored to the needs of specific programs and services; federal government should help subsidize adoption of electronic medical records by hospitals to improve signoutWhen feasible, handovers should be a team effort including nurses, patients, and familiesHospitals should include residents in their quality improvement and patient safety efforts; the ACGME should specify in their core competency requirements that resident physicians work on quality improvement projects; likewise, the Joint Commission should require that resident physicians be included in quality improvement and patient safety programs at teaching hospitals; hospital administrators and residency program directors should create opportunities for resident physicians to become involved in ongoing quality improvement projects and root cause analysis teams; feedback on successful quality improvement interventions should be shared with resident physicians and broadly disseminatedQuality improvement/patient safety concepts should be integral to the medical school curriculum; medical school deans should elevate the topics of patient safety, quality improvement, and teamwork; these concepts should be integrated throughout the medical school curriculum and reinforced throughout residency; mastery of these concepts by medical students should be tested on the United States Medical Licensing Examination (USMLE) stepsFederal government should support involvement of resident physicians in quality improvement efforts; initiatives to improve quality by including resident physicians in quality improvement projects should be financially supported by the Department of Health and Human Services
Monitoring and oversight of the ACGME
While the ACGME is a key stakeholder in residency training, external voices are essential to ensure that public interests are heard in the development and monitoring of standards. Consequently, the Institute of Medicine report recommended external oversight and monitoring through the Joint Commission and Centers for Medicare and Medicaid Services (CMS). The recommendations are: Make comprehensive fatigue management a Joint Commission National Patient Safety Goal; fatigue is a safety concern not only for resident physicians, but also for nurses, attending physicians, and other health care workers; the Joint Commission should seek to ensure that all health care workers, not just resident physicians, are working as safely as possibleFederal government, including the Centers for Medicare and Medicaid Services and the Agency for Healthcare Research and Quality, should encourage development of comprehensive fatigue management programs which all health systems would eventually be required to implementMake ACGME compliance with working hours a “ condition of participation” for reimbursement of direct and indirect graduate medical education costs; financial incentives will greatly increase the adoption of and compliance with ACGME standards
Future financial support for implementation
The Institute of Medicine’s report estimates that $1.7 billion (in 2008 dollars) would be needed to implement its recommendations. Twenty-five percent of that amount ($376 million) will be required just to bring hospitals into compliance with the existing 2003 ACGME rules. Downstream savings to the health care system could potentially result from safer care, but these benefits typically do not accrue to hospitals and residency programs, who have been asked historically to bear the burden of residency reform costs. The recommendations are: The Institute of Medicine should convene a panel of stakeholders, including private and public funders of health care and graduate medical education, to lay down the concrete steps necessary to identify and allocate the resources needed to implement the recommendations contained in the IOM “Resident duty hours: Enhancing sleep, supervision and safety” report. Conference participants suggested several approaches to engage public and private support for this initiativeEfforts to find additional funding to implement the Institute of Medicine recommendations should focus more broadly on patient safety and health care delivery reform; policy efforts focused narrowly upon resident physician work hours are less likely to succeed than broad patient safety initiatives that include residency redesign as a key componentHospitals should view the Institute of Medicine recommendations as an opportunity to begin resident physician work redesign projects as the core of a business model that embraces safety and ultimately saves resourcesBoth the Secretary of Health and Human Services and the Director of the Centers for Medicare and Medicaid Services should take the Institute of Medicine recommendations into consideration when promulgating rules for innovation grantsThe National Health Care Workforce Commission should consider the Institute of Medicine recommendations when analyzing the nation’s physician workforce needs
Recommendations for future research
Conference participants concurred that convening the stakeholders and agreeing on a research agenda was key. Some observed that some sectors within the medical education community have been reluctant to act on the data. Several logical funders for future research were identified. But above all agencies, Centers for Medicare and Medicaid Services is the only stakeholder that funds graduate medical education upstream and will reap savings downstream if preventable medical errors are reduced as a result of reform of resident physician work hours.
PMCID: PMC3630963  PMID: 23616719
resident; hospital; working hours; safety
3.  Does managed care make a difference? Physicians' length of stay decisions under managed and non-managed care 
In this study we examined the influence of type of insurance and the influence of managed care in particular, on the length of stay decisions physicians make and on variation in medical practice.
We studied lengths of stay for comparable patients who are insured under managed or non-managed care plans. Seven Diagnosis Related Groups were chosen, two medical (COPD and CHF), one surgical (hip replacement) and four obstetrical (hysterectomy with and without complications and Cesarean section with and without complications). The 1999, 2000 and 2001 – data from hospitals in New York State were used and analyzed with multilevel analysis.
Average length of stay does not differ between managed and non-managed care patients. Less variation was found for managed care patients. In both groups, the variation was smaller for DRGs that are easy to standardize than for other DRGs.
Type of insurance does not affect length of stay. An explanation might be that hospitals have a general policy concerning length of stay, independent of the type of insurance of the patient.
PMCID: PMC368442  PMID: 15028122
4.  Hospital-at-Home Programs for Patients With Acute Exacerbations of Chronic Obstructive Pulmonary Disease (COPD) 
Executive Summary
In July 2010, the Medical Advisory Secretariat (MAS) began work on a Chronic Obstructive Pulmonary Disease (COPD) evidentiary framework, an evidence-based review of the literature surrounding treatment strategies for patients with COPD. This project emerged from a request by the Health System Strategy Division of the Ministry of Health and Long-Term Care that MAS provide them with an evidentiary platform on the effectiveness and cost-effectiveness of COPD interventions.
After an initial review of health technology assessments and systematic reviews of COPD literature, and consultation with experts, MAS identified the following topics for analysis: vaccinations (influenza and pneumococcal), smoking cessation, multidisciplinary care, pulmonary rehabilitation, long-term oxygen therapy, noninvasive positive pressure ventilation for acute and chronic respiratory failure, hospital-at-home for acute exacerbations of COPD, and telehealth (including telemonitoring and telephone support). Evidence-based analyses were prepared for each of these topics. For each technology, an economic analysis was also completed where appropriate. In addition, a review of the qualitative literature on patient, caregiver, and provider perspectives on living and dying with COPD was conducted, as were reviews of the qualitative literature on each of the technologies included in these analyses.
The Chronic Obstructive Pulmonary Disease Mega-Analysis series is made up of the following reports, which can be publicly accessed at the MAS website at:
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:
For more information on the economic analysis, please visit the PATH website:
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:
The objective of this analysis was to compare hospital-at-home care with inpatient hospital care for patients with acute exacerbations of chronic obstructive pulmonary disease (COPD) who present to the emergency department (ED).
Clinical Need: Condition and Target Population
Acute Exacerbations of Chronic Obstructive Pulmonary Disease
Chronic obstructive pulmonary disease is a disease state characterized by airflow limitation that is not fully reversible. This airflow limitation is usually both progressive and associated with an abnormal inflammatory response of the lungs to noxious particles or gases. The natural history of COPD involves periods of acute-onset worsening of symptoms, particularly increased breathlessness, cough, and/or sputum, that go beyond normal day-to-day variations; these are known as acute exacerbations.
Two-thirds of COPD exacerbations are caused by an infection of the tracheobronchial tree or by air pollution; the cause in the remaining cases is unknown. On average, patients with moderate to severe COPD experience 2 or 3 exacerbations each year.
Exacerbations have an important impact on patients and on the health care system. For the patient, exacerbations result in decreased quality of life, potentially permanent losses of lung function, and an increased risk of mortality. For the health care system, exacerbations of COPD are a leading cause of ED visits and hospitalizations, particularly in winter.
Hospital-at-home programs offer an alternative for patients who present to the ED with an exacerbation of COPD and require hospital admission for their treatment. Hospital-at-home programs provide patients with visits in their home by medical professionals (typically specialist nurses) who monitor the patients, alter patients’ treatment plans if needed, and in some programs, provide additional care such as pulmonary rehabilitation, patient and caregiver education, and smoking cessation counselling.
There are 2 types of hospital-at-home programs: admission avoidance and early discharge hospital-at-home. In the former, admission avoidance hospital-at-home, after patients are assessed in the ED, they are prescribed the necessary medications and additional care needed (e.g., oxygen therapy) and then sent home where they receive regular visits from a medical professional. In early discharge hospital-at-home, after being assessed in the ED, patients are admitted to the hospital where they receive the initial phase of their treatment. These patients are discharged into a hospital-at-home program before the exacerbation has resolved. In both cases, once the exacerbation has resolved, the patient is discharged from the hospital-at-home program and no longer receives visits in his/her home.
In the models that exist to date, hospital-at-home programs differ from other home care programs because they deal with higher acuity patients who require higher acuity care, and because hospitals retain the medical and legal responsibility for patients. Furthermore, patients requiring home care services may require such services for long periods of time or indefinitely, whereas patients in hospital-at-home programs require and receive the services for a short period of time only.
Hospital-at-home care is not appropriate for all patients with acute exacerbations of COPD. Ineligible patients include: those with mild exacerbations that can be managed without admission to hospital; those who require admission to hospital; and those who cannot be safely treated in a hospital-at-home program either for medical reasons and/or because of a lack of, or poor, social support at home.
The proposed possible benefits of hospital-at-home for treatment of exacerbations of COPD include: decreased utilization of health care resources by avoiding hospital admission and/or reducing length of stay in hospital; decreased costs; increased health-related quality of life for patients and caregivers when treated at home; and reduced risk of hospital-acquired infections in this susceptible patient population.
Ontario Context
No hospital-at-home programs for the treatment of acute exacerbations of COPD were identified in Ontario. Patients requiring acute care for their exacerbations are treated in hospitals.
Research Question
What is the effectiveness, cost-effectiveness, and safety of hospital-at-home care compared with inpatient hospital care of acute exacerbations of COPD?
Research Methods
Literature Search
Search Strategy
A literature search was performed on August 5, 2010, using OVID MEDLINE, OVID MEDLINE In-Process and Other Non-Indexed Citations, OVID EMBASE, EBSCO Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Wiley Cochrane Library, and the Centre for Reviews and Dissemination database for studies published from January 1, 1990, to August 5, 2010. Abstracts were reviewed by a single reviewer and, for those studies meeting the eligibility criteria, full-text articles were obtained. Reference lists and health technology assessment websites were also examined for any additional relevant studies not identified through the systematic search.
