Community Factors and Hospital Readmission Rates. (9th April 2014)

• Record Type: Journal Article
• Authors: Herrin, Jeph; St. Andre, Justin; Kenward, Kevin; Joshi, Maulik S.; Audet, Anne‐Marie J.; Hines, Stephen C.
• Is Part Of: Health services research. Volume 50:Number 1(2015:Feb.)
• Page Start: 20
• Page End: 39
• Publication Date: 2014-04-09
• Subjects: Medical care -- Periodicals; Medical care -- Evaluation -- Periodicals; Hospital care -- Periodicals; Health services administration -- Periodicals; 362
• DOI: 10.1111/1475-6773.12177
• Languages: English
• ISSNs: 0017-9124

Abstract

<abstract abstract-type="main" id="hesr12177-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="hesr12177-sec-0001" sec-type="section"> <title>Objective</title> <p>To examine the relationship between community factors and hospital readmission rates.</p> </sec> <sec id="hesr12177-sec-0002" sec-type="section"> <title>Data Sources/Study Setting</title> <p>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 (AMI), heart failure (HF), or pneumonia (PN). We linked these to publicly available county data from the Area Resource File, the Census, Nursing Home Compare, and the Neilsen PopFacts datasets.</p> </sec> <sec id="hesr12177-sec-0003" sec-type="section"> <title>Study Design</title> <p>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.</p> </sec> <sec id="hesr12177-sec-0004" sec-type="section"> <title>Data Collection/Extraction Methods</title> <p>Not applicable.</p> </sec> <sec id="hesr12177-sec-0005" sec-type="section"> <title>Principal Findings</title> <p>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.</p> </sec> <sec id="hesr12177-sec-0006" sec-type="section"> <title>Conclusions</title> <p>Community factors, as measured by county characteristics, explain a substantial amount of variation in hospital readmission rates.</p> </sec> </abstract>