title: Admission Data Predict High Hospital Readmission Risk.
abstract: OBJECTIVE
  The purpose of this study was to identify data available at the time of hospital admission that predict readmission risk.
  
  
  METHODS
  We performed a retrospective multiple regression analysis of 958 adult, nonpregnant patients admitted to the Family Medicine Service between June 2012 and October 2013. Data were abstracted from hospital administrative sources and electronic medical records. The outcome was 30-day hospital readmission. Candidate readmission predictors included polypharmacy (≥6 medicines), Charlson comorbidity index, age, sex, insurance status, emergency department use, smoking, nursing report of cognitive issues, patient report of social support or financial issues, and a history of heart failure, pneumonia, or chronic obstructive pulmonary disease.
  
  
  RESULTS
  Patients at the Family Medicine Service had a 14% readmission risk. Bivariate analysis showed that high Charlson scores (≥5), polypharmacy, heart failure, pneumonia, or chronic obstructive pulmonary disease each increased readmission risk (P < .05). A logistic model showed an estimated odds ratio for readmission for high Charlson scores of 1.7 (95% confidence interval, 1.1-2.6) and of 2.1 for polypharmacy (95% confidence interval, 1.3-3.7). The model yielded a readmission risk estimate of 6% if neither a high Charlson score nor polypharmacy was present, 9% if only the Charlson score was high, 12% if only polypharmacy was present, and 19% if both were present. The receiver operating characteristics curve for the 2-factor model yielded an estimated area under the curve of 85%. Cross-validation supported this result.
  
  
  CONCLUSIONS
  Polypharmacy and higher Charlson score at admission predict readmission risk as well as or better than published risk prediction models. The model could help to conserve limited resources and to target interventions for reducing readmission among the highest-risk patients.
authors.affiliation: From the Department of Family Medicine, Summa Health System, Akron, OH. LogueE@summahealth.org.
authors.forename: Everett
authors.initials: E
authors.lastname: Logue
authors.affiliation: From the Department of Family Medicine, Summa Health System, Akron, OH.
authors.forename: William
authors.initials: W
authors.lastname: Smucker
authors.affiliation: From the Department of Family Medicine, Summa Health System, Akron, OH.
authors.forename: Christine
authors.initials: C
authors.lastname: Regan
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D060825:Cognitive Dysfunction; D015897:Comorbidity; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D005194:Family Practice / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D007348:Insurance, Health / Q000145:classification; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009820:Ohio; D010343:Patient Admission / Q000191:economics / Q000592:standards / Q000706:statistics & numerical data*; D010359:Patient Readmission / Q000706:statistics & numerical data*; D064798:Polypharmacology; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods* / Q000706:statistics & numerical data; D064876:Safety-net Providers / Q000706:statistics & numerical data; D012907:Smoking / Q000453:epidemiology; D012959:Socioeconomic Factors; D055815:Young Adult
keywords: Comorbidity; Hospital Readmission; Polypharmacy; Risk