***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: OBJECTIVE To assess the impact of diverse  continuing medical education ( CME ) interventions on  physician performance and health care outcomes .  DATA SOURCES Using continuing medical education and related phrases , we performed regular search es of the indexed literature ( MEDLINE , Social Science Index , the National Technical Information Service , and Educational Research Information Clearinghouse ) from 1975 through 1991 . In addition , for these years , we used manual search es , key informants , and requests to authors to locate other indexed articles and the nonindexed literature of adult and continuing professional education . STUDY SELECTION From the result ing data base we selected studies that met the following criteria : r and omized controlled trials ; educational programs , activities , or other interventions ; studies that included 50 % or more physicians ; follow-up assessment s of at least 75 % of study subjects ; and objective assessment s of either physician performance or health care outcomes . DATA EXTRACTION Studies were review ed for data related to physician specialty and setting . Continuing medical education interventions were classified by their mode(s ) of activity as being predisposing , enabling , or facilitating . Using the statistical tests supplied by the original investigators , physician performance outcomes and patient outcomes were classified as positive , negative , or inconclusive . DATA SYNTHESIS We located 777 CME studies , of which 50 met all criteria . Thirty-two of these analyzed physician performance ; seven evaluated patient outcomes ; 11 examined both measures . The majority of the 43 studies of physician performance showed positive results in some important measures of re source utilization , counseling strategies , and preventive medicine . Of the 18 studies of health care outcomes , eight demonstrated positive changes in patients ' health care outcomes . CONCLUSION Broadly defined CME interventions using practice -enabling or reinforcing strategies consistently improve physician performance and , in some instances , health care outcomes Computers are steadily being incorporated in clinical practice . We conducted a nonr and omised , controlled , prospect i ve trial of electronic messages design ed to enhance adherence to clinical practice guidelines . We studied 126 physicians and nurse practitioners who used electronic medical records when caring for 349 patients with HIV infection in a primary care practice . We analysed the response times of clinicians to the situations that triggered alerts and reminders , the number of ambulatory visits , and hospitalisation . The median response times to 303 alerts in the intervention group and 388 alerts in the control group were 11 and 52 days ( p < 0.0001 ) , respectively . The median response time to 432 reminders in the intervention group was 114 days and that for 360 reminders in the control group was over 500 days ( p < 0.0001 ) . There was no effect on visits to the primary care practice . There was , however , a significant increase in the rate of visits outside the primary care practice ( p = 0.02 ) , which is explained by the increased frequency of visits to ophthalmologists . There were no differences in admission rates ( p = 0.47 ) , in admissions for pneumocystosis ( p = 0.09 ) , in visits to the emergency ward ( p = 0.24 ) , or in survival ( p = 0.19 ) . We conclude that the electronic medical record was effective in helping clinicians adhere to practice guidelines PURPOSE Clinical guidelines are design ed to assist in the management of specific diseases ; however , these guidelines are often neglected in the delivery of care . The purpose of this study was to determine whether clinician use of an clinical practice guideline would increase in response to having , at the patient visit , a decision support system based on a practice guideline that generates a customized management protocol for the individual patient using data from the patient 's electronic medical record . SUBJECTS AND METHODS In a 6-month controlled trial at a primary care clinic , 58 primary care clinicians were r and omized to receive either a special encounter form with the computer-generated guideline recommendations or a st and ard encounter form . The effect of computer-generated advice on clinician behavior was measured as rate of compliance with guideline recommendations . Data from 30 clinicians were analyzed ; data from 28 clinicians were excluded because these clinicians did not meet predefined criteria for minimum exposure to diabetic patient care . RESULTS Availability of patient management recommendations generated by the decision support system result ed in a two-fold increase in clinician compliance with care guidelines for diabetes mellitus ( P = 0.01 ) . Median compliance for the group receiving the recommendations was 32.0 % versus 15.6 % for the control group . CONCLUSION Decision support based on a clinical practice guideline is an effective tool for assisting clinicians in the management of diabetic patients . This decision support system provides a model for how a clinical practice guideline can be integrated into the care process by computer to assist clinicians in managing a specific disease through helping them comply with care st and ards . Use of decision support systems based on clinical practice