Inclusion Criteria
English language full-text reports;
health technology assessments, systematic reviews, meta-analyses, and randomized controlled trials (RCTs);
studies performed exclusively in patients with a diagnosis of COPD or studies including patients with COPD as well as patients with other conditions, if results are reported for COPD patients separately;
studies performed in patients with acute exacerbations of COPD who present to the ED;
studies published between January 1, 1990, and August 5, 2010;
studies comparing hospital-at-home and inpatient hospital care for patients with acute exacerbations of COPD;
studies that include at least 1 of the outcomes of interest (listed below).
Cochrane Collaboration reviews have defined hospital-at-home programs as those that provide patients with active treatment for their acute exacerbation in their home by medical professionals for a limited period of time (in this case, until the resolution of the exacerbation). If a hospital-at-home program had not been available, these patients would have been admitted to hospital for their treatment.
Exclusion Criteria
< 18 years of age
animal studies
duplicate publications
grey literature
Outcomes of Interest
Patient/clinical outcomes
lung function (forced expiratory volume in 1 second)
health-related quality of life
patient or caregiver preference
patient or caregiver satisfaction with care
Health system outcomes
hospital readmissions
length of stay in hospital and hospital-at-home
ED visits
transfer to long-term care
days to readmission
eligibility for hospital-at-home
Statistical Methods
When possible, results were pooled using Review Manager 5 Version 5.1; otherwise, results were summarized descriptively. Data from RCTs were analyzed using intention-to-treat protocols. In addition, a sensitivity analysis was done assigning all missing data/withdrawals to the event. P values less than 0.05 were considered significant. A priori subgroup analyses were planned for the acuity of hospital-at-home program, type of hospital-at-home program (early discharge or admission avoidance), and severity of the patients’ COPD. Additional subgroup analyses were conducted as needed based on the identified literature. Post hoc sample size calculations were performed using STATA 10.1.
Quality of Evidence
The quality of each included study was assessed, taking into consideration allocation concealment, randomization, blinding, power/sample size, withdrawals/dropouts, and intention-to-treat analyses.
The quality of the body of evidence was assessed as high, moderate, low, or very low according to the GRADE Working Group criteria. The following definitions of quality were used in grading the quality of the evidence:
Summary of Findings
Fourteen studies met the inclusion criteria and were included in this review: 1 health technology assessment, 5 systematic reviews, and 7 RCTs.
The following conclusions are based on low to very low quality of evidence. The reviewed evidence was based on RCTs that were inadequately powered to observe differences between hospital-at-home and inpatient hospital care for most outcomes, so there is a strong possibility of type II error. Given the low to very low quality of evidence, these conclusions must be considered with caution.
Approximately 21% to 37% of patients with acute exacerbations of COPD who present to the ED may be eligible for hospital-at-home care.
Of the patients who are eligible for care, some may refuse to participate in hospital-at-home care.
Eligibility for hospital-at-home care may be increased depending on the design of the hospital-at-home program, such as the size of the geographical service area for hospital-at-home and the hours of operation for patient assessment and entry into hospital-at-home.
Hospital-at-home care for acute exacerbations of COPD was associated with a nonsignificant reduction in the risk of mortality and hospital readmissions compared with inpatient hospital care during 2- to 6-month follow-up.
Limited, very low quality evidence suggests that hospital readmissions are delayed in patients who received hospital-at-home care compared with those who received inpatient hospital care (mean additional days before readmission comparing hospital-at-home to inpatient hospital care ranged from 4 to 38 days).
There is insufficient evidence to determine whether hospital-at-home care, compared with inpatient hospital care, is associated with improved lung function.
The majority of studies did not find significant differences between hospital-at-home and inpatient hospital care for a variety of health-related quality of life measures at follow-up. However, follow-up may have been too late to observe an impact of hospital-at-home care on quality of life.
A conclusion about the impact of hospital-at-home care on length of stay for the initial exacerbation (defined as days in hospital or days in hospital plus hospital-at-home care for inpatient hospital and hospital-at-home, respectively) could not be determined because of limited and inconsistent evidence.
Patient and caregiver satisfaction with care is high for both hospital-at-home and inpatient hospital care.
PMCID: PMC3384361  PMID: 23074420
5.  Automated Detection of Infectious Disease Outbreaks in Hospitals: A Retrospective Cohort Study 
PLoS Medicine  2010;7(2):e1000238.
Susan Huang and colleagues describe an automated statistical software, WHONET-SaTScan, its application in a hospital, and the potential it has to identify hospital infection clusters that had escaped routine detection.
Detection of outbreaks of hospital-acquired infections is often based on simple rules, such as the occurrence of three new cases of a single pathogen in two weeks on the same ward. These rules typically focus on only a few pathogens, and they do not account for the pathogens' underlying prevalence, the normal random variation in rates, and clusters that may occur beyond a single ward, such as those associated with specialty services. Ideally, outbreak detection programs should evaluate many pathogens, using a wide array of data sources.
Methods and Findings
We applied a space-time permutation scan statistic to microbiology data from patients admitted to a 750-bed academic medical center in 2002–2006, using WHONET-SaTScan laboratory information software from the World Health Organization (WHO) Collaborating Centre for Surveillance of Antimicrobial Resistance. We evaluated patients' first isolates for each potential pathogenic species. In order to evaluate hospital-associated infections, only pathogens first isolated >2 d after admission were included. Clusters were sought daily across the entire hospital, as well as in hospital wards, specialty services, and using similar antimicrobial susceptibility profiles. We assessed clusters that had a likelihood of occurring by chance less than once per year. For methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant enterococci (VRE), WHONET-SaTScan–generated clusters were compared to those previously identified by the Infection Control program, which were based on a rule-based criterion of three occurrences in two weeks in the same ward. Two hospital epidemiologists independently classified each cluster's importance. From 2002 to 2006, WHONET-SaTScan found 59 clusters involving 2–27 patients (median 4). Clusters were identified by antimicrobial resistance profile (41%), wards (29%), service (13%), and hospital-wide assessments (17%). WHONET-SaTScan rapidly detected the two previously known gram-negative pathogen clusters. Compared to rule-based thresholds, WHONET-SaTScan considered only one of 73 previously designated MRSA clusters and 0 of 87 VRE clusters as episodes statistically unlikely to have occurred by chance. WHONET-SaTScan identified six MRSA and four VRE clusters that were previously unknown. Epidemiologists considered more than 95% of the 59 detected clusters to merit consideration, with 27% warranting active investigation or intervention.
Automated statistical software identified hospital clusters that had escaped routine detection. It also classified many previously identified clusters as events likely to occur because of normal random fluctuations. This automated method has the potential to provide valuable real-time guidance both by identifying otherwise unrecognized outbreaks and by preventing the unnecessary implementation of resource-intensive infection control measures that interfere with regular patient care.
Please see later in the article for the Editors' Summary
Editors' Summary
Admission to a hospital is often a life-saving necessity—individuals injured in a road accident, for example, may need immediate medical and surgical attention if they are to survive. Unfortunately, many patients acquire infections, some of which are life-threatening, during their stay in a hospital. The World Health Organization has estimated that, globally, 8.7% of hospital patients develop hospital-acquired infections (infections that are identified more than two days after admission to hospital). In the US alone, 2 million people develop a hospital-acquired infection every year, often an infection of a surgical wound, or a urinary tract or lung infection. Infections are common among hospital patients because increasing age or underlying illnesses can reduce immunity to infection and because many medical and surgical procedures bypass the body's natural protective barriers. In addition, poor infection control practices can facilitate the transmission of bacteria—including meticillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE)—and other infectious agents (pathogens) between patients.
Why Was This Study Done?
Sometimes, the number of cases of hospital-acquired infections increases unexpectedly or a new infection emerges. Such clusters account for relatively few health care–associated infections, but, because they may arise from the transmission of a pathogen within a hospital, they need to be rapidly identified and measures implemented (for example, isolation of affected patients) to stop transmission if an outbreak is confirmed. Currently, the detection of clusters of hospital-acquired infections is based on simple rules, such as the occurrence of three new cases of a single pathogen in two weeks on the same ward. This rule-based approach relies on the human eye to detect infection clusters within microbiology data (information collected on the pathogens isolated from patients), it focuses on a few pathogens, and it does not consider the random variation in infection rates or the possibility that clusters might be associated with shared facilities rather than with individual wards. In this study, the researchers test whether an automated statistical system can detect outbreaks of hospital-acquired infections quickly and accurately.
What Did the Researchers Do and Find?
The researchers combined two software packages used to track diseases in populations to create the WHONET-SaTScan cluster detection tool. They then compared the clusters of hospital-acquired infection identified by the new tool in microbiology data from a 750-bed US academic medical center with those generated by the hospital's infection control program, which was largely based on the simple rule described above. WHONET-SaTScan found 59 clusters of infection that occurred between 2002 and 2006, about three-quarters of which were identified by characteristics other than a ward-based location. Nearly half the cluster alerts were generated on the basis of shared antibiotic susceptibility patterns. Although WHONET-SaTScan identified all the clusters previously identified by the hospital's infection control program, it classified most of these clusters as likely to be the result of normal random variations in infection rates rather than the result of “true” outbreaks. By contrast, the hospital's infection control department only identified three of the 59 statistically significant clusters identified by WHONET-SaTScan. Furthermore, the new tool identified six previously unknown MRSA outbreaks and four previously unknown VRE outbreaks. Finally, two hospital epidemiologists (scientists who study diseases in populations) classified 95% of the clusters detected by WHONET-SaTScan as worthy of consideration by the hospital infection control team and a quarter of the clusters as warranting active investigation or intervention.
What Do These Findings Mean?
These findings suggest that automated statistical software should be able to detect clusters of hospital-acquired infections that would escape detection using routine rule-based systems. Importantly, they also suggest that an automated system would be able to discount a large number of supposed outbreaks identified by rule-based systems. These findings need to be confirmed in other settings and in prospective studies in which the outcomes of clusters detected with WHONET-SaTScan are carefully analyzed. For now, however, these findings suggest that automated statistical tools could provide hospital infection control experts with valuable real-time guidance by identifying outbreaks that would be missed by routine detection methods and by preventing the implementation of intensive and costly infection control measures in situations where they are unnecessary.
