title: Factors affecting unplanned readmissions from community hospitals to acute hospitals: a prospective observational study.
abstract: BACKGROUND
  While the readmission rate from community hospitals is known, the factors affecting it are not. Our aim was to determine the factors predicting unplanned readmissions from community hospitals (CHs) to acute hospitals (AHs).
  
  
  METHODS
  This was an observational prospective cohort study, involving 842 patients requiring post-acute rehabilitation in 2 CHs admitted from 3 AHs in Singapore. We studied the role of the Cumulative Illness Rating Scale (CIRS) organ impairment scores, the Mini-mental State Examination (MMSE) score, the Shah modified Barthel Index (BI) score, and the triceps skin fold thickness (TSFT) in predicting the rate of unplanned readmissions (UR), early unplanned readmissions (EUPR) and late unplanned readmissions (LUPR). We developed a clinical prediction rule to determine the risk of UR and EUPR.
  
  
  RESULTS
  The rates of EUPR and LUPR were 7.6% and 10.3% respectively. The factors that predicted UR were the CIRS-heart score, the CIRS-haemopoietic score, the CIRS-endocrine / metabolic score and the BI on admission. The MMSE was predictive of EUPR. The TSFT and CIRS-liver score were predictive of LUPR. Upon receiver operator characteristics analysis, the clinical prediction rules for the prediction of EUPR and UR had areas under the curve of 0.745 and 0.733 respectively. The likelihood ratios of the clinical prediction rules for EUPR and UR ranged from 0.42 to 5.69 and 0.34 to 3.16 respectively.
  
  
  CONCLUSIONS
  Patients who have UR can be identified by the admission BI, the MMSE, the TSFT and CIRS scores in the cardiac, haemopoietic, liver and endocrine/metabolic systems.
authors.affiliation: Department of Geriatric Medicine, Tan Tock Seng Hospital, Singapore. ian_leong@ttsh.com.sg
authors.forename: Ian Y O
authors.initials: IY
authors.lastname: Leong
authors.forename: Siew-Pang
authors.initials: SP
authors.lastname: Chan
authors.forename: Boon-Yeow
authors.initials: BY
authors.lastname: Tan
authors.forename: Yih-Yiow
authors.initials: YY
authors.lastname: Sitoh
authors.forename: Yan-Hoon
authors.initials: YH
authors.lastname: Ang
authors.forename: Reshma
authors.initials: R
authors.lastname: Merchant
authors.forename: Kala
authors.initials: K
authors.lastname: Kanagasabai
authors.forename: Patricia S Y
authors.initials: PS
authors.lastname: Lee
authors.forename: Weng-Sun
authors.initials: WS
authors.lastname: Pang
mesh_terms: D000208:Acute Disease / Q000628:therapy; D000368:Aged; D005260:Female; D005500:Follow-Up Studies; D006764:Hospitals, Community / Q000706:statistics & numerical data*; D006782:Hospitals, Special / Q000706:statistics & numerical data*; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data; D008297:Male; D010359:Patient Readmission / Q000639:trends*; D011446:Prospective Studies; D012307:Risk Factors; D012720:Severity of Illness Index; D012846:Singapore