Powered by: Blackwell Publishing

HRET - Health Research & Educational Trust

HSR - Health Services Research

Impacting Health Practice and Policy Through State-of-the-Art Research and Thinking

Our Next Issue

August 2018
Coming Soon! Read

< ABSTRACT LIST

VOLUME 50 | NUMBER 5 | OCTOBER 2015


Modeling Area-Level Health Rankings

Keywords: County; rank; health; factor analysis; Bayesian

Objective: Rank county health using a Bayesian factor analysis model.

Data Sources: Secondary county data from the National Center for Health Statistics (through 2007) and Behavioral Risk Factor Surveillance System (through 2009).

Study Design: Our model builds on the existing county health rankings (CHRs) by using data-derived weights to compute ranks from mortality and morbidity variables, and by quantifying uncertainty based on population, spatial correlation, and missing data. We apply our model to Wisconsin, which has comprehensive data, and Texas, which has substantial missing information.

Data Collection Methods: The data were downloaded from www.countyhealthrankings.org.

Principal Findings: Our estimated rankings are more similar to the CHRs for Wisconsin than Texas, as the data-derived factor weights are closer to the assigned weights for Wisconsin. The correlations between the CHRs and our ranks are 0.89 for Wisconsin and 0.65 for Texas. Uncertainty is especially severe for Texas given the state's substantial missing data.

Conclusions: The reliability of comprehensive CHRs varies from state to state. We advise focusing on the counties that remain among the least healthy after incorporating alternate weighting methods and accounting for uncertainty. Our results also highlight the need for broader geographic coverage in health data.

back to top | back to article index | access/purchase full article

Copyright© 2017, Health Research & Educational Trust. All rights reserved. Content Disclaimer
Health Research & Educational Trust, 155 North Wacker, 4th Floor Chicago, IL 60606 (312) 422.2600