Volume 50 | Number 1 | February 2015

Abstract List

Jeph Herrin Ph.D., Justin St. Andre M.A., Kevin Kenward, Maulik S. Joshi Dr.P.H., Anne‐Marie J. Audet M.D., M.Sc., Stephen C. Hines Ph.D.


To examine the relationship between community factors and hospital readmission rates.

Data Sources/Study Setting

We examined all hospitals with publicly reported 30‐day readmission rates for patients discharged during July 1, 2007, to June 30, 2010, with acute myocardial infarction (), heart failure (), or pneumonia (). We linked these to publicly available county data from the Area Resource File, the Census, Nursing Home Compare, and the Neilsen PopFacts datasets.

Study Design

We used hierarchical linear models to assess the effect of county demographic, access to care, and nursing home quality characteristics on the pooled 30‐day risk‐standardized readmission rate.

Data Collection/Extraction Methods

Not applicable.

Principal Findings

The study sample included 4,073 hospitals. Fifty‐eight percent of national variation in hospital readmission rates was explained by the county in which the hospital was located. In multivariable analysis, a number of county characteristics were found to be independently associated with higher readmission rates, the strongest associations being for measures of access to care. These county characteristics explained almost half of the total variation across counties.


Community factors, as measured by county characteristics, explain a substantial amount of variation in hospital readmission rates.