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PubMed · 9917472

Administrative data for quality improvement.

Abstract

This article discusses the use of administrative data for quality improvement in perinatal and neonatal medicine. We review the nature of administrative data and focus on hospital discharge abstract data as the primary source of hospital- and community-based assessments. Although discharge abstract data lack the richness of primary data, these data are the most accessible comparative data source for examining all patients admitted to a hospital. When aggregated to the state level as occurs in more than 30 states, hospital discharge data reflects hospital utilization and outcomes for an entire geographic population at the state and community level. This article reviews some of the weaknesses of administrative data and then focuses how these data can be used for hospital- and community-based assessment of perinatal care citing as examples the measures of perinatal process and outcome used by the National Perinatal Information Center in its Quality/Efficiency Reports for member hospitals and a study of perinatal high-risk care in the State of Florida. The use of discharge abstract data for performance measurement at either the hospital or the system level requires a thorough understanding of how to select a patient group, its characteristics, the intervention, and the outcomes relevant to that patient group. In the perinatal arena, the National Perinatal Information Center has selected and presents those measures that rely on data items shown to be the most reliable based on validity studies and clinician opinion, delineation of the intervention, and the measurement of what occurred. As hospitals respond to the recent pressures of the Joint Commission on Accreditation of Healthcare Organizations and other quality assurance entities, the accuracy of the discharge data will improve. With accepted caution, these data sets are invaluable to researchers studying comparative populations over time or across large geographic areas.

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BibTeXRIS

R M Schwartz, D E Gagnon, J H Muri, Q R Zhao, R Kellogg. 1999. Administrative data for quality improvement.. https://pubmed.ncbi.nlm.nih.gov/9917472/

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