title: Constructing Episodes of Inpatient Care: How to Define Hospital Transfer in Hospital Administrative Health Data?
abstract: BACKGROUND
  Hospital administrative health data create separate records for each hospital stay of patients. Treating a hospital transfer as a readmission could lead to biased results in health service research.
  
  
  METHODS
  This is a cross-sectional study. We used the hospital discharge abstract database in 2013 from Alberta, Canada. Transfer cases were defined by transfer institution code and were used as the reference standard. Four time gaps between 2 hospitalizations (6, 9, 12, and 24 h) and 2 day gaps between hospitalizations [same day (up to 24 h), ≤1 d (up to 48 h)] were used to identify transfer cases. We compared the sensitivity and positive predictive value (PPV) of 6 definitions across different categories of sex, age, and location of residence. Readmission rates within 30 days were compared after episodes of care were defined at the different time gaps.
  
  
  RESULTS
  Among the 6 definitions, sensitivity ranged from 93.3% to 98.7% and PPV ranged from 86.4% to 96%. The time gap of 9 hours had the optimal balance of sensitivity and PPV. The time gaps of same day (up to 24 h) and 9 hours had comparable 30-day readmission rates as the transfer indicator after defining episode of care.
  
  
  CONCLUSIONS
  We recommend the use of a time gap of 9 hours between 2 hospitalizations to define hospital transfer in inpatient databases. When admission or discharge time is not available in the database, a time gap of same day (up to 24 h) can be used to define hospital transfer.
authors.affiliation: *Department of Community Health Sciences †O'Brien Institute for Public Health, University of Calgary ‡Alberta Health Sciences, Calgary, AB, Canada.
authors.forename: Mingkai
authors.initials: M
authors.lastname: Peng
authors.forename: Bing
authors.initials: B
authors.lastname: Li
authors.forename: Danielle A
authors.initials: DA
authors.lastname: Southern
authors.forename: Cathy A
authors.initials: CA
authors.lastname: Eastwood
authors.forename: Hude
authors.initials: H
authors.lastname: Quan
mesh_terms: D000328:Adult; D000368:Aged; D000416:Alberta; D015982:Bias; D003430:Cross-Sectional Studies; D016208:Databases, Factual; D017050:Episode of Care; D005260:Female; D006302:Health Services Research / Q000379:methods*; D006801:Humans; D008297:Male; D008875:Middle Aged; D010351:Patient Discharge / Q000706:statistics & numerical data*; D010359:Patient Readmission / Q000706:statistics & numerical data*; D010360:Patient Transfer / Q000706:statistics & numerical data*; D013997:Time Factors; D055815:Young Adult