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


METHODS
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.


METHODS
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.
Shwartz
M
M
Operations Management Department, School of Management, Boston University, MA 02215, USA.
Klimberg
R K
RK
Karp
M
M
Iezzoni
L I
LI
Ash
A S
AS
Heineke
J
J
Payne
S M
SM
Restuccia
J D
JD
D015982:Bias; D003627:Data Interpretation, Statistical; D003953:Diagnosis-Related Groups; D006300:Health Services Misuse / Q000706:statistics & numerical data; D006302:Health Services Research / Q000379:methods*; D006761:Hospitals / Q000592:standards / Q000706:statistics & numerical data*; D008499:Medical Records / Q000706:statistics & numerical data; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care; D011787:Quality of Health Care / Q000706:statistics & numerical data; D012494:Sampling Studies; D017062:Small-Area Analysis; D014481:United States