Additional Information
Please access these Web sites via the online version of this summary at
The World Health Organization's Prevention of Hospital-Acquired Infections, A Practical Guide contains detailed information on all aspects of hospital-acquired infections
MedlinePlus provides links to information on infection control in hospitals (in English and Spanish)
The US Centers for Disease Control and Prevention also provides information on infectious diseases in health care settings (in English and Spanish)
The WHONET/Baclink software and the SatScan software, the two components of WHONET-SaTScan are both available on the internet (the WHONET-SaTScan cluster detection tool is freely available as part of the version of WHONET/BacLink released June 2009)
PMCID: PMC2826381  PMID: 20186274
6.  Excess acute care bed capacity and its causes: the experience of New York State. 
Health Services Research  1995;30(1 Pt 1):115-131.
OBJECTIVE. The study was developed to identify numbers of excess hospital medical-surgical and pediatric bed capacity and the variables that produce them in the counties of New York State. DATA SOURCES/STUDY SETTING. Data were collected from New York's Statewide Planning and Research Cooperative System (SPARCS) for 1991. This system includes data for all hospital discharges in New York State by county. The counties of New York State include a full range of urban, suburban, and rural settings. STUDY DESIGN. A methodology was developed for projecting excess numbers of acute medical-surgical and pediatric beds. The impact of utilization variables (such as hospital discharge rates and lengths of stay) on bed levels were analyzed, as well as the effects of demographic, social, and health care resource availability. DATA COLLECTION/EXTRACTION METHODS. Data were collected through discharge abstracts provided by hospitals in New York State. PRINCIPAL FINDINGS. The data demonstrated that hospital discharges and lengths of stay contributed to excess utilization at different levels in New York State counties. The data also identified relationships between lower incomes and educational levels, as well as larger supplies of physicians and high-variation discharges, and excess beds. CONCLUSIONS. The causes of excess hospital beds varied considerably among communities in New York State; each community must develop its own approach to this problem.
PMCID: PMC1070353  PMID: 7721582
7.  Costs of day hospital and community residential chemical dependency treatment 
Evidence suggests that expensive hospital-based inpatient chemical dependency programs do not deliver outcomes that are superior to less costly day hospital programs, but patient placement criteria developed by the Addiction Society of Medicine (ASAM) nonetheless have identified a need for low-intensity residential treatment for patients with higher levels of severity. Community-based residential programs may represent a low-cost inpatient alternative that satisfies the ASAM criteria, but research is lacking in this area. A recent clinical trial has found similar outcomes at social model residential treatment and clinically-oriented day hospital programs, but did not report on the costs associated with treatment in that study.
This paper addresses whether the similar outcomes in the recent trial were delivered with comparable costs. It also studies costs separately for men and women, and for Whites and non-Whites, subgroups not included or identified in prior cost effectiveness work.
This paper reports on clients who participated in a randomized trial conducted in three metropolitan areas served by a large pre-paid health plan. Clients were eligible if they met the first five dimensions of the ASAM criteria for low-intensity residential treatment and had not been mandated to residential treatment due to dangerous home environment (the sixth ASAM dimension). The five day hospital programs included here are typical of mainstream private chemical dependency programs that were developed as an alternative to inpatient treatment. The seven residential programs are typical of those historically developed by members of alcohol mutual-help programs. Cost data for the study sites were collected using the Drug Abuse Treatment Cost Analysis Program (DATCAP) which produces estimates of average costs per week per client treated at a particular treatment program. Lengths of stay were derived from program records. Costs per episode for each study subject were calculated by multiplying the DATCAP-based program-specific costs (per week) by the number of weeks the subject stayed in the program to which they had been randomly assigned. Differences in length of stay, and in per-episode costs, were compared between residential and day hospital subjects using the Brown-Forsythe robust test of the equality of means.
Lengths of stay at residential treatment were significantly longer than at day hospital, in the sample overall and in the disaggregated analyses for both genders and for both Whites and non-Whites. This difference was especially marked among non-Whites, who had quite short stays in day hospital. The average cost per week was $575 per week at day hospital, versus $370 per week at the residential programs. However, because of the longer stays in residential programs, this lower cost per week did not always translate to lower per-episode costs. Instead, the per-episode costs were significantly higher for those treated in residential programs than in day hospital in the sample overall, and among non-Whites. Costs were comparable for Whites and for women treated in either setting, but were marginally higher for men randomized to residential programs.
These cost results must be considered in light of the null findings comparing outcomes between subjects randomized to residential versus day hospital programs in this study, in the overall sample and by gender and race/ethnicity: That is, the longer stays in the sample overall and for non-White clients at residential programs came at higher costs but did not lead to better rates of abstinence. An important component of the cost differential arose from especially short stays in day hospital among non-Whites, calling into question the attractiveness of day hospital for minority clients.
Outcomes and costs at residential versus day hospital programs were similar for women and for Whites in a randomized trial of pre-paid health plan members who met ASAM criteria for low-intensity residential treatment but were not at environmental risk. For non-Whites, and marginally for men, a preference for residential care would appear to come at a higher cost.
Implications for health care provision and use
Lengths of stay in residential treatment are significantly longer than in day hospital, but costs per week are lower. Women and Whites appear to be equally well-served in residential and day hospital programs, with no significant cost differential. Provision of residential treatment for non-Whites may be more costly than day hospital, because their residential stays are likely to be 3 times longer than they would be if treated in day hospital. For men, residential care will be marginally more costly.
Implications for health policy formulation
Residential treatment appears to represent a cost-effective alternative to day hospital for female and White clients with severe alcohol and drug problems who are not at environmental risk, although it will be important that the current study be replicated with different samples and study programs.
Implications for further research
The much shorter stays in day hospital than at residential among non-Whites highlight the need for research to better understand how to best meet the needs and preferences of non-White clients when considering both costs and outcomes.
PMCID: PMC2744443  PMID: 18424874
8.  Community-Based Care for the Specialized Management of Heart Failure 
Executive Summary
In August 2008, the Medical Advisory Secretariat (MAS) presented a vignette to the Ontario Health Technology Advisory Committee (OHTAC) on a proposed targeted health care delivery model for chronic care. The proposed model was defined as multidisciplinary, ambulatory, community-based care that bridged the gap between primary and tertiary care, and was intended for individuals with a chronic disease who were at risk of a hospital admission or emergency department visit. The goals of this care model were thought to include: the prevention of emergency department visits, a reduction in hospital admissions and re-admissions, facilitation of earlier hospital discharge, a reduction or delay in long-term care admissions, and an improvement in mortality and other disease-specific patient outcomes.
OHTAC approved the development of an evidence-based assessment to determine the effectiveness of specialized community based care for the management of heart failure, Type 2 diabetes and chronic wounds.
Please visit the Medical Advisory Secretariat Web site at: to review the following reports associated with the Specialized Multidisciplinary Community-Based care series.
Specialized multidisciplinary community-based care series: a summary of evidence-based analyses
Community-based care for the specialized management of heart failure: an evidence-based analysis
Community-based care for chronic wound management: an evidence-based analysis
Please note that the evidence-based analysis of specialized community-based care for the management of diabetes titled: “Community-based care for the management of type 2 diabetes: an evidence-based analysis” has been published as part of the Diabetes Strategy Evidence Platform at this URL:
Please visit the Toronto Health Economics and Technology Assessment Collaborative Web site at: to review the following economic project associated with this series:
Community-based Care for the specialized management of heart failure: a cost-effectiveness and budget impact analysis.
The objective of this evidence-based analysis was to determine the effectiveness of specialized multidisciplinary care in the management of heart failure (HF).
Clinical Need: Target Population and Condition
HF is a progressive, chronic condition in which the heart becomes unable to sufficiently pump blood throughout the body. There are several risk factors for developing the condition including hypertension, diabetes, obesity, previous myocardial infarction, and valvular heart disease.(1) Based on data from a 2005 study of the Canadian Community Health Survey (CCHS), the prevalence of congestive heart failure in Canada is approximately 1% of the population over the age of 12.(2) This figure rises sharply after the age of 45, with prevalence reports ranging from 2.2% to 12%.(3) Extrapolating this to the Ontario population, an estimated 98,000 residents in Ontario are believed to have HF.
Disease management programs are multidisciplinary approaches to care for chronic disease that coordinate comprehensive care strategies along the disease continuum and across healthcare delivery systems.(4) Evidence for the effectiveness of disease management programs for HF has been provided by seven systematic reviews completed between 2004 and 2007 (Table 1) with consistency of effect demonstrated across four main outcomes measures: all cause mortality and hospitalization, and heart-failure specific mortality and hospitalization. (4-10)
However, while disease management programs are multidisciplinary by definition, the published evidence lacks consistency and clarity as to the exact nature of each program and usual care comparators are generally ill defined. Consequently, the effectiveness of multidisciplinary care for the management of persons with HF is still uncertain. Therefore, MAS has completed a systematic review of specialized, multidisciplinary, community-based care disease management programs compared to a well-defined usual care group for persons with HF.
Evidence-Based Analysis Methods
Research Questions
What is the effectiveness of specialized, multidisciplinary, community-based care (SMCCC) compared with usual care for persons with HF?
Literature Search Strategy
A comprehensive literature search was completed of electronic databases including MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, Cochrane Library and Cumulative Index to Nursing & Allied Health Literature. Bibliographic references of selected studies were also searched. After a review of the title and abstracts, relevant studies were obtained and the full reports evaluated. All studies meeting explicit inclusion and exclusion criteria were retained. Where appropriate, a meta-analysis was undertaken to determine the pooled estimate of effect of specialized multidisciplinary community-based care for explicit outcomes. The quality of the body of evidence, defined as one or more relevant studies was determined using GRADE Working Group criteria. (11)
Inclusion Criteria
Randomized controlled trial
Systematic review with meta analysis
Population includes persons with New York Heart Association (NYHA) classification 1-IV HF
The intervention includes a team consisting of a nurse and physician one of which is a specialist in HF management.
