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How Do the Determinants of Demand for GP Visits Respond to Higher Supply? An Analysis of Grouped Counts

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Author Info
Paulos Teckle
Matt Sutton
Abstract

Although there is a substantial literature on the determinants of demand for primary care, few studies have been able to examine how these determinants respond to higher supply. Some demand studies include supply variables or regional dummy variables to allow for different supply conditions. A few have tested for marginal effects of supply variables attributed at a highly aggregated geographic level. However, relatively little is known about whether there is a supply constraint and how demand responses differ across population groups. We used information from a household survey of 60'806 individuals for whom we had detailed information on supply and access conditions. As in many surveys, the annual measure of utilisation is a grouped count and we estimate a grouped negative binomial model (NegBin2) of the determinants of demand for general practitioner (GP) visits by Maximum Likelihood. We exploit a variable on which respondents were asked to report the convenience with which they were able to access GP services. We demonstrate the significance of this variable in determining the number of GP visits. We then examine which demand determinants are correlated with reported convenience. Finally, we compare the demand equations for respondents reporting unconstrained access to GPs with respondents reporting constrained access. We find that being unemployed has a significant positive effect on GP visits for individuals who reported poor access. People who own a car and reported a good access to GPs have significantly higher visits.

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Article provided by Swiss Society of Economics and Statistics (SSES) in its journal Swiss Journal of Economics and Statistics.

Volume (Year): 144 (2008)
Issue (Month): III (September)
Pages: 495-513
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Handle: RePEc:ses:arsjes:2008-iii-10

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Related research
Keywords: health care utilization: equity: access to services: survey methods;

Find related papers by JEL classification:
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
I10 - Health, Education, and Welfare - - Health - - - General

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  1. Jones, Andrew M., 2000. "Health econometrics," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 6, pages 265-344 Elsevier. [Downloadable!] (restricted)
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This page was last updated on 2009-12-11.


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