Development of a predictive score for potentially avoidable hospital readmissions for general internal medicine patients

PLoS One. 2019 Jul 15;14(7):e0219348. doi: 10.1371/journal.pone.0219348. eCollection 2019.

Abstract

Background: Identifying patients at high risk of hospital preventable readmission is an essential step towards selecting those who might benefit from specific transitional interventions.

Objective: Derive and validate a predictive risk score for potentially avoidable readmission (PAR) based on analysis of readmissions, with a focus on medication.

Design/setting/participants: Retrospective analysis of all hospital admissions to internal medicine wards between 2011 and 2014. Comparison between patients readmitted within 30 days and non-readmitted patients, as identified using a specially designed algorithm. Univariate and multivariate regression analyses of demographic data, clinical diagnoses, laboratory results, and the medication data of patients admitted during the first period (2011-2013), to identify factors associated with PAR. Using these, derive a predictive score with a regression coefficient-based scoring method. Subsequently, validate this score with a second cohort of patients admitted in 2013-2014. Variables were identified at hospital discharge.

Results: The derivation cohort included 7,317 hospital stays. Multivariate logistic regressions found significant associations with PAR for: [adjusted OR (95% CI)] hospital length of stay > 4 days [1.3 (1.1-1.7)], admission in previous 6 months [2.3 (1.9-2.8)], heart failure [1.3 (1.0-1.7)], chronic ischemic heart disease [1.7 (1.2-2.3)], diabetes with organ damage [2.2 (1.3-3.8)], cancer [1.4 (1.0-1.9)], metastatic carcinoma [1.9 (1.3-3.0)], anemia [1.2 (1.0-1.5)], hypertension [1.3 (1.1-1.7)], arrhythmia [1.3 (1.0-1.6)], hyperkalemia [1.4 (1.0-1.7)], opioid drug prescription [1.3 (1.1-1.6)], and acute myocardial infarction [0.6 (0.4-0.9)]. The PAR-Risk Score, derived from these results, demonstrated fair discriminatory and calibration power (C-statistic = 0.699; Brier Score = 0.069). The results for the validation cohort's operating characteristics were similar (C-statistic = 0.687; Brier Score = 0.064).

Conclusion: This study identified routinely-available factors that were significantly associated with PAR. A predictive score was derived and internally validated.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Algorithms
  • Diabetes Mellitus / therapy
  • Female
  • Heart Failure / therapy
  • Humans
  • Internal Medicine / methods*
  • Length of Stay / statistics & numerical data
  • Logistic Models
  • Male
  • Multivariate Analysis
  • Myocardial Ischemia / therapy
  • Neoplasms / therapy
  • Patient Discharge / statistics & numerical data
  • Patient Readmission / statistics & numerical data*
  • Predictive Value of Tests
  • Retrospective Studies
  • Risk Assessment / methods*

Grants and funding

ALB as a PhD-student was supported by the 2013 national research grant from the Swiss Association of Public Health Administration and Hospital Pharmacists (GSASA), 2013 (http://www.gsasa.ch/pages/recherche/projets-de-recherche-d-ampleur-nationale/projet2013/?oid=1658&lang=FR). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.