Do Non-Clinical Factors Improve Prediction of Readmission Risk?: Results From the Tele-HF Study

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• 作者：Harlan M. Krumholz ; MD ; SM^&lowast ; ; ^&dagger ; ; ^&Dagger ; ; ^§ ; ; ^{harlan.krumholz@yale.edu" class="auth_mail" title="E-mail the corresponding author} ; Sarwat I. Chaudhry ; MD^‖ ; John A. Spertus ; MD ; MPH^¶ ; ; Jennifer A. Mattera ; MPH ; DrPH^&Dagger ; ; Beth Hodshon ; JD ; MPH ; RN^‖ ; Jeph Herrin ; PhD^&lowast ; ; ^#
• 关键词：heart failure ; prognosis ; readmission
• 刊名：JACC: Heart Failure
• 出版年：2016
• 出版时间：January 2016
• 年：2016
• 卷：4
• 期：1
• 页码：12-20
• 全文大小：215 K

文摘

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)