The control group receives care by a single practitioner (e.g. primary care physician (PCP) or cardiologist)
The intervention begins after discharge from the hospital
The study reports 1-year outcomes
Exclusion Criteria
The intervention is delivered predominately through home-visits
Studies with mixed populations where discrete data for HF is not reported
Outcomes of Interest
All cause mortality
All cause hospitalization
HF specific mortality
HF specific hospitalization
All cause duration of hospital stay
HF specific duration of hospital stay
Emergency room visits
Quality of Life
Summary of Findings
One large and seven small randomized controlled trials were obtained from the literature search.
A meta-analysis was completed for four of the seven outcomes including:
All cause mortality
HF-specific mortality
All cause hospitalization
HF-specific hospitalization.
Where the pooled analysis was associated with significant heterogeneity, subgroup analyses were completed using two primary categories:
direct and indirect model of care; and
type of control group (PCP or cardiologist).
The direct model of care was a clinic-based multidisciplinary HF program and the indirect model of care was a physician supervised, nurse-led telephonic HF program.
All studies, except one, were completed in jurisdictions outside North America. (12-19) Similarly, all but one study had a sample size of less than 250. The mean age in the studies ranged from 65 to 77 years. Six of the studies(12;14-18) included populations with a NYHA classification of II-III. In two studies, the control treatment was a cardiologist (12;15) and two studies reported the inclusion of a dietitian, physiotherapist and psychologist as members of the multidisciplinary team (12;19).
All Cause Mortality
Eight studies reported all cause mortality (number of persons) at 1 year follow-up. (12-19) When the results of all eight studies were pooled, there was a statistically significant RRR of 29% with moderate heterogeneity (I2 of 38%). The results of the subgroup analyses indicated a significant RRR of 40% in all cause mortality when SMCCC is delivered through a direct team model (clinic) and a 35% RRR when SMCCC was compared with a primary care practitioner.
HF-Specific Mortality
Three studies reported HF-specific mortality (number of persons) at 1 year follow-up. (15;18;19) When the results of these were pooled, there was an insignificant RRR of 42% with high statistical heterogeneity (I2 of 60%). The GRADE quality of evidence is moderate for the pooled analysis of all studies.
All Cause Hospitalization
Seven studies reported all cause hospitalization at 1-year follow-up (13-15;17-19). When pooled, their results showed a statistically insignificant 12% increase in hospitalizations in the SMCCC group with high statistical heterogeneity (I2 of 81%). A significant RRR of 12% in all cause hospitalization in favour of the SMCCC care group was achieved when SMCCC was delivered using an indirect model (telephonic) with an associated (I2 of 0%). The Grade quality of evidence was found to be low for the pooled analysis of all studies and moderate for the subgroup analysis of the indirect team care model.
HF-Specific Hospitalization
Six studies reported HF-specific hospitalization at 1-year follow-up. (13-15;17;19) When pooled, the results of these studies showed an insignificant RRR of 14% with high statistical heterogeneity (I2 of 60%); however, the quality of evidence for the pooled analysis of was low.
Duration of Hospital Stay
Seven studies reported duration of hospital stay, four in terms of mean duration of stay in days (14;16;17;19) and three in terms of total hospital bed days (12;13;18). Most studies reported all cause duration of hospital stay while two also reported HF-specific duration of hospital stay. These data were not amenable to meta-analyses as standard deviations were not provided in the reports. However, in general (and in all but one study) it appears that persons receiving SMCCC had shorter hospital stays, whether measured as mean days in hospital or total hospital bed days.
Emergency Room Visits
Only one study reported emergency room visits. (14) This was presented as a composite of readmissions and ER visits, where the authors reported that 77% (59/76) of the SMCCC group and 84% (63/75) of the usual care group were either readmitted or had an ER visit within the 1 year of follow-up (P=0.029).
Quality of Life
Quality of life was reported in five studies using the Minnesota Living with HF Questionnaire (MLHFQ) (12-15;19) and in one study using the Nottingham Health Profile Questionnaire(16). The MLHFQ results are reported in our analysis. Two studies reported the mean score at 1 year follow-up, although did not provide the standard deviation of the mean in their report. One study reported the median and range scores at 1 year follow-up in each group. Two studies reported the change scores of the physical and emotional subscales of the MLHFQ of which only one study reported a statistically significant change from baseline to 1 year follow-up between treatment groups in favour of the SMCCC group in the physical sub-scale. A significant change in the emotional subscale scores from baseline to 1 year follow-up in the treatment groups was not reported in either study.
There is moderate quality evidence that SMCCC reduces all cause mortality by 29%. There is low quality evidence that SMCCC contributes to a shorter duration of hospital stay and improves quality of life compared to usual care. The evidence supports that SMCCC is effective when compared to usual care provided by either a primary care practitioner or a cardiologist. It does not, however, suggest an optimal model of care or discern what the effective program components are. A field evaluation could address this uncertainty.
PMCID: PMC3377506  PMID: 23074521
9.  The effect of physician practice organization on efficient utilization of hospital resources. 
Health Services Research  1994;29(5):583-603.
OBJECTIVE. This study examines variations in the efficient use of hospital resources across individual physicians. DATA SOURCES AND SETTING. The study is conducted over a two-year period (1989-1990) in all short-term general hospitals with 50 or more beds in Arizona. We examine hospital discharge data for 43,625 women undergoing cesarean sections and vaginal deliveries without complications. These data include physician identifiers that permit us to link patient information with information on physicians provided by the state medical association. STUDY DESIGN. The study first measures the contribution of physician characteristics to the explanatory power of regression models that predict resource use. It then tests hypothesized effects on resource utilization exerted by two sets of physician level factors: physician background and physician practice organization. The latter includes effects of hospital practice volume, concentration of hospital practice, percent managed care patients in one's hospital practice, and diversity of patients treated. Efficiency (inefficiency) is measured as the degree of variation in patient charges and length of stay below (above) the average of treating all patients with the same condition in the same hospital in the same year with the same severity of illness, controlling for discharge status and the presence of complications. PRINCIPAL FINDINGS. After controlling for patient factors, physician characteristics explain a significant amount of the variability in hospital charges and length of stay in the two maternity conditions. Results also support hypotheses that efficiency is influenced by practice organization factors such as patient volume and managed care load. Physicians with larger practices and a higher share of managed care patients appear to be more efficient. CONCLUSIONS. The results suggest that health care reform efforts to develop physician-hospital networks and managed competition may promote greater parsimony in physicians' practice behavior.
PMCID: PMC1070029  PMID: 8002351
10.  Evaluating Syndromic Data for Surveillance of Non-infectious Disease 
To evaluate several non-infectious disease related syndromes that are based on chief complaint (cc) emergency department (ED) syndromic surveillance (SS) data by comparing these with the New York Statewide Planning and Research Cooperative System (SPARCS) clinical diagnosis data. In particular, this work compares SS and SPARCS data for total ED visits and visits associated with three non-infectious disease syndromes, namely asthma, oral health and hypothermia.
Syndromic surveillance data has predominantly been used for surveillance of infectious disease and for broad symptom types that could be associated with bioterrorism. There has been a growing interest to expand the uses of syndromic data beyond infectious disease. Because many of these conditions are specific and can be swiftly diagnosed (as opposed to infectious agents that require a lab test for confirmation) there could be added value in using the ICD9 ED discharge diagnosis field collected by SS. However, SS discharge diagnosis data is not complete or as timely as chief complaint data. Therefore, for the time being SS chief complaint data is relied on for non-infectious disease surveillance.
SPARCS data are based on clinical diagnoses and include information on final diagnosis, providing a means for comparing the chief complaint (from SS) to a diagnosis code (from SPARCS), for evaluating how well the syndrome is captured by SS and for assessing if it would be advantageous to get SS ED diagnosis codes in a more timely and complete manner.
Syndromes previously developed by the DOHMH were used for this work. Syndrome definitions are based on querying the cc field in SS data for terms associated with asthma, oral health and hypothermia. The asthma syndrome consists of search terms for ‘ASTHMA’, ‘WHEEZING’ and ‘COPD’. The oral health syndrome uses (‘TOOTH’ or ‘GUM’) and (‘ACHE’, ‘HURT’) and excludes visits resulting from trauma (e.g., ‘INJURY’, ‘ACCIDENT’). The hypothermia syndrome is limited to search for the word ‘HYPOTHERMIA’. For the purpose of comparison of the SS data with SPARCS data for the three syndromes, the following ICD9 diagnosis codes were considered in SPARCS: 493 for asthma, 521–523, 525, 528–529 for oral health and 991 for hypothermia.
SS and SPARCS data for 2007 were used for this work as this was the most recent and complete SPARCS ED dataset that was available. Overall city-wide daily counts and hospital-level annual counts for total ED, asthma-, oral health- and hypothermia-related visits were computed for SS ED data and SPARCS ED data. A comparison of daily and hospital trends for SS and SPARCS for total and syndrome-related counts were conducted using correlation coefficients.
There is a high correlation between total ED SS and SPARCS daily counts (r=0.98, p-value<0.001). On average, SPARCS daily counts are higher by approximately 75 visits (range: −674, 591) per day. Correlations between SS and SPARCS daily counts for asthma, oral health and hypothermia were 0.96 (p-value<0.001), 0.66 (p-value<0.001) and 0.45 (p-value<0.001), respectively. Correlations between SS and SPARCS hospital-level annual counts for asthma, oral health and hypothermia were 0.89 (p<0.001), 0.87 (p<0.001) and 0.07 (p=0.61). In 2007, less than 8% of individual SS records had a discharge diagnosis, and this was found to vary between hospitals (0–69%); therefore, a comparison between SS discharge diagnosis and SPARCS diagnosis data was not possible.
Overall, syndromic surveillance data was found to be a useful data source for public health surveillance of non-infectious disease. Total ED visits were found to be comparable between SS and SPARCS. While direct comparison of counts for syndromes is not possible, the daily syndrome counts between SS and SPARCS correlated well. However, the strength of correlation varied depending on the syndrome, with a better correlation for syndromes with larger volume of visits to the ED (e.g., asthma) and with more commonly used terms in the cc search (e.g., ‘tooth ache’) compared to syndromes with very specific search terms (e.g., ‘hypothermia’).
In certain instances, it is hypothesized that SS discharge diagnosis would provide more reliable and representative estimates than cc for tracking non-infectious disease. Future work will consider a period with more complete SS ED discharge diagnosis data for further comparisons and to test the hypothesis that more complete and timely SS ED discharge diagnosis data could improve surveillance efforts.
