title: Metric properties of the appropriateness evaluation protocol and predictors of inappropriate hospital use in Germany: an approach using longitudinal patient data.
abstract: BACKGROUND
  The German health care system, renowned for its unrestricted access, high quality care, and comprehensive coverage, is challenged by increasing health care costs. This has been attributed partly to inefficiencies in the in-patient sector, but has been studied little. Attempts at quality improvement need to relate costs to outcomes. Until now, there has been no standardized methodology to evaluate the appropriateness of hospital care.
  
  
  OBJECTIVE
  To develop and evaluate the metric properties of a method to assess inappropriate hospital care in Germany based on a widely used measure, the Appropriateness Evaluation Protocol (AEP).
  
  
  METHODS
  The original AEP was translated and adapted to reflect differences in the provision of health care in Germany. Psychometric testing was performed in a stratified sample of all patients admitted to the Departments of Medicine and Surgery of a 400-bed teaching hospital during 1 year. Three board-certified physicians participated in each department to evaluate intra-rater reliability, while two additional independent physicians judged inter-rater reliability.
  
  
  RESULTS
  Inter-rater agreement for the evaluation of hospital days among surgical patients was 84% (80-87%), with an average kappa value of 0.58 (0.48-0.68). Corresponding figures for patients in medicine were 76% (73-80%) with a K value of 0.42 (0.34-0.42). Inter-rater agreement for hospital admissions and K was 74% (62-86%) and 0.44 (0.21-0.67) in surgery, and 92% (85-100%) and 0.31 (0-0.80) in medicine, respectively. Thirty-three per cent of all admissions and 28% of consecutive hospital days were judged inappropriate in surgery; among medicine patients, reviewers found 6% of admissions and 33% of hospital days inappropriate. Time since admission was the strongest predictor of inappropriate hospital use adjusted for length of stay, comorbidity, age, and gender.
authors.affiliation: Department of Health Policy and Management, Harvard School of Public Health, Boston, MA, USA.
authors.forename: Oliver
authors.initials: O
authors.lastname: Sangha
authors.forename: Sebastian
authors.initials: S
authors.lastname: Schneeweiss
authors.forename: Manfred
authors.initials: M
authors.lastname: Wildner
authors.forename: E Francis
authors.initials: EF
authors.lastname: Cook
authors.forename: Troyen A
authors.initials: TA
authors.lastname: Brennan
authors.forename: Jens
authors.initials: J
authors.lastname: Witte
authors.forename: Matthew H
authors.initials: MH
authors.lastname: Liang
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D015897:Comorbidity; D003211:