Literature DB >> 9180613

A comparison of three methods for estimating the requirements for medical specialists: the case of otolaryngologists.

G F Anderson1, K C Han, R H Miller, M E Johns.   

Abstract

OBJECTIVE: To compare three methods of computing the national requirements for otolaryngologists in 1994 and 2010. DATA SOURCES: Three large HMOs, a Delphi panel, the Bureau of Health Professions (BHPr), and published sources. STUDY
DESIGN: Three established methods of computing requirements for otolaryngologists were compared: managed care, demand-utilization, and adjusted needs assessment. Under the managed care model, a published method based on reviewing staffing patterns in HMOs was modified to estimate the number of otolaryngologists. We obtained from BHPr estimates of work force projections from their demand model. To estimate the adjusted needs model, we convened a Delphi panel of otolaryngologists using the methodology developed by the Graduate Medical Education National Advisory Committee (GMENAC). DATA COLLECTION/EXTRACTION
METHODS: Not applicable. PRINCIPAL
FINDINGS: Wide variation in the estimated number of otolaryngologists required occurred across the three methods. Within each model it was possible to alter the requirements for otolaryngologists significantly by changing one or more of the key assumptions. The managed care model has a potential to obtain the most reliable estimates because it reflects actual staffing patterns in institutions that are attempting to use physicians efficiently.
CONCLUSIONS: Estimates of work force requirements can vary considerably if one or more assumptions are changed. In order for the managed care approach to be useful for actual decision making concerning the appropriate number of otolaryngologists required, additional research on the methodology used to extrapolate the results to the general population is necessary.

Mesh:

Year:  1997        PMID: 9180613      PMCID: PMC1070178     

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


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