guidelines could ultimately improve the quality of medical care A r and omized controlled trial with 76 physicians in 16 community hospitals evaluated audit and feedback and local opinion leader education as methods of encouraging compliance with a guideline for the management of women with a previous cesarean section . The guideline recommended clinical actions to increase trial of labor and vaginal birth rates . Charts for all 3552 cases in the study groups were audited . After 24 months the trial of labor and vaginal birth rates in the audit and feedback group were no different from those in the control group , but rates were 46 % and 85 % higher , respectively , among physicians educated by an opinion leader . Duration of hospital stay was lower in the opinion leader education group than in the other two groups . The overall cesarean section rate was reduced only in the opinion leader education group . There were no adverse clinical outcomes attributable to the interventions . The use of opinion leaders improved the quality of care Currently , considerable enthusiasm exists for practice guideline development . However , little is known about their real effect , and substantial doubt exists about whether guidelines can actually decrease health care costs and improve quality of care [ 1 , 2 ] . Physicians have expressed reservations about practice guidelines , including concerns that they may be misapplied or even abused [ 3 ] , and the specter of cookbook medicine is often raised [ 2 ] . Because few controlled interventional trials using guidelines have been done , little is known about their actual performance in clinical practice and their acceptance by physicians . In addition , some have recommended that practice guidelines be used to certify and license physicians and to make decisions about which medical services to fund [ 1 ] . Thus , it is important to underst and physicians ' responses to guidelines and how to judge their usefulness in clinical practice . We hypothesized that the reasons for the failure of physicians to comply with the recommendations of a length-of-hospitalization practice guideline could be multifactorial . Noncompliance of physicians could be related to physician attitudes toward the guideline leading to rejection , to limitations of the guideline itself or its implementation strategy , to inefficiencies in the hospital or health care delivery system , or to differences in the patient 's clinical status . Although these and other factors might all contribute to apparent noncompliance of physicians , improvement in guideline performance and in physician compliance would be dependent on addressing the true causes rather than on simply assuming that the reason is physician resistance . We retrospectively analyzed the results from a successfully implemented practice guideline  that sought to reduce hospital length of stay for patients admitted with chest pain [ 4 ] in order to determine the ways in which that effort might have been improved . The guideline recommended a 2-day length of hospital stay for carefully selected low-risk patients with chest pain . The guideline had previously been vali date d and shown to be relatively safe [ 5 ] . Attending physicians were given risk information concurrently by utilization-management nurses through the placement of letters on the chart and by telephone calls from utilization-management physician advisors . In a controlled interventional trial [ 4 ] , the guideline decreased length of stay and hospital costs and did not have an adverse effect on patient morbidity , mortality , health status , or satisfaction . The statistically significant total reductions in length of stay and total cost reductions of approximately $ 1397 per low-risk patient were achieved by improving physician compliance with the guideline from 50 % during control months to 69 % during intervention months . We determined the reasons why the remaining 31 % of low-risk patients were not discharged at hospital day 2 according to the chest pain guideline recommendations and why patients who were truly at high risk were misclassified as being at low risk . Methods Study Design The study was a retrospective analysis of a prospect i ve , controlled interventional trial [ 4 ] . Institutional Characteristics The study was done at Cedars-Sinai Medical Center , a large university-affiliated community teaching hospital in Los Angeles . Most patients were cared for by private practitioners . Although a coronary care unit director , cardiology faculty , cardiology fellows , medical housestaff , and medical students participated in the clinical care of many of the study patients , private practitioners had the ultimate responsibility for patient care decisions for most study patients , including the decision to discharge a patient from the hospital . Patient Population The prospect i ve , controlled interventional trial was done between 1 September 1991 and 31 August 1992 . Physicians were informed of risk information and guideline recommendations on an alternating month basis . The retrospective analysis done for the current study included patients from all interventional months ( October 1991 , December 1991 , February 1992 , April 1992 , June 1992 , and August 1992 ) . Patients were eligible for enrollment in the study if they were at least 30 years of age , presented with a chief symptom of chest pain , and were admitted