FASStR: a framework for ensuring high-quality operational metrics in health care.

OBJECTIVES: Poorly defined measurement impairs interinstitutional comparison, interpretation of results, and process improvement in health care operations. We sought to develop a unifying framework that could be used by administrators, practitioners, and investigators to help define and document operational performance measures that are comparable and reproducible. STUDY DESIGN: Retrospective analysis. METHODS: Health care operations and clinical investigators used an iterative process consisting of (1) literature review, (2) expert assessment and collaborative design, and (3) end-user feedback. We sampled the literature from the medical, health systems research, and health care operations (business and engineering) disciplines to assemble a representative sample of studies in which outpatient health care performance metrics were used to describe the primary or secondary outcome of the research. RESULTS: We identified 2 primary deficiencies in outpatient performance metric definitions: incompletion and inconsistency. From our review of performance metrics, we propose the FASStR framework for the Focus, Activity, Statistic, Scale type, and Reference dimensions of a performance metric. The FASStR framework is a method by which performance metrics can be developed and examined from a multidimensional perspective to evaluate their comprehensiveness and clarity. The framework was tested and revised in an iterative process with both practitioners and investigators. CONCLUSIONS: The FASStR framework can guide the design, development, and implementation of operational metrics in outpatient health care settings. Further, this framework can assist investigators in the evaluation of the metrics that they are using. Overall, the FASStR framework can result in clearer, more consistent use and evaluation of outpatient performance metrics.

Designing appointment scheduling systems for ambulatory care services.

The current climate in the health care industry demands efficiency and patient satisfaction in medical care delivery. These two demands intersect in scheduling of ambulatory care visits. This paper uses patient and doctor-related measures to assess ambulatory care performance and investigates the interactions among appointment system elements and patient panel characteristics. Analysis methodology involves simulation modeling of clinic sessions where empirical data forms the basis of model design and assumptions. Results indicate that patient sequencing has a greater effect on ambulatory care performance than the choice of an appointment rule, and that panel characteristics such as walk-ins, no-shows, punctuality and overall session volume, influence the effectiveness of appointment systems.