Literature DB >> 29616911

The Rural Inpatient Mortality Study: Does Urban-Rural County Classification Predict Hospital Mortality in California?

Daniel T Linnen1, John Kornak2, Caroline Stephens3.   

Abstract

CONTEXT: Evidence suggests an association between rurality and decreased life expectancy.
OBJECTIVE: To determine whether rural hospitals have higher hospital mortality, given that very sick patients may be transferred to regional hospitals.
DESIGN: In this ecologic study, we combined Medicare hospital mortality ratings (N = 1267) with US census data, critical access hospital classification, and National Center for Health Statistics urban-rural county classifications. Ratings included mortality for coronary artery bypass grafting, stroke, chronic obstructive pulmonary disease, heart attack, heart failure, and pneumonia across 277 California hospitals between July 2011 and June 2014. We used generalized estimating equations to evaluate the association of urban-rural county classifications on mortality ratings. MAIN OUTCOME MEASURES: Unfavorable Medicare hospital mortality rating "worse than the national rate" compared with "better" or "same."
RESULTS: Compared with large central "metro" (metropolitan) counties, hospitals in medium-sized metro counties had 6.4 times the odds of rating "worse than the national rate" for hospital mortality (95% confidence interval = 2.8-14.8, p < 0.001). For hospitals in small metro counties, the odds of having such a rating were 3.7 times greater (95% confidence interval = 0.7-23.4, p = 0.12), although not statistically significant. Few ratings were provided for rural counties, and analysis of rural counties was underpowered.
CONCLUSION: Hospitals in medium-sized metro counties are associated with unfavorable Medicare mortality ratings, but current methods to assign mortality ratings may hinder fair comparisons. Patient transfers from rural locations to regional medical centers may contribute to these results, a potential factor that future research should examine.

Entities:  

Mesh:

Year:  2018        PMID: 29616911      PMCID: PMC5882190          DOI: 10.7812/TPP/17-078

Source DB:  PubMed          Journal:  Perm J        ISSN: 1552-5767


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