Do Non-Clinical Factors Improve Prediction of Readmission Risk?: Results From the Tele-HF Study
Harlan M Krumholz, Sarwat I Chaudhry, John A Spertus, Jennifer A Mattera, Beth Hodshon, Jeph Herrin, Harlan M Krumholz, Sarwat I Chaudhry, John A Spertus, Jennifer A Mattera, Beth Hodshon, Jeph Herrin
Abstract
Objectives: 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).
Keywords: heart failure; prognosis; readmission.
Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Source: PubMed