title: Do Non-Clinical Factors Improve Prediction of Readmission Risk?: Results From the Tele-HF Study.
abstract: OBJECTIVE
  This study sought to determine whether a model that included self-reported socioeconomic, health status, and psychosocial characteristics obtained from patients recently discharged from hospitalizations for heart failure substantially improved 30-day readmission risk prediction compared with a model that incorporated only clinical and demographic factors.
  
  
  BACKGROUND
  Existing readmission risk models have poor discrimination and it is unknown whether they would be markedly improved by the inclusion of patient-reported information.
  
  
  METHODS
  As part of the Tele-HF (Telemonitoring to Improve Heart Failure Outcomes) trial, we conducted medical record abstraction and telephone interviews in a sample of 1,004 patients recently hospitalized for heart failure to obtain clinical, functional, and psychosocial information within 2 weeks of discharge. Candidate risk factors included 110 variables divided into 2 groups: demographic and clinical variables generally available from the medical record; and socioeconomic, health status, adherence, and psychosocial variables from patient interview.
  
  
  RESULTS
  The 30-day readmission rate was 17.1%. Using the 3-level risk score derived from the restricted medical record variables, patients with a score of 0 (no risk factors) had a readmission rate of 10.9% (95% confidence interval [CI]: 8.2% to 14.2%), and patients with a score of 2 (all risk factors) had a readmission rate of 32.1% (95% CI: 22.4% to 43.2%), a C-statistic of 0.62. Using the 5-level risk score derived from all variables, patients with a score of 0 (no risk factors) had a readmission rate of 9.6% (95% CI: 6.1% to 14.2%), and patients with a score of 4 (all risk factors) had a readmission rate of 55.0% (95% CI: 31.5% to 76.9%), a C-statistic of 0.65.
  
  
  CONCLUSIONS
  Self-reported socioeconomic, health status, adherence, and psychosocial variables are not dominant factors in predicting readmission risk for patients with heart failure. Patient-reported information improved model discrimination and extended the predicted ranges of readmission rates, but the model performance remained poor. (Telemonitoring to Improve Heart Failure Outcomes [Tele-HF]; NCT00303212).
authors.affiliation: Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut; Robert Wood Johnson Foundation Clinical Scholars Program, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut; Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut. Electronic address: harlan.krumholz@yale.edu.
authors.forename: Harlan M
authors.initials: HM
authors.lastname: Krumholz
authors.affiliation: Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
authors.forename: Sarwat I
authors.initials: SI
authors.lastname: Chaudhry
authors.affiliation: Mid America Heart Institute, University of Missouri-Kansas City School of Medicine, Kansas City, Missouri.
authors.forename: John A
authors.initials: JA
authors.lastname: Spertus
authors.affiliation: Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut.
authors.forename: Jennifer A
authors.initials: JA
authors.lastname: Mattera
authors.affiliation: Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
authors.forename: Beth
authors.initials: B
authors.lastname: Hodshon
authors.affiliation: Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut; Health Research and Educational Trust, Chicago, Illinois.
authors.forename: Jeph
authors.initials: J
authors.lastname: Herrin
mesh_terms: D000328:Adult; D000368:Aged; D005260:Female; D006304:Health Status; D006333:Heart Failure / Q000628:therapy*; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000379:methods; D010359:Patient Readmission / Q000706:statistics & numerical data*; D018802:Patient-Centered Care / Q000379:methods; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D057566:Self Report; D012959:Socioeconomic Factors; D017216:Telemedicine / Q000379:methods; D016896:Treatment Outcome
keywords: heart failure; prognosis; readmission