An integer programming model to limit hospital selection in studies with repeated sampling

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Department of Quantitative Health Sciences

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Bias (Epidemiology); 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


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.


Health Serv Res. 1995 Jun;30(2):359-76. Link to article on publisher's site

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Health services research

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Link to Article in PubMed