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Making Sense Out of Utilization Data

Bibliographic Data

ID9100613
AuthorsJohn C Hershey (Stanford University, corresponding author), Harold S Luft (0000-0002-4696-2745, Health Resources and Services Administration, corresponding author), Joan M Gianaris
Year1975
Volume13
Issue10
Pages838-854
Publication date1975-10-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/00005650-197510000-00004
PMID1181496
OpenAlexW1981419242
LanguageEN
Citations received21
References cited5

Health care utilization studies often reach conflicting conclusions about the appropriate measures of utilization and the relationships between such measures and the explanatory variables. The purpose of this paper is to demonstrate why such ambiguities exist, provide empirical tests of different models, and suggest an appropriate analytical framework. A household survey of a rural California community was used to collect both family and individual data on utilization, "need," accessibility, attitudes, and demographics. A number of possible utilization models are presented, each containing alternative sets of dependent and independent variables. Multiple regression analysis is applied to each model, providing considerable insight into the roles of specific independent variables in explaining alternative utilization measures. The omission of certain variables, such as health status (or "need"), can result in an incorrect interpretation of the results

Demographics · Econometrics · Economics · Health care · Interpretation (philosophy) · Machine learning · Regression analysis · Sociology · Variables · Computer Science · Gender, Labor, and Family Dynamics · Global Health Care Issues · Healthcare Policy and Management · Mathematics

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Unique citing works21
Citations per year0,42
Citation span1976 - 2011 (36)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 10

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