Predictors and outcomes of unplanned readmission to a different hospital

Int J Qual Health Care. 2015 Dec;27(6):513-9. doi: 10.1093/intqhc/mzv082. Epub 2015 Oct 15.

Abstract

Objectives: To examine patient, hospital and market factors and outcomes associated with readmission to a different hospital compared with the same hospital.

Design: A population-based, secondary analysis using multilevel causal modeling.

Setting: Acute care hospitals in California in the USA.

Participants: In total, 509 775 patients aged 50 or older who were discharged alive from acute care hospitals (index hospitalizations), and 59 566 who had a rehospitalization within 30 days following their index discharge.

Intervention: No intervention.

Main outcome measure(s): Thirty-day unplanned readmissions to a different hospital compared with the same hospital and also the costs and health outcomes of the readmissions.

Results: Twenty-one percent of patients with a rehospitalization had a different-hospital readmission. Compared with the same-hospital readmission group, the different-hospital readmission group was more likely to be younger, male and have a lower income. The index hospitals of the different-hospital readmission group were more likely to be smaller, for-profit hospitals, which were also more likely to be located in counties with higher competition. The different-hospital readmission group had higher odds for in-hospital death (8.1 vs. 6.7%; P < 0.0001) and greater readmission hospital costs ($15 671.8 vs. $14 286.4; P < 0.001) than the same-hospital readmission group.

Conclusions: Patient, hospital and market characteristics predicted different-hospital readmissions compared with same-hospital readmissions. Mortality and cost outcomes were worse among patients with different-hospital readmissions. Strategies for better care coordination targeting people at risk for different-hospital readmissions are necessary.

Keywords: health policy; hospital care; patient outcomes; readmissions.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Aged
  • Aged, 80 and over
  • California
  • Data Interpretation, Statistical
  • Datasets as Topic
  • Female
  • Forecasting
  • Hospitals*
  • Humans
  • Male
  • Middle Aged
  • Outcome Assessment, Health Care
  • Patient Discharge
  • Patient Readmission / trends*