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Background Assessing care continuity is important in evaluating the impact of health care reform and changes to health care delivery. Multiple measures of care continuity have been developed for use with claims data. Objective This study examined whether alternative continuity measures provide distinct assessments of coordination within pre-defined episodes of care. Research Design and Subjects Retrospective cohort study using 2008–9 claims files for a national 5% sample of beneficiaries with congestive heart failure, chronic obstructive pulmonary disease, and diabetes mellitus. Measures Correlation among four measures of care continuity—the Bice-Boxerman Continuity of Care Index, Herfindahl Index, usual provider of care, and Sequential Continuity of Care Index—derived at the provider- and practice-levels. Results Across the three conditions, results on four claims-based care coordination measures were highly correlated at the provider level (Pearson correlation coefficient r = 0.87 to 0.98) and practice level (r = 0.75 to 0.98). Correlation of the results was also high for the same measures between the provider and practice levels (r = 0.65 to 0.92). Conclusion Claims-based care continuity measures are all highly correlated with one another within episodes of care.

Key features in the success of the system included use of dedicated senior staff for Fast Track patients, and quarantining of clinical resources. The ED aiming to improve their waiting times and throughput should consider using complexity as a key criterion for triaging patients into separate streams. A low-complexity patient stream in the ED provides an ideal focus for advanced nursing practice.

The current evidence base is inadequate to inform providers and policymakers about the most effective strategies for managing or allocating scarce resources during mass casualty events. Consensus on methodological standards that encompass a range of study designs is needed to guide future research and strengthen the evidence base. Evidentiary standards should be developed to promote consensus interpretations of the evidence supporting individual strategies.

Despite widespread enthusiasm about the potential impact of new investments in comparative effectiveness research, recent history suggests that scientific evidence may be slow to change clinical practice. Reflecting on studies conducted over the past decade, we identify five causes that underlie the failure of many comparative effectiveness studies to alter patient care. These are financial incentives, such as fee-for-service payment, that may militate against the adoption of new clinical practices; ambiguity of study results that hamper decision making; cognitive biases in the interpretation of new information; failure of the research to address the needs of end users; and limited use of decision support by patients and clinicians. Policies that encourage the development of consensus objectives, methods, and evidentiary standards before studies get under way and that provide strong incentives for patients and providers to use resources efficiently may help overcome at least some of these barriers and enable comparative effectiveness results to alter medical practice more quickly.