PMCID: PMC3692813
chief complaint; syndromic surveillance; New York City; non-infectious disease; discharge diagnosis
11.  Event Rates, Hospital Utilization, and Costs Associated with Major Complications of Diabetes: A Multicountry Comparative Analysis 
PLoS Medicine  2010;7(2):e1000236.
Philip Clarke and colleagues examined patient-level data for over 11,000 participants with type 2 diabetes from 20 countries and find that major complications of diabetes significantly increased hospital use and costs across settings.
Diabetes imposes a substantial burden globally in terms of premature mortality, morbidity, and health care costs. Estimates of economic outcomes associated with diabetes are essential inputs to policy analyses aimed at prevention and treatment of diabetes. Our objective was to estimate and compare event rates, hospital utilization, and costs associated with major diabetes-related complications in high-, middle-, and low-income countries.
Methods and Findings
Incidence and history of diabetes-related complications, hospital admissions, and length of stay were recorded in 11,140 patients with type 2 diabetes participating in the Action in Diabetes and Vascular Disease (ADVANCE) study (mean age at entry 66 y). The probability of hospital utilization and number of days in hospital for major events associated with coronary disease, cerebrovascular disease, congestive heart failure, peripheral vascular disease, and nephropathy were estimated for three regions (Asia, Eastern Europe, and Established Market Economies) using multiple regression analysis. The resulting estimates of days spent in hospital were multiplied by regional estimates of the costs per hospital bed-day from the World Health Organization to compute annual acute and long-term costs associated with the different types of complications. To assist, comparability, costs are reported in international dollars (Int$), which represent a hypothetical currency that allows for the same quantities of goods or services to be purchased regardless of country, standardized on purchasing power in the United States. A cost calculator accompanying this paper enables the estimation of costs for individual countries and translation of these costs into local currency units. The probability of attending a hospital following an event was highest for heart failure (93%–96% across regions) and lowest for nephropathy (15%–26%). The average numbers of days in hospital given at least one admission were greatest for stroke (17–32 d across region) and heart failure (16–31 d) and lowest for nephropathy (12–23 d). Considering regional differences, probabilities of hospitalization were lowest in Asia and highest in Established Market Economies; on the other hand, lengths of stay were highest in Asia and lowest in Established Market Economies. Overall estimated annual hospital costs for patients with none of the specified events or event histories ranged from Int$76 in Asia to Int$296 in Established Market Economies. All complications included in this analysis led to significant increases in hospital costs; coronary events, cerebrovascular events, and heart failure were the most costly, at more than Int$1,800, Int$3,000, and Int$4,000 in Asia, Eastern Europe, and Established Market Economies, respectively.
Major complications of diabetes significantly increase hospital use and costs across various settings and are likely to impose a high economic burden on health care systems.
Please see later in the article for the Editors' Summary
Editors' Summary
Worldwide, nearly 250 million people have diabetes, and this number is increasing rapidly. Diabetes is characterized by dangerous amounts of sugar (glucose) in the blood. Blood sugar levels are normally controlled by insulin, a hormone produced by the pancreas. Blood sugar control fails in people with diabetes because they make no insulin (type 1 diabetes) or, more commonly, because the fat and muscle cells that usually respond to insulin by removing excess sugar from the blood have become insulin insensitive (type 2 diabetes). Type 2 diabetes can be prevented and controlled by eating a healthy diet and exercising regularly. It can also be treated with drugs that help the pancreas make more insulin or that increase insulin sensitivity. Major long-term complications of diabetes include kidney failure and an increased risk of cardiovascular problems such as heart attacks, heart failure, stroke, and problems with the blood vessels in the arms and legs. Because of these complications, the life expectancy of people with diabetes is about ten years shorter than that of people without diabetes.
Why Was This Study Done?
Diabetes imposes considerable demands on health care systems but little is known about the direct medical costs associated with treating this chronic disease in low- and middle-income countries where more than three-quarters of affected people live. In particular, although estimates have been made of the overall resources devoted to the treatment of diabetes, very little is known about how the different long-term complications of diabetes contribute to health care costs in different countries. Public-health experts and governments need this information to help them design effective and sustainable policies for the prevention and treatment of diabetes. In this study, the researchers estimate the resource use associated with diabetes-related complications in three economic regions using information collected in the Action in Diabetes and Vascular Disease (ADVANCE) study. This multinational clinical trial is investigating how drugs that control blood pressure and blood sugar levels affect the long-term complications of diabetes.
What Did the Researchers Do and Find?
The researchers recorded diabetes-related complications, hospital admissions for these complications, and length of hospital stays in 11,140 patients with severe diabetes from 20 countries who participated in the ADVANCE study. They used “multiple regression analysis” to estimate the number of days spent in hospital for diabetes-related complications in Asia, Eastern Europe, and the Established Market Economies (Canada, Australia, New Zealand, and several Western European countries). Finally, they calculated the economic costs of each complication using regional estimates of the costs per bed-day from the World Health Organization's CHOICE project (CHOosing Interventions that are Cost Effective). Nearly everyone in the study who developed heart failure attended a hospital, but only 15%–26% of people attended a hospital for kidney problems. The chances of hospitalization for any complication were lowest in Asia and highest in the Established Market Economies; conversely, lengths of stay were longest in Asia and shortest in the Established Market Economies. Finally, the estimated annual hospital costs for patients who had a coronary event, stroke, or heart failure were more than Int$1,800, Int$3,000, and Int$4,000 in Asia, Eastern Europe, and the Established Market Economies, respectively (the international dollar, Int$, is a hypothetical currency that has the same purchasing power in all countries), compared to Int$76, Int$156, and Int$296 for patients who experienced none of these events.
What Do These Findings Mean?
Because the ADVANCE trial had strict entry criteria, the findings of this study may not be generalizable to the broader population of people with diabetes. Nevertheless, given the lack of information about the costs associated with diabetes-related complications in low- and middle-income countries, these findings provide important new information about the patterns of hospital resource use and costs in these countries. Specifically, these findings show that the major complications of diabetes greatly increase hospital use and costs in all three economic regions considered and impose a high economic burden on health care systems that is likely to increase as the diabetes epidemic develops. Importantly, these findings should help policy makers anticipate the future health care costs associated with diabetes and should help them evaluate which therapies aimed at preventing diabetes-related complications will reduce these costs most effectively.
Additional Information
Please access these Web sites via the online version of this summary at
The International Diabetes Federation provides information about all aspects of diabetes
The US National Diabetes Information Clearinghouse provides detailed information about diabetes for patients, health care professionals, and the general public (in English and Spanish)
The UK National Health Service also provides information for patients and caregivers about type 2 diabetes (in several languages)
Information about the ADVANCE study is available
The World Health Organization's CHOICE Web site provides information about the analysis of the cost effectiveness of health care interventions
PMCID: PMC2826379  PMID: 20186272
12.  Optimizing triage and hospitalization in adult general medical emergency patients: the triage project 
Patients presenting to the emergency department (ED) currently face inacceptable delays in initial treatment, and long, costly hospital stays due to suboptimal initial triage and site-of-care decisions. Accurate ED triage should focus not only on initial treatment priority, but also on prediction of medical risk and nursing needs to improve site-of-care decisions and to simplify early discharge management. Different triage scores have been proposed, such as the Manchester triage system (MTS). Yet, these scores focus only on treatment priority, have suboptimal performance and lack validation in the Swiss health care system. Because the MTS will be introduced into clinical routine at the Kantonsspital Aarau, we propose a large prospective cohort study to optimize initial patient triage. Specifically, the aim of this trial is to derive a three-part triage algorithm to better predict (a) treatment priority; (b) medical risk and thus need for in-hospital treatment; (c) post-acute care needs of patients at the most proximal time point of ED admission.
Prospective, observational, multicenter, multi-national cohort study. We will include all consecutive medical patients seeking ED care into this observational registry. There will be no exclusions except for non-adult and non-medical patients. Vital signs will be recorded and left over blood samples will be stored for later batch analysis of blood markers. Upon ED admission, the post-acute care discharge score (PACD) will be recorded. Attending ED physicians will adjudicate triage priority based on all available results at the time of ED discharge to the medical ward. Patients will be reassessed daily during the hospital course for medical stability and readiness for discharge from the nurses and if involved social workers perspective. To assess outcomes, data from electronic medical records will be used and all patients will be contacted 30 days after hospital admission to assess vital and functional status, re-hospitalization, satisfaction with care and quality of life measures.
We aim to include between 5000 and 7000 patients over one year of recruitment to derive the three-part triage algorithm. The respective main endpoints were defined as (a) initial triage priority (high vs. low priority) adjudicated by the attending ED physician at ED discharge, (b) adverse 30 day outcome (death or intensive care unit admission) within 30 days following ED admission to assess patients risk and thus need for in-hospital treatment and (c) post acute care needs after hospital discharge, defined as transfer of patients to a post-acute care institution, for early recognition and planning of post-acute care needs. Other outcomes are time to first physician contact, time to initiation of adequate medical therapy, time to social worker involvement, length of hospital stay, reasons for discharge delays, patient’s satisfaction with care, overall hospital costs and patients care needs after returning home.
Using a reliable initial triage system for estimating initial treatment priority, need for in-hospital treatment and post-acute care needs is an innovative and persuasive approach for a more targeted and efficient management of medical patients in the ED. The proposed interdisciplinary , multi-national project has unprecedented potential to improve initial triage decisions and optimize resource allocation to the sickest patients from admission to discharge. The algorithms derived in this study will be compared in a later randomized controlled trial against a usual care control group in terms of resource use, length of hospital stay, overall costs and patient’s outcomes in terms of mortality, re-hospitalization, quality of life and satisfaction with care.
Trial registration Identifier, NCT01768494
PMCID: PMC3723418  PMID: 23822525
Triage; Biomarker; Post-acute care needs; Emergency medicine; Manchester triage system
13.  Do Hospital Length of Stay and Staffing Ratio Affect Elderly Patients' Risk of Readmission? A Nation-wide Study of Norwegian Hospitals 
Health Services Research  2002;37(3):647-665.
To test whether there is an association between hospital operating conditions such as average length of stays (LOS) and staffing ratio, and elderly patients' risk of readmission.
Data Sources
The main data source was a national patient database of admissions to all acute-care Norwegian hospitals during the year of 1996.
