title: Derivation and validation of a formula to estimate risk for 30-day readmission in medical patients.
abstract: OBJECTIVE
  To create a simple readmission risk-prediction tool that can be generated easily at the bedside by physicians, nurses, care coordinators and discharge planners.
  
  
  METHODS
  Retrospective cohort study.
  
  
  METHODS
  Tertiary academic medical center.
  
  
  METHODS
  Inpatients aged 18 and older on general internal medicine services.
  
  
  METHODS
  Predictor variables included age, prior hospitalization, high-risk diagnoses, high-risk medications, polypharmacy, depression, use of palliative care and a cumulative score summing these factors (readmission risk score-RRS). The main outcome measure was 30-day readmission. Predictive values were calculated.
  
  
  RESULTS
  Readmission increased linearly from 4.9% of those whose RRS score was 0-37.5% of those with highest risk scores (P = 0.0002). We derived a simple formula for readmission risk as 8 and 4% more for each additional readmission risk factor. The positive predictive value for RRS >0 was low, while the negative predictive value for this cutoff was 95%.
  
  
  CONCLUSIONS
  An easily calculated 7-point score can be used to estimate readmission risk. This tool may be particularly useful for identifying lower risk patients who may not require intensive intervention, thus aiding in appropriate targeting of resources.
authors.affiliation: Division of General and Geriatric Medicine, University of Kansas School of Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
authors.forename: Mohammad
authors.initials: M
authors.lastname: Taha
authors.affiliation: Division of General and Geriatric Medicine, University of Kansas School of Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
authors.forename: Aroop
authors.initials: A
authors.lastname: Pal
authors.affiliation: Department of Biostatistics, University of Kansas School of Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
authors.forename: Jonathan D
authors.initials: JD
authors.lastname: Mahnken
authors.affiliation: Division of General and Geriatric Medicine, University of Kansas School of Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
authors.forename: Sally K
authors.initials: SK
authors.lastname: Rigler
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D015897:Comorbidity; D003863:Depression / Q000453:epidemiology; D005260:Female; D006701:Home Nursing; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D007388:Internal Medicine; D008297:Male; D008875:Middle Aged; D010166:Palliative Care; D010359:Patient Readmission / Q000706:statistics & numerical data*; D019338:Polypharmacy; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D014481:United States / Q000453:epidemiology
keywords: adult; comorbidity; patient readmission; polypharmacy; risk prediction