Literature DB >> 7782221

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

M Shwartz1, R K Klimberg, M Karp, L I Iezzoni, A S Ash, J Heineke, S M Payne, J D Restuccia.   

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.

Mesh:

Year:  1995        PMID: 7782221      PMCID: PMC1070068     

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


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