Study Design
It is a cross-sectional study, where Cox' regression analysis was used to test the factors acting on the probability of early unplanned readmission (within 30 days), and later occurring ones. The principal hospital variables included average hospital LOS and staffing ratio (discharges per man-years of personnel). Adjusting patient variables in the model included age, gender, and cost-weights of the Diagnosis Related Groups (DRGs).
Data Extraction Methods
The selected material included discharges from 59 hospitals, and 113,055 elderly patients (≥67 years). Multiple admissions to the same hospital were linked together chronologically, and additional hospital data were matched on. To maximize the association between the index stay and the defined outcome (unplanned readmission), no intervening planned admission was accepted.
Principal Findings
Being admitted to a hospital with relatively short average LOS increased the patient's risk of early readmission significantly. In addition it was found that more intensive care (more staff) could have a compensatory effect. Furthermore, the predictive factors were shown to be time dependent, as hospital variables had much less impact on readmissions occurring late (within 90–180 days).
The results give support to the assumption of a link between hospital operating conditions and patient outcome.
PMCID: PMC1434663  PMID: 12132599
Patient readmission; outcome assessment (health care); multivariate analysis; hospitals
14.  Effectiveness of early discharge planning in acutely ill or injured hospitalized older adults: a systematic review and meta-analysis 
BMC Geriatrics  2013;13:70.
Older age and higher acuity are associated with prolonged hospital stays and hospital readmissions. Early discharge planning may reduce lengths of hospital stay and hospital readmissions; however, its effectiveness with acutely admitted older adults is unclear.
In this systematic review, we compared the effectiveness of early discharge planning to usual care in reducing index length of hospital stay, hospital readmissions, readmission length of hospital stay, and mortality; and increasing satisfaction with discharge planning and quality of life for older adults admitted to hospital with an acute illness or injury.
We searched the Cochrane Library, DARE, HTA, NHSEED, ACP, MEDLINE, EMBASE, CINAHL, Proquest Dissertations and Theses, PubMed, Web of Science, SciSearch, PEDro, Sigma Theta Tau International’s registry of nursing research, Joanna Briggs Institute, CRISP, OT Seeker, and several internet search engines. Hand-searching was conducted in four gerontological journals and references of all included studies and previous systematic reviews. Two reviewers independently extracted data and assessed risk of bias. Data were pooled using a random-effects meta-analysis. Where meta-analysis was not possible, narrative analysis was performed.
Nine trials with a total of 1736 participants were included. Compared to usual care, early discharge planning was associated with fewer hospital readmissions within one to twelve months of index hospital discharge [risk ratio (RR) = 0.78, 95% CI = 0.69 − 0.90]; and lower readmission lengths of hospital stay within three to twelve months of index hospital discharge [weighted mean difference (WMD) = −2.47, 95% confidence intervals (CI) = −4.13 − −0.81)]. No differences were found in index length of hospital stay, mortality or satisfaction with discharge planning. Narrative analysis of four studies indicated that early discharge planning was associated with greater overall quality of life and the general health domain of quality of life two weeks after index hospital discharge.
Early discharge planning with acutely admitted older adults improves system level outcomes after index hospital discharge. Service providers can use these findings to design and implement early discharge planning for older adults admitted to hospital with an acute illness or injury.
PMCID: PMC3707815  PMID: 23829698
Discharge planning; Aged; Length of stay; Hospital readmission; Patient discharge; Systematic review; Meta-analysis
15.  What effect does physician "profiling" have on inpatient physician satisfaction and hospital length of stay? 
2002 marked the first time that the rate of hospital spending in the United States outpaced the overall health care spending rate of growth since 1991. As hospital spending continues to grow and as reimbursement for hospital expenses has moved towards the prospective payment system, there is still increasing pressure to reduce costs. Hospitals have a major incentive to decrease resource utilization, including hospital length of stay. We evaluated whether physician profiling affects physician satisfaction and hospital length of stay, and assessed physicians' views concerning hospital cost containment and the quality of care they provide.
To determine if physician profiling affects hospital length of stay and/or physician satisfaction, we used quasi-experimental with before-versus-after and intervention-versus-control comparisons of length of stay data collected at an intervention and six control hospitals. Intervention hospital physicians were informed their length of stay would be compared to their peers and were given a questionnaire assessing their experience.
Nearly half of attending pre-profiled physicians felt negative about the possibility of being profiled, while less than one-third of profiled physicians reported feeling negative about having been profiled. Nearly all physicians greatly enjoyed their ward month. Length of stay at the profiled site decreased by an additional 1/3 of a day in the profiling year, compared to the non-profiled sites (p < 0.001).
A relatively non-instrusive profiling intervention modestly reduced length of stay without adversely affecting physician satisfaction.
PMCID: PMC1481613  PMID: 16595002
16.  Longer postpartum hospitalization options – who stays, who leaves, what changes? 
This paper examines the practice implications of a policy initiative, namely, offering women in Ontario Canada up to a 60-hour postpartum in-hospital stay following an uncomplicated vaginal delivery. This change was initiated out of concern for the effects of 'early' discharge on the health of mothers and their infants. We examined who was offered and who accepted extended stays, to determine what factors were associated with the offer and acceptance of this option, and the impact that these decisions had on post-discharge health status and service utilization of mothers and infants.
The data reported here came from two related studies of health outcomes and service utilization of mothers and infants. Data were collected from newly delivered mothers who had uncomplicated vaginal deliveries. Questionnaires prior to discharge and structured telephone interviews at 4-weeks post discharge were used to collect data before and after policy implementation. Qualitative data were collected using focus groups with hospital and community-based health care managers and providers at each site. For both studies, samples were drawn from the same five purposefully selected hospitals. Further analysis compared postpartum health outcomes and post discharge service utilization of women and infants before and after the practice change.
Average length of stay (LOS) increased marginally. There was a significant reduction in stays of <24 hours. The offer of up to a 60-hour LOS was dependent upon the hospital site, having a family physician, and maternal ethnicity. Acceptance of a 60-hour LOS was more likely if the baby had a post-delivery medical problem, it was the woman's first live birth, the mother identified two or more unmet learning needs in hospital, or the mother was unsure about her own readiness for discharge. Mother and infant health status in the first 4 weeks after discharge were unchanged following introduction of the extended stay option. Infant service use also was unchanged but rate of maternal readmission to hospital increased and mothers' use of community physicians and emergency rooms decreased.
This research demonstrates that this policy change was selectively implemented depending upon both institutional and maternal factors. LOS marginally increased overall with a significant decrease in <24-hour stays. Neither health outcomes nor service utilization changed for infants. Women's health outcomes remained unchanged but service utilization patterns changed.
PMCID: PMC1266374  PMID: 16225678
17.  Physician Emigration from Sub-Saharan Africa to the United States: Analysis of the 2011 AMA Physician Masterfile 
PLoS Medicine  2013;10(9):e1001513.
Siankam Tankwanchi and colleagues used the AMA Physician Masterfile and the WHO Global Health Workforce Statistics on physicians in sub-Saharan Africa to determine trends in physician emigration to the United States.
Please see later in the article for the Editors' Summary
The large-scale emigration of physicians from sub-Saharan Africa (SSA) to high-income nations is a serious development concern. Our objective was to determine current emigration trends of SSA physicians found in the physician workforce of the United States.
Methods and Findings
We analyzed physician data from the World Health Organization (WHO) Global Health Workforce Statistics along with graduation and residency data from the 2011 American Medical Association Physician Masterfile (AMA-PM) on physicians trained or born in SSA countries who currently practice in the US. We estimated emigration proportions, year of US entry, years of practice before emigration, and length of time in the US. According to the 2011 AMA-PM, 10,819 physicians were born or trained in 28 SSA countries. Sixty-eight percent (n = 7,370) were SSA-trained, 20% (n = 2,126) were US-trained, and 12% (n = 1,323) were trained outside both SSA and the US. We estimated active physicians (age ≤70 years) to represent 96% (n = 10,377) of the total. Migration trends among SSA-trained physicians increased from 2002 to 2011 for all but one principal source country; the exception was South Africa whose physician migration to the US decreased by 8% (−156). The increase in last-decade migration was >50% in Nigeria (+1,113) and Ghana (+243), >100% in Ethiopia (+274), and >200% (+244) in Sudan. Liberia was the most affected by migration to the US with 77% (n = 175) of its estimated physicians in the 2011 AMA-PM. On average, SSA-trained physicians have been in the US for 18 years. They practiced for 6.5 years before US entry, and nearly half emigrated during the implementation years (1984–1999) of the structural adjustment programs.
Physician emigration from SSA to the US is increasing for most SSA source countries. Unless far-reaching policies are implemented by the US and SSA countries, the current emigration trends will persist, and the US will remain a leading destination for SSA physicians emigrating from the continent of greatest need.
Please see later in the article for the Editors' Summary
Editors' Summary
Population growth and aging and increasingly complex health care interventions, as well as existing policies and market forces, mean that many countries are facing a shortage of health care professionals. High-income countries are addressing this problem in part by encouraging the immigration of foreign health care professionals from low- and middle-income countries. In the US, for example, international medical graduates (IMGs) can secure visas and permanent residency by passing examinations provided by the Educational Commission of Foreign Medical Graduates and by agreeing to provide care in areas that are underserved by US physicians. Inevitably, the emigration of physicians from low- and middle-income countries undermines health service delivery in the emigrating physicians' country of origin because physician supply is already inadequate in those countries. Physician emigration from sub-Saharan Africa, which has only 2% of the global physician workforce but a quarter of the global burden of disease, is particularly worrying. Since 1970, as a result of large-scale emigration and limited medical education, there has been negligible or negative growth in the density of physicians in many countries in sub-Saharan Africa. In Liberia, for example, in 1973, there were 7.76 physicians per 100,000 people but by 2008 there were only 1.37 physicians per 100,000 people; in the US, there are 250 physicians per 100,000 people.
Why Was This Study Done?
Before policy proposals can be formulated to address global inequities in physician distribution, a clear picture of the patterns of physician emigration from resource-limited countries is needed. In this study, the researchers use data from the 2011 American Medical Association Physician Masterfile (AMA-PM) to investigate the “brain drain” of physicians from sub-Saharan Africa to the US. The AMA-PM collects annual demographic, academic, and professional data on all residents (physicians undergoing training in a medical specialty) and licensed physicians who practice in the US.
