Darcey D Terris1, David G Litaker, Siran M Koroukian. 1. Division of Health Services Research & Policy, Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA. ddt@case.edu
Abstract
OBJECTIVE: Secondary databases are used in descriptive studies of patient subgroups; evaluation of associations between individual characteristics and diagnosis, prognosis, and/or service utilization rates; and studies of the quality of health care delivered. This article identifies sources of bias for health state characteristics stored in secondary databases that arise from patients' encounters with health systems, highlighting sources of bias that arise from organizational and environmental factors. STUDY DESIGN AND SETTING: Potential sources of bias, from patient access of services and diagnosis, through encoding and filing of patient information in secondary databases, are discussed. A patient presenting with acute myocardial infarction is used as an illustrative example. RESULTS: The accuracy of health state characteristics derived from secondary databases is a function of both the quality and quantity of information collected before data entry and is dependent on complex interactions between patients, clinicians, and the structures and systems surrounding them. CONCLUSION: The use of health state information included in secondary databases requires that estimates of potential bias from all sources be included in the analysis and presentation of results. By making this common practice in the field, greater value can be achieved from secondary database analyses.
OBJECTIVE: Secondary databases are used in descriptive studies of patient subgroups; evaluation of associations between individual characteristics and diagnosis, prognosis, and/or service utilization rates; and studies of the quality of health care delivered. This article identifies sources of bias for health state characteristics stored in secondary databases that arise from patients' encounters with health systems, highlighting sources of bias that arise from organizational and environmental factors. STUDY DESIGN AND SETTING: Potential sources of bias, from patient access of services and diagnosis, through encoding and filing of patient information in secondary databases, are discussed. A patient presenting with acute myocardial infarction is used as an illustrative example. RESULTS: The accuracy of health state characteristics derived from secondary databases is a function of both the quality and quantity of information collected before data entry and is dependent on complex interactions between patients, clinicians, and the structures and systems surrounding them. CONCLUSION: The use of health state information included in secondary databases requires that estimates of potential bias from all sources be included in the analysis and presentation of results. By making this common practice in the field, greater value can be achieved from secondary database analyses.
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