to a monitored bed in the cardiac intensive care unit or the cardiac observation unit . Patients were enrolled in the study if they were concurrently classified as being at low risk for in-hospital complications according to our previously described practice guideline [ 4 ] or if they were identified through our hospital information system for retrospective review of all eligible patients admitted during intervention months . The guideline prescribed a 2-day length of hospital stay for patients classified as being at low risk . Noncompliance of physicians with the guideline was defined as a 3-day or greater length of stay . Analysis was by intention to treat . Intervention Before the study , all attending physicians received a letter describing the study and information about the chest pain practice guideline . The guideline [ 4 ] recommended a 2-day length of stay for patients hospitalized with chest pain who had none of the following conditions 24 hours after hospitalization : 1 ) acute myocardial infa rct ion ; 2 ) recurrent chest pain ; 3 ) previous cardiac intervention ; 4 ) planned cardiac intervention ; 5 ) previous complication ; 6 ) ongoing intervention ; or 7 ) unstable comorbid condition . All seven elements describing low-risk status were explicitly defined . Physicians caring for patients classified as low-risk received concurrent , personalized , written , and physician-to-physician feedback over the telephone about the guideline recommendations . Both types of feedback were delivered to physicians using the following structured format : Your patient ( Patient Name ) may be at low-risk for serious in-hospital complications . In fact , approximately 98 % of patients similar to your patient suffered no serious in-hospital complications after 2 days of hospitalization . If your patient continues to have an uncomplicated hospital course without chest pain , please consider whether a 2 day length of stay is appropriate for your patient . If further diagnostic testing is absolutely required prior to discharge , please let me know if we can help facilitate any test for you . Only you as the primary physician can determine the most appropriate length of stay for your patient . Thank you . No incentives were added or disincentives removed to enhance physician compliance with the guidelines . Specifically , no financial incentives were offered for complying with guideline recommendations , nor were any sanctions used against physicians who rejected the guidelines . Inclusion Criteria All patients eligible for enrollment in the study during intervention months who were classified at 24 hours as being at low risk by either concurrent utilization-management review or by retrospective review who were discharged 3 or more days after admission ( our definition of noncompliance of physicians ) were included in the analysis . Sources of Information Decisions about the possible cause or causes of noncompliance of physicians were based on review of the medical records and on the utilization-management physician-to-physician interaction sheets . Analytic Framework Patients were retrospectively assigned by an experienced research nurse to one of the following five general categories of physician noncompliance on the basis of a structured explicit review of medical records and of the utilization-management physician-to-physician interaction sheets ( the combination was considered the criterion st and ard ) . 1 . Noncompliance of Physicians Based on Guideline Implementation Problems a ) False-positive result : those patients misclassified as being at low risk during concurrent utilization-management review who after structured explicit review ( the criterion st and ard ) were considered high risk and , therefore , should not have been discharged according to the guideline 's recommendation . b ) False-negative result : 1 ) those patients falsely classified as being at high risk and , therefore , the physician was not contacted ; or 2 ) those patients not identified by utilization-management nurses as being at low risk but , instead , were identified retrospectively using the hospital information system and from retrospective structured explicit review ( that is , patients not enrolled in the study despite meeting eligibility requirements ) . 2 . Noncompliance of Physicians Based on Health Care System Inefficiencies Patients correctly categorized as being at low risk whose physician agreed to discharge them but because of health care system inefficiency were not discharged before day 3 . The delay tool [ 6 ] was used for the abstract ion and categorization of inefficiency . Examples of delays included waiting for tests , procedures , or results ; social issues ( for example , waiting for nursing home placement ) ; waiting for consultation ; and patient refusal . 3 . Noncompliance of Physicians Based on Changes in Patient Clinical Status between 24 and 48 Hours Patients correctly classified at 24 hours as being at low risk 
    Output:
    
Because research ers believe that 70 % of disease is preventable ( 6 , 7 ) , effective implementation of preventive care guidelines can lead to even greater improvements in patient care than the introduction of some new technologies .
Additional benefits , including reductions in mortality , morbidity , and suffering , could accrue from increasing the rates of provision of other recommended preventive care procedures ( 1 , 7 ) .