Using administrative databases to evaluate the quality of medical care: A conceptual framework
AbstractHealth care is consuming an ever larger share of national resources in the United States. Measures to contain costs and evidence of unexplained variation in patient outcomes have led to concern about inadequacy in the quality of health care. As a measure of quality, the evaluation of hospitals through analysis of their discharge databases has been suggested because of the scope and economy offered by this methodology. However, the value of the information obtained through these analyses has been questioned because of the inadequacy of the clinical data contained in administrative databases and the resultant inability to control accurately for patient variation. We suggest, however, that the major shortcoming of prior attempts to use large databases to perform across-facility evaluation has resulted from the lack of a conceptual framework to guide the analysis. We propose a framework which identifies component areas and clarifies the underlying assumptions of the analytic process. For each area, criteria are identified which will maximize the validity of the results. Hospitals identified as having unexpectedly high unfavorable outcomes when our framework is applied will be those where poor quality will most likely be found by primary review of the process of care. We outline the following criteria for the selection of disease-outcome pairs to be studied in large administrative database analysis: (1) disease entities or clinical states selected should be well defined and easily diagnosed; (2) if diagnostic classification systems are used, disease groups should be homogeneous as to the clinical states they contain; (3) the disease entities should be prevalent; (4) a plausible link should exist between the quality (process) of care and the frequency of the outcome; (5) types of care which conform to acceptable practice standards but still lead to variation in the outcome of interest should be excluded from the analysis; (6) the outcomes should be prevalent; (7) constraints of the ICD-9 coding system should be understood such that only those disease-outcome pairs least affected by these limitations are selected for analysis; (8) constraints of the structure of the database should be considered when the analysis is performed; and (9) disease-outcome pairs should be chosen where there is agreement on the processes of care that affect the outcome of interest, either favorably or unfavorably.
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Bibliographic InfoArticle provided by Elsevier in its journal Social Science & Medicine.
Volume (Year): 40 (1995)
Issue (Month): 12 (June)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description
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- Häkkinen, Unto & Iversen, Tor & Peltola, Mikko & Seppälä, Timo T. & Malmivaara, Antti & Belicza, Éva & Fattore, Giovanni & Numerato, Dino & Heijink, Richard & Medin, Emma & Rehnberg, Clas, 2013. "Health care performance comparison using a disease-based approach: The EuroHOPE project," Health Policy, Elsevier, vol. 112(1), pages 100-109.
- Jenni Pääkkönen & Timo Seppälä, 2012. "Dimensions of health care system quality in Finland," Working Papers 31, Government Institute for Economic Research Finland (VATT).
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