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Do Non-Clinical Factors Improve Prediction of Readmission Risk?: Results From the Tele-HF Study.
Krumholz, Harlan M; Chaudhry, Sarwat I; Spertus, John A; Mattera, Jennifer A; Hodshon, Beth; Herrin, Jeph.
Affiliation
  • Krumholz HM; 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 Evaluatio
  • Chaudhry SI; Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
  • Spertus JA; Mid America Heart Institute, University of Missouri-Kansas City School of Medicine, Kansas City, Missouri.
  • Mattera JA; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut.
  • Hodshon B; Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
  • Herrin J; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut; Health Research and Educational Trust, Chicago, Illinois.
JACC Heart Fail ; 4(1): 12-20, 2016 Jan.
Article in En | MEDLINE | ID: mdl-26656140
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).
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Patient Readmission / Heart Failure Type of study: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies Aspects: Patient_preference Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: JACC Heart Fail Year: 2016 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Patient Readmission / Heart Failure Type of study: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies Aspects: Patient_preference Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: JACC Heart Fail Year: 2016 Document type: Article
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