Measuring horizontal inequity in Belgian health care using a Gaussian random effects two part count data model

49Citations
Citations of this article
50Readers
Mendeley users who have this article in their library.
Get full text

Abstract

We estimate the determinants of utilisation of physician and hospital services in Belgium using a one- and two-part panel count data model, and a one- and two-part pooled count data model. We conclude that the two-part panel count data model is most appropriate as it controls for unobserved heterogeneity and allows for a two-part decision-making process. The estimates of the determinants of utilisation of health care are then used to calculate indices of horizontal inequity. We find that inequity for general practitioner and hospital services is stable across time and in favour of low-income individuals, in the sense that, overall, they consume more than one would expect on the basis of their need, albeit the indices for hospital care are not significant. Horizontal equity applies to specialist care in all years, but from 1999 onwards, some evidence (although not statistically significant) of pro-rich inequity is found. Copyright © 2004 John Wiley & Sons, Ltd.

Cite

CITATION STYLE

APA

Van Ourti, T. (2004). Measuring horizontal inequity in Belgian health care using a Gaussian random effects two part count data model. Health Economics, 13(7), 705–724. https://doi.org/10.1002/hec.920

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free