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An integer programming model to limit hospital selection in studies with repeated sampling
M Shwartz1, R K Klimberg, M Karp
1Operations Management Department, School of Management, Boston University, MA 02215, USA.
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.