Errors today and errors tomorrow.
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Biomedical subjects
Publications and source records attributed to Donald M Berwick.
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Health care is rich in evidence-based innovations, yet even when such innovations are implemented successfully in one location, they often disseminate slowly-if at all. Diffusion of innovations is a major challenge in all industries including health care. This article examines the theory and research on the dissemination of innovations and suggests applications of that theory to health care. It explores in detail 3 clusters of influence on the rate of diffusion of innovations within an organization: the perceptions of the innovation, the characteristics of the individuals who may adopt the change, and contextual and managerial factors within the organization. This theory makes plausible at least 7 recommendations for health care executives who want to accelerate the rate of diffusion of innovations within their organizations: find sound innovations, find and support "innovators," invest in "early adopters," make early adopter activity observable, trust and enable reinvention, create slack for change, and lead by example.
Delay of care is a persistent and undesirable feature of current health care systems. Although delay seems to be inevitable and linked to resource limitations, it often is neither. Rather, it is usually the result of unplanned, irrational scheduling and resource allocation. Application of queuing theory and principles of industrial engineering, adapted appropriately to clinical settings, can reduce delay substantially, even in small practices, without requiring additional resources. One model, sometimes referred to as advanced access, has increasingly been shown to reduce waiting times in primary care. The core principle of advanced access is that patients calling to schedule a physician visit are offered an appointment the same day. Advanced access is not sustainable if patient demand for appointments is permanently greater than physician capacity to offer appointments. Six elements of advanced access are important in its application balancing supply and demand, reducing backlog, reducing the variety of appointment types, developing contingency plans for unusual circumstances, working to adjust demand profiles, and increasing the availability of bottleneck resources. Although these principles are powerful, they are counter to deeply held beliefs and established practices in health care organizations. Adopting these principles requires strong leadership investment and support.
BACKGROUND: Health care organizations are increasingly adopting multiorganizational collaborative approaches to quality improvement. Collaboratives have been conducted in many countries. There are large variations in the way collaboratives are structured and run, but there is no widely accepted framework for describing the components of collaboratives. Thus, it is difficult to study which approaches are most effective. METHOD: The authors conducted semistructured interviews with 15 leaders of collaboratives to ascertain the common components of collaboratives and identify variations in the ways these components are implemented. RESULTS: The study identified seven features of collaboratives that the leaders interviewed thought were critical determinants of how effective the collaboratives were: sponsorship, topic, ideas for improvements, participants, senior leadership support, preliminary work and learning, and strategies for learning about and making improvements. For example, every interviewee mentioned that having participants collect data, perform audit work, or analyze the system they were in before the collaboration started was important to understanding their organization and the nature of the problems they had and to developing baseline data for later comparison. The authors describe variations in how these features have been implemented and possible functions of these features. CONCLUSION: Systematically studying the impact of variations in the seven key features of collaboratives could yield important information about their role and impact.
BACKGROUND: Variability in the demand for any service is a significant barrier to efficient distribution of limited resources. In health care, demand is often highly variable and access may be limited when peaks cannot be accommodated in a downsized care delivery system. Intensive care units may frequently present bottlenecks to patient flow, and saturation of these services limits a hospital's responsiveness to new emergencies. METHODS: Over a 1-yr period, information was collected prospectively on all requests for admission to the intensive care unit of a large, urban children's hospital. Data included the nature of each request, as well as each patient's final disposition. The daily variability of requests was then analyzed and related to the unit's ability to accommodate new admissions. RESULTS: Day-to-day demand for intensive care services was extremely variable. This variability was particularly high among patients undergoing scheduled surgical procedures, with variability of scheduled admissions exceeding that of emergencies. Peaks of demand were associated with diversion of patients both within the hospital (to off-service care sites) and to other institutions (ambulance diversions). Although emergency requests for admission outnumbered scheduled requests, diversion from the intensive care unit was better correlated with scheduled caseload (r = 0.542, P < 0.001) than with unscheduled volume (r = 0.255, P < 0.001). During the busiest periods, nearly 70% of all diversions were associated with variability in the scheduled caseload. CONCLUSIONS: Variability in scheduled surgical caseload represents a potentially reducible source of stress on intensive care units in hospitals and throughout the healthcare delivery system generally. When uncontrolled, variability limits access to care and impairs overall responsiveness to emergencies.
BACKGROUND: Measurement is necessary but not sufficient for quality improvement. Because the purpose of the national quality measurement and reporting system (NQMRS) is to improve quality, a discussion of the link between measurement and improvement is critical for ensuring an appropriate system design. OBJECTIVES: To classify approaches to the use of measurement in improvement into two different--although linked and potentially synergistic--agendas, or "pathways." To discuss the barriers encountered in each of these pathways and identify steps needed to motivate improvement in both pathways. RESEARCH DESIGN: Descriptive, conceptual discussion. FINDINGS: The barriers to the use of information to motivate change include, in Pathway I (selection), the lack of skill, knowledge, and motivation on the part of those who could drive change by using data to choose from among competing providers, and, in Pathway II (change in care delivery), the deficiencies in organizational and professional capacity in health care to lead change and improvement itself. CONCLUSIONS: Neither the dynamics of selection nor the dynamics of improvement work reliably today. The barriers are not just in the lack of uniform, simple, and reliable measurements, they also include a lack of capacity among the organizations and individuals acting on both pathways.
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Most people in developed countries will live with a serious, eventually fatal, chronic condition for months or years before dying; yet, the delivery of health care services has only just recently begun adapting to this reality. Quality improvement methods have been effective in helping clinical services to make substantial changes quickly. Quality improvement requires stating an aim, measuring success, and testing possible improvements. The testing of changes requires a clinical team to Plan, Do, Study, and Act on new insights (the "PDSA cycle"). Repeated PDSA cycles generate deep understanding of complex systems and make sustainable improvements rapidly. This paper discusses a composite case study in a nursing home setting, which builds on experience with multisite collaborative efforts and introduces quality improvement methods in the context of end-of-life care.
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Fifteen months after releasing its report on patient safety (To Err Is Human), the Institute of Medicine released Crossing the Quality Chasm. Although less sensational than the patient safety report, the Quality Chasm report is more comprehensive and, in the long run, more important. It calls for improvements in six dimensions of health care performance: safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity; and it asserts that those improvements cannot be achieved within the constraints of the existing system of care. It provides a rationale and a framework for the redesign of the U.S. health care system at four levels: patients' experiences; the "microsystems" that actually give care; the organizations that house and support microsystems; and the environment of laws, rules, payment, accreditation, and professional training that shape organizational action.
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New patient safety standards from JCAHO that require hospitals to disclose to patients all unexpected outcomes of care took effect 1 July 2001. In an early 2002 survey of risk managers at a nationally representative sample of hospitals, the vast majority reported that their hospital's practice was to disclose harm at least some of the time, although only one-third of hospitals actually had board-approved policies in place. More than half of respondents reported that they would always disclose a death or serious injury, but when presented with actual clinical scenarios, respondents were much less likely to disclose preventable harms than to disclose nonpreventable harms of comparable severity. Reluctance to disclose preventable harms was twice as likely to occur at hospitals having major concerns about the malpractice implications of disclosure.