LAUSR

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.