What Did the Researchers Do and Find?
The researchers used data from the World Health Organization (WHO) Global Health Workforce Statistics and graduation and residency data from the 2011 AMA-PM to estimate physician emigration rates from sub-Saharan African countries, year of US entry, years of service provided before emigration to the US, and length of time in the US. There were 10,819 physicians who were born or trained in 28 sub-Saharan African countries in the 2011 AMA-PM. By using a published analysis of the 2002 AMA-PM, the researchers estimated that US immigration among sub-Saharan African-trained physicians had increased over the past decade for all the countries examined except South Africa, where physician emigration had decreased by 8%. Overall, the number of sub-Saharan African IMGs in the US had increased by 38% since 2002. More than half of this increase was accounted for by Nigerian IMGs. Liberia was the country most affected by migration of its physicians to the US—77% of its estimated 226 physicians were in the 2011 AMA-PM. On average, sub-Saharan African IMGs had been in the US for 18 years and had practiced for 6.5 years before emigration. Finally, nearly half of the sub-Saharan African IMGs had migrated to US between 1984 and 1995, years during which structural adjustment programs, which resulted in deep cuts to public health care services, were implemented in developing countries by international financial institutions as conditions for refinancing.
What Do These Findings Mean?
Although the sub-Saharan African IMGs in the 2011 AMA-PM only represent about 1% of all the physicians and less than 5% of the IMGs in the AMA-PM, these findings reveal a major loss of physicians from sub-Saharan Africa. They also suggest that emigration of physicians from sub-Saharan Africa is a growing problem and is likely to continue unless job satisfaction for physicians is improved in their country of origin. Moreover, because the AMA-PM only lists physicians who qualify for a US residency position, more physicians may have moved from sub-Saharan Africa to the US than reported here and may be working in other jobs incommensurate with their medical degrees (“brain waste”). The researchers suggest that physician emigration from sub-Saharan Africa to the US reflects the complexities in the labor markets for health care professionals in both Africa and the US and can be seen as low- and middle-income nations subsidizing the education of physicians in high-income countries. Policy proposals to address global inequities in physician distribution will therefore need both to encourage the recruitment, training, and retention of health care professionals in resource-limited countries and to persuade high-income countries to train more home-grown physicians to meet the needs of their own populations.
Additional Information
Please access these websites via the online version of this summary at
The Foundation for Advancement of International Medical Education and Research is a non-profit foundation committed to improving world health through education that was established in 2000 by the Educational Commission for Foreign Medical Graduates
The Global Health Workforce Alliance is a partnership of national governments, civil society, international agencies, finance institutions, researchers, educators, and professional associations dedicated to identifying, implementing and advocating for solutions to the chronic global shortage of health care professionals (available in several languages)
Information on the American Medical Association Physician Masterfile and the providers of physician data lists is available via the American Medical Associations website
The World Health Organization (WHO) annual World Health Statistics reports present the most recent health statistics for the WHO Member States
The Medical Education Partnership Initiative is a US-sponsored initiative that supports medical education and research in sub-Saharan African institutions, aiming to increase the quantity, quality, and retention of graduates with specific skills addressing the health needs of their national populations
CapacityPlus is the USAID-funded global project uniquely focused on the health workforce needed to achieve the Millennium Development Goals
Seed Global Health cultivates the next generation of health professionals by allying medical and nursing volunteers with their peers in resource-limited settings
"America is Stealing the Worlds Doctors", a 2012 New York Times article by Matt McAllester, describes the personal experience of a young doctor who emigrated from Zambia to the US
Path to United States Practice Is Long Slog to Foreign Doctors, a 2013 New York Times article by Catherine Rampell, describes the hurdles that immigrant physicians face in practicing in the US
PMCID: PMC3775724  PMID: 24068894
18.  Predicting length of stay from an electronic patient record system: a primary total knee replacement example 
To investigate whether factors can be identified that significantly affect hospital length of stay from those available in an electronic patient record system, using primary total knee replacements as an example. To investigate whether a model can be produced to predict the length of stay based on these factors to help resource planning and patient expectations on their length of stay.
Data were extracted from the electronic patient record system for discharges from primary total knee operations from January 2007 to December 2011 (n = 2,130) at one UK hospital and analysed for their effect on length of stay using Mann-Whitney and Kruskal-Wallis tests for discrete data and Spearman’s correlation coefficient for continuous data. Models for predicting length of stay for primary total knee replacements were tested using the Poisson regression and the negative binomial modelling techniques.
Factors found to have a significant effect on length of stay were age, gender, consultant, discharge destination, deprivation and ethnicity. Applying a negative binomial model to these variables was successful. The model predicted the length of stay of those patients who stayed 4–6 days (~50% of admissions) with 75% accuracy within 2 days (model data). Overall, the model predicted the total days stayed over 5 years to be only 88 days more than actual, a 6.9% uplift (test data).
Valuable information can be found about length of stay from the analysis of variables easily extracted from an electronic patient record system. Models can be successfully created to help improve resource planning and from which a simple decision support system can be produced to help patient expectation on their length of stay.
PMCID: PMC3992140  PMID: 24708853
Length of stay; Regression analysis; Models, statistical; negative binomial; Total knee replacement; Computerized Medical Records; Hospital planning
19.  Hospital discharge decisions, health outcomes, and the use of unobserved information on case-mix severity. 
Health Services Research  1991;26(1):27-51.
Although implementation of the Medicare prospective payment system has been accompanied by significant decreases in hospital length of stay, the early discharge of some patients may lead to worse health outcomes, particularly if sufficient aftercare services following hospitalization are not available. This article develops an empirical model of the relationship between the choice of length of stay and patient outcome. The model incorporates information on the severity of a patient's medical condition known by the physician who chooses length of stay for a patient but generally not known by a researcher interested in the factors that affect length of stay and health outcome. Joint estimation of equations for length of stay and health outcome controls for unmeasured aspects of case severity that affect both variables. The ratio of nursing home beds to Medicare enrollees in the county is included as an exogenous variable in both equations to assess whether variation in nursing home bed availability is correlated with length of stay or health outcome. The model is estimated using billing data for Medicare patients admitted with congestive heart failure to New Jersey hospitals during 1982 and 1983. Two measures of outcome are used: (1) a discrete measure of survival time following admission, and (2) a categorical measure of whether or not the patient was discharged dead or died within six months after discharge. Empirical results show no evidence that longer lengths of stay for congestive heart failure patients lead to lower postadmission mortality. However, greater availability of nursing home beds may reduce length of stay and may shift the provision of terminal care away from a hospital setting. Therefore, policies to expand the nursing home bed supply may enable further decreases in hospital length of stay without deleterious effect on patient outcome.
PMCID: PMC1069809  PMID: 2016169
20.  The use of a standardized PCT-algorithm reduces costs in intensive care in septic patients - a DRG-based simulation model 
The management of bloodstream infections especially sepsis is a difficult task. An optimal antibiotic therapy (ABX) is paramount for success. Procalcitonin (PCT) is a well investigated biomarker that allows close monitoring of the infection and management of ABX. It has proven to be a cost-efficient diagnostic tool. In Diagnoses Related Groups (DRG) based reimbursement systems, hospitals get only a fixed amount of money for certain treatments. Thus it's very important to obtain an optimal balance of clinical treatment and resource consumption namely the length of stay in hospital and especially in the Intensive Care Unit (ICU). We investigated which economic effects an optimized PCT-based algorithm for antibiotic management could have.
Materials and methods
We collected inpatient episode data from 16 hospitals. These data contain administrative and clinical information such as length of stay, days in the ICU or diagnoses and procedures. From various RCTs and reviews there are different algorithms for the use of PCT to manage ABX published. Moreover RCTs and meta-analyses have proven possible savings in days of ABX (ABD) and length of stay in ICU (ICUD). As the meta-analyses use studies on different patient populations (pneumonia, sepsis, other bacterial infections), we undertook a short meta-analyses of 6 relevant studies investigating in sepsis or ventilator associated pneumonia (VAP). From this analyses we obtained savings in ABD and ICUD by calculating the weighted mean differences. Then we designed a new PCT-based algorithm using results from two very recent reviews. The algorithm contains evidence from several studies. From the patient data we calculated cost estimates using German National standard costing information for the German G-DRG system.
We developed a simulation model where the possible savings and the extra costs for (in average) 8 PCT tests due to our algorithm were brought into equation.
We calculated ABD savings of -4 days and ICUD reductions of -1.8 days. our algorithm contains recommendations for ABX onset (PCT ≥ 0.5 ng/ml), validation whether ABX is appropriate or not (Delta from day 2 to day 3 ≥ 30% indicates inappropriate ABX) and recommendations for discontinuing ABX (PCT ≤ 0.25 ng/ml).
We received 278, 264 episode datasets where we identified by computer-based selection 3, 263 cases with sepsis. After excluding cases with length of stay (LOS) too short to achieve the intended savings, we ended with 1, 312 cases with ICUD and 268 cases without ICUD. Average length of stay of ICU-patients was 27.7 ± 25.7 days and for Non-ICU patients 17.5 ± 14.6 days respectively. ICU patients had an average of 8.8 ± 8.7 ICUD.
After applying the simulation model on this population we calculated possible savings of € -1, 163, 000 for ICU-patients and € -36, 512 for Non-ICU patients.
Our findings concerning the savings from the reduction of ABD are consistent with other publications. Savings ICUD had never been economically evaluated so far. our algorithm is able to possibly set a new standard in PCT-based ABX. However the findings are based on data modelling. The algorithm will be implemented in 5-10 hospitals in 2012 and effects in clinical reality measured 6 months after implementation.
Managing sepsis with daily monitoring of PCT using our refined algorithm is suitable to save substantial costs in hospitals. Implementation in clinical routine settings will show how much of the calculated effect will be achieved in reality.
PMCID: PMC3351898  PMID: 22112361
21.  Computer-generated informational messages directed to physicians: effect on length of hospital stay. 
OBJECTIVE: With the advent of hospital payment by diagnosis-related group (DRG), length of stay (LOS) has become a major issue in hospital efforts to control costs. Because the Columbia-Presbyterian Medical Center (CPMC) has had above-average LOSs for many DRGs, the authors tested the hypothesis that a computer-generated informational message directed to physicians would shorten LOS. DESIGN: Randomized clinical trial with the patient as the unit of randomization. SETTING AND STUDY POPULATION: From June 1991 to April 1993, at CPMC in New York, 7,109 patient admissions were randomly assigned to an intervention (informational message) group and 6,990 to a control (no message) group. INTERVENTION: A message giving the average LOS for the patient's admission or provisional DRG, as assigned by hospital utilization review, and the current LOS, in days, was included in the main menu for review of test results in the hospital's clinical information system, available at all nursing stations in the hospital. MAIN OUTCOME MEASURE: Hospital LOS. RESULTS: The median LOS for study patients was 7 days. After adjustment for covariates including age, sex, payor, patient care unit, and time trends, the mean LOS in the intervention group was 3.2% shorter than that in the control group (p = 0.022). CONCLUSION: Computer-generated patient-specific LOS information directed to physicians was associated with a reduction in hospital LOS.
PMCID: PMC116237  PMID: 7895137
22.  Evaluation of the impact of Medicare and Medicaid prospective payment on utilization of Philadelphia area hospitals. 
Health Services Research  1986;21(4):529-546.
The article evaluates the impact of Medicare and Medicaid DRG prospective payment on utilization in Philadelphia area hospitals. These hospitals began a combined Medicare-Medicaid DRG prospective payment at the same time after a common cost-based reimbursement history. Particular attention is paid to the hospital-driven as opposed to physician-driven explanations of declining inpatient utilization. The evaluation of the Tax Equity and Fiscal Responsibility Act (TEFRA) and Diagnosis-Related Group (DRG) interventions uses an ARIMA model that removes both seasonal and autoregressive effects. Both TEFRA and the DRG payment system produced significant reductions in average length of stay, total hospital days, and hospital occupancy rates. Neither, however, had a significant effect on admissions. Hospitals with a higher proportion of Medicare and Medicaid discharges reduced their average length of stay more than other facilities. Hospitals with a higher proportion of outpatient visits to inpatient admissions also reduced inpatient length of stay more. Hospitals with higher than expected overall admissions after the introduction of the DRG program tended to have lower than expected average lengths of stay. The results lend support to the "hospital-driven" interpretation of declines in average length of stay. They fail to support the contention that the DRG system will produce automatic counteracting increases in admissions in the system as a whole.
PMCID: PMC1068970  PMID: 3095267
23.  Predicting Judged Quality of Patient Care in General Hospitals 
Health Services Research  1967;2(1):26-33.
Cleveland physicians with in-depth knowledge about hospitals in their community were asked to rank general hospitals, on a 5-point scale, in an attempt to evaluate quality of patient care. Nine physicians showed reasonable agreement in their judgments. In a broader sample, six additional physicians ranked the same hospitals, to provide a check on overall inter-rater reliability. Average hospital rank assigned by the first group correlated +.89 with average rank for the broader sample, indicating good criterion reliability.
Later, published data about the hospitals, such as number of residency programs offered, number of beds, and average length of stay, were correlated with the rankings provided by all 15 physicians. Resulting correlations were substantial (e.g., +.86 for number of approved residency programs), and the best combination of three variables predicted the criterion with a multiple correlation of +.94. Cross validation in four other metropolitan areas in Ohio and Pennsylvania, where 75 physician raters provided ratings of 36 general hospitals, showed that the three variables isolated for the Cleveland sample predicted the overall quality of patient care in the four other communities, with a correlation of +.82.
The study was made by a team of physicians and psychologists as part of a larger investigation of practicing physicians and the doctor-patient relationship. The work reported here was directed at establishing ratings of the hospitals in which these physicians work and were trained.
PMCID: PMC1065733
24.  Benchmarking and reducing length of stay in Dutch hospitals 
To assess the development of and variation in lengths of stay in Dutch hospitals and to determine the potential reduction in hospital days if all Dutch hospitals would have an average length of stay equal to that of benchmark hospitals.
The potential reduction was calculated using data obtained from 69 hospitals that participated in the National Medical Registration (LMR). For each hospital, the average length of stay was adjusted for differences in type of admission (clinical or day-care admission) and case mix (age, diagnosis and procedure). We calculated the number of hospital days that theoretically could be saved by (i) counting unnecessary clinical admissions as day cases whenever possible, and (ii) treating all remaining clinical patients with a length of stay equal to the benchmark (15th percentile length of stay hospital).
The average (mean) length of stay in Dutch hospitals decreased from 14 days in 1980 to 7 days in 2006. In 2006 more than 80% of all hospitals reached an average length of stay shorter than the 15th percentile hospital in the year 2000. In 2006 the mean length of stay ranged from 5.1 to 8.7 days. If the average length of stay of the 15th percentile hospital in 2006 is identified as the standard that other hospitals can achieve, a 14% reduction of hospital days can be attained. This percentage varied substantially across medical specialties. Extrapolating the potential reduction of hospital days of the 69 hospitals to all 98 Dutch hospitals yielded a total savings of 1.8 million hospital days (2006). The average length of stay in Dutch hospitals if all hospitals were able to treat their patients as the 15th percentile hospital would be 6 days and the number of day cases would increase by 13%.
Hospitals in the Netherlands vary substantially in case mix adjusted length of stay. Benchmarking – using the method presented – shows the potential for efficiency improvement which can be realized by decreasing inputs (e.g. available beds for inpatient care). Future research should focus on the effect of length of stay reduction programs on outputs such as quality of care.
PMCID: PMC2582034  PMID: 18950476
25.  Patient Outcomes with Teaching Versus Nonteaching Healthcare: A Systematic Review 
PLoS Medicine  2006;3(9):e341.
Extensive debate exists in the healthcare community over whether outcomes of medical care at teaching hospitals and other healthcare units are better or worse than those at the respective nonteaching ones. Thus, our goal was to systematically evaluate the evidence pertaining to this question.
Methods and Findings
We reviewed all studies that compared teaching versus nonteaching healthcare structures for mortality or any other patient outcome, regardless of health condition. Studies were retrieved from PubMed, contact with experts, and literature cross-referencing. Data were extracted on setting, patients, data sources, author affiliations, definition of compared groups, types of diagnoses considered, adjusting covariates, and estimates of effect for mortality and for each other outcome. Overall, 132 eligible studies were identified, including 93 on mortality and 61 on other eligible outcomes (22 addressed both). Synthesis of the available adjusted estimates on mortality yielded a summary relative risk of 0.96 (95% confidence interval [CI], 0.93–1.00) for teaching versus nonteaching healthcare structures and 1.04 (95% CI, 0.99–1.10) for minor teaching versus nonteaching ones. There was considerable heterogeneity between studies (I2 = 72% for the main analysis). Results were similar in studies using clinical and those using administrative databases. No differences were seen in the 14 studies fully adjusting for volume/experience, severity, and comorbidity (relative risk 1.01). Smaller studies did not differ in their results from larger studies. Differences were seen for some diagnoses (e.g., significantly better survival for breast cancer and cerebrovascular accidents in teaching hospitals and significantly better survival from cholecystectomy in nonteaching hospitals), but these were small in magnitude. Other outcomes were diverse, but typically teaching healthcare structures did not do better than nonteaching ones.
The available data are limited by their nonrandomized design, but overall they do not suggest that a healthcare facility's teaching status on its own markedly improves or worsens patient outcomes. Differences for specific diseases cannot be excluded, but are likely to be small.
Published data do not suggest that the teaching status of a hospital or other healthcare facility alone influences the outcome of patients treated in that facility.
Editors' Summary
When people need medical treatment they may be given it in a “teaching hospital.” This is a place where student doctors and other trainee healthcare workers are receiving part of their education. They help give some of the treatment that patients receive. Teaching hospitals are usually large establishments and in most countries they are regarded as being among the very best hospitals available, with leading physicians and surgeons among the staff. It is usually assumed that patients who are being treated in a teaching hospital are lucky, because they are getting such high-quality healthcare. However, it has sometimes been suggested that, because some of the people involved in their care are still in training, the patients may face higher risks than those who are in nonteaching hospitals.
Why Was This Study Done?
The researchers wanted to find out which patients do best after treatment—those who were treated in teaching hospitals or those who were in nonteaching hospitals. This is a difficult issue to study. The most reliable way of comparing two types of treatment would be to decide at random which treatment each patient should receive. (For more on this see the link below for “randomized controlled trials.”) In practice, it would be difficult to set up a study where the decision on which hospital a patient should go to was made at random. One problem is that, because of the high reputation of teaching hospitals, the patients whose condition is the most serious are often sent there, with other patients going to nonteaching hospitals. It would not be a fair test to compare the “outcome” for the most seriously ill patients with the outcome for those whose condition was less serious.
What Did the Researchers Do and Find?
The researchers conducted a thorough search for studies that had already been done, which met criteria which the researchers had specified in advance. This type of research is called a “systematic review.” They found 132 studies that had compared the outcomes of patients in teaching or nonteaching hospitals. None of these studies was a trial. (They were “observational studies” where researchers had gathered information on what was already taking place, rather than setting up an experiment.) However, in 14 studies, extensive allowances had been made for differences in such factors as the severity of the patients' condition, and whether or not they had more than one type of illness when they were treated. There was a great deal of variability in the results between the studies but, overall, there was no major difference in the effectiveness of treatment provided by the two types of hospital.
What Do These Findings Mean?
There is no evidence to support that it is better to be given treatment in a teaching or a nonteaching hospital. The authors do note that a limitation in their analysis is that it was based on studies that were not randomized controlled trials. They also raise the question that differences might be found if considering specific diseases one by one, rather than putting information on all conditions together. However, they believe that any such difference would be small. Their findings will be useful in the continuing debate on the most effective ways to train doctors, while at the same time providing the best possible care for patients.
Additional Information.
Please access these Web sites via the online version of this summary at
Wikipedia entry on teaching hospitals (note: Wikipedia is a free online encyclopedia that anyone can edit)
Information on randomized clinical trials from the US National Institutes of Health
A definition of systematic reviews from the Cochrane Collaboration, an organization which produces systematic reviews
All of the above include links to other Web sites where more detailed information can be found.
PMCID: PMC1564172  PMID: 16968119

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