title: Identifying Potentially Avoidable Readmissions: A Medication-Based 15-Day Readmission Risk Stratification Algorithm.
abstract: Stratifying patients according to 15-day readmission risk would be useful in identifying those who may benefit from targeted interventions during and/or following hospital discharge that are designed to reduce the likelihood of readmission.
  
  
  
  A prediction model was derived via a case-control analysis of patients discharged from a tertiary hospital in Singapore using multivariate logistic regression. The model was validated in two independent external cohorts separated temporally and geographically. Model discrimination was assessed using the C-statistic, while calibration was assessed using the Hosmer-Lemeshow χ2and the Brier score statistics.
  
  
  
  A total of 1291 patients were included with 670, 101, and 520 patients in the derivation, temporal, and geographical validation cohorts, respectively. Age (odds ratio [OR] 1.02, 95% confidence interval [CI] 1.01-1.03, p=0.008), anemia (OR 2.08, 95% CI 1.15-8.05, p=0.015), malignancy (OR 3.37, 95% CI 1.16-9.80, p=0.026), peptic ulcer disease (OR 3.05, 95% CI 1.12-8.26, p=0.029), chronic obstructive pulmonary disease (OR 3.16, 95% CI 1.24-8.05, p=0.016), number of discharge medications (OR 1.06, 95% CI 1.01-1.12, p=0.026), discharge to nursing homes (OR 3.57, 95% CI 1.57-8.34, p=0.003), and premature discharge against medical advice (OR 5.05, 95% CI 1.20-21.23, p=0.027) were independent predictors of 15-day readmission risk. The model demonstrated reasonable discrimination on the temporal and geographical validation cohorts with a C-statistic of 0.65 and 0.64, respectively. Model miscalibration was observed in both validation cohorts.
  
  
  
  A 15-day readmission risk prediction model is proposed and externally validated. The model facilitates the targeting of interventions for patients who are at high risk of an early readmission.
authors.affiliation: Department of Pharmacy, National University of Singapore, Singapore.
authors.forename: Sreemanee Raaj
authors.initials: SR
authors.lastname: Dorajoo
authors.affiliation: Department of Pharmacy, National University of Singapore, Singapore.
authors.forename: Vincent
authors.initials: V
authors.lastname: See
authors.affiliation: Department of Pharmacy, National University of Singapore, Singapore.
authors.forename: Chen Teng
authors.initials: CT
authors.lastname: Chan
authors.affiliation: Department of Pharmacy, Khoo Teck Puat Hospital Singapore, Singapore.
authors.forename: Joyce Zhenyin
authors.initials: JZ
authors.lastname: Tan
authors.affiliation: Department of Pharmacy, Khoo Teck Puat Hospital Singapore, Singapore.
authors.forename: Doreen Su Yin
authors.initials: DS
authors.lastname: Tan
authors.affiliation: Department of Pharmacy, Singapore General Hospital, Singapore.
authors.forename: Siti Maryam Binte
authors.initials: SM
authors.lastname: Abdul Razak
authors.affiliation: Department of Pharmacy, Singapore General Hospital, Singapore.
authors.forename: Ting Ting
authors.initials: TT
authors.lastname: Ong
authors.affiliation: Department of Pharmacy, Singapore General Hospital, Singapore.
authors.forename: Narendran
authors.initials: N
authors.lastname: Koomanan
authors.affiliation: Department of Pharmacy, National University of Singapore, Singapore.
authors.forename: Chun Wei
authors.initials: CW
authors.lastname: Yap
authors.affiliation: Department of Pharmacy, National University of Singapore, Singapore.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Chan
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D010351:Patient Discharge; D010359:Patient Readmission / Q000706:statistics & numerical data*; D012307:Risk Factors; D012846:Singapore; D062606:Tertiary Care Centers; D013997:Time Factors
keywords: avoidable readmission; early readmission; external validation; polypharmacy; prediction model