An integer programming model to limit hospital selection in studies with repeated sampling
Shwartz, Michael ; Klimberg, Ronald K. ; Karp, Melinda ; Iezzoni, Lisa I. ; Ash, Arlene S. ; Heineke, Janelle ; Payne, Susan M. C. ; Restuccia, Joseph D.
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UMass Chan Affiliations
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Keywords
Data Interpretation, Statistical
Diagnosis-Related Groups
Health Services Misuse
Health Services Research
Hospitals
Medical Records
Models, Statistical
Outcome Assessment (Health Care)
Quality of Health Care
*Sampling Studies
Small-Area Analysis
United States
Biostatistics
Epidemiology
Health Services Research
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Abstract
OBJECTIVE: We describe an integer programming model that, for studies requiring repeated sampling from hospitals, can aid in selecting a limited set of hospitals from which medical records are reviewed.
STUDY SETTING: The model is illustrated in the context of two studies: (1) an analysis of the relationship between variations in hospital admission rates across geographic areas and rates of inappropriate admissions; and (2) a validation of computerized algorithms that screen for complications of hospital care.
STUDY DESIGN: Common characteristics of the two studies: (1) hospitals are classified into categories, e.g., high, medium, and low; (2) the classification process is repeated several times, e.g., for different medical conditions; (3) medical records are selected separately for each iteration of the classification; and (4) for budgetary and logistical reasons, reviews must be concentrated in a relatively small subset of hospitals.
DATA COLLECTION/EXTRACTION METHODS. In each study, hospitals are ranked based on analysis of hospital discharge abstract data.
CONCLUSIONS: The model is useful for identifying a subset of hospitals at which more intensive reviews will be conducted.
Source
Health Serv Res. 1995 Jun;30(2):359-76. Link to article on publisher's site