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International Journal of Health Geographics
Volume 8

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Open AccessMethodology

Using hospitalization for ambulatory care sensitive conditions to
measure access to primary health care: an application of spatial
structural equation modeling
=================================================================

Md Monir Hossain1 email and James N Laditka2 email

1. Biostatistics, Epidemiology and Research Design (BERD) Core, Center for Clinical and Translational Sciences, The University of Texas Health Science Center at Houston, UT Professional Building, Room
2. 100.25, 6410 Fannin Street, Houston, TX, 77030, USA

1. Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA

author email corresponding author email

International Journal of Health Geographics 2009, 8:51doi:10.1186/1476-072X-8-51

Published:

28 August 2009

Abstract

Background

In data commonly used for health services research, a number of
relevant variables are unobservable. These include population
lifestyle and socio-economic status, physician practice behaviors,
population tendency to use health care resources, and disease
prevalence. These variables may be considered latent constructs of
many observed variables. Using health care data from South Carolina,
we show an application of spatial structural equation modeling to
identify how these latent constructs are associated with access to
primary health care, as measured by hospitalizations for ambulatory
care sensitive conditions. We applied the confirmatory factor analysis
approach, using the Bayesian paradigm, to identify the spatial
distribution of these latent factors. We then applied cluster
detection tools to identify counties that have a higher probability of
hospitalization for each of the twelve adult ambulatory care sensitive
conditions, using a multivariate approach that incorporated the
correlation structure among the ambulatory care sensitive conditions
into the model.

Results

For the South Carolina population ages 18 and over, we found that
counties with high rates of emergency department visits also had less
access to primary health care. We also observed that in those counties
there are no community health centers.

Conclusion

Locating such clusters will be useful to health services researchers
and health policy makers; doing so enables targeted policy
interventions to efficiently improve access to primary care.

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