Supplier-induced demand for psychiatric admissions in Northern New England.

Bradley V Watts,Gunnar Klauss,William B Weeks,Brian Shiner

doi:10.1186/1471-244x-11-146

Abstract

BackgroundThe development of hospital service areas (HSAs) using small area analysis has been useful in examining variation in medical and surgical care; however, the techniques of small area analysis are underdeveloped in understanding psychiatric admission rates. We sought to develop these techniques in order to understand the relationship between psychiatric bed supply and admission rates in Northern New England. Our primary hypotheses were that there would be substantial variation in psychiatric admission across geographic settings and that bed availability would be positively correlated with admission rates, reflecting a supplier-induced demand phenomenon. Our secondary hypothesis was that the construction of psychiatric HSAs (PHSAs) would yield more meaningful results than the use of existing general medical hospital service areas.MethodsTo address our hypotheses, we followed a four-step analytic process: 1) we used small area analytic techniques to define our PHSAs, 2) we calculated the localization index for PHSAs and compared that to the localization index for general medical HSAs, 3) we used the number of psychiatric hospital beds, the number of psychiatric admissions, and census data to calculate population-based bed-supply and psychiatric admission rates for each PHSA, and 4) we correlated population-based admission rates to population-based psychiatric bed supply.ResultsThe admission rate for psychiatric diagnosis varied considerably among the PHSAs, with rates varying from 2.4 per 100,000 in Portsmouth, NH to 13.4 per 100,000 in Augusta, ME. There was a positive correlation of 0.71 between a PHSA's supply of beds and admission rate. Using our PSHAs produced a substantially higher localization index than using general medical hospital services areas (0.69 vs. 0.23), meaning that our model correctly predicted geographic utilization at three times the rate of the existing model.ConclusionsThe positive correlation between admission and bed supply suggests that psychiatric bed availability may partially explain the variation in admission rates. Development of PHSAs, rather than relying on the use of established general medical HSAs, improves the relevance and accuracy of small area analysis in understanding mental health services utilization.

Highlights

The development of hospital service areas (HSAs) using small area analysis has been useful in examining variation in medical and surgical care; the techniques of small area analysis are underdeveloped in understanding psychiatric admission rates
This study found that population variables such as poverty and population density were highly correlated with mental health service utilization
To address our hypotheses, we followed a four-step analytic process: 1) we used small area analytic techniques to define our psychiatric HSAs (PHSAs), 2) we calculated the localization index for psychiatric hospital service areas and compared that to the localization index for general medical HSAs, 3) we used the number of psychiatric hospital beds, the number of psychiatric admissions, and census data to calculate population-based bed-supply and psychiatric admission rates for each psychiatric service area, and 4) we correlated population-based admission rates to population-based psychiatric bed supply

Summary

Introduction

The development of hospital service areas (HSAs) using small area analysis has been useful in examining variation in medical and surgical care; the techniques of small area analysis are underdeveloped in understanding psychiatric admission rates. Our primary hypotheses were that there would be substantial variation in psychiatric admission across geographic settings and that bed availability would be positively correlated with admission rates, reflecting a supplier-induced demand phenomenon. Small area analysis is a health services research technique that facilitates geographic comparison of health services utilization rates [1]. Using this technique, researchers have consistently documented the existence of supplier-induced demand [2] for health services [3,4,5]. While there is general agreement that utilization and supply are correlated, there is less agreement regarding the meaning and drivers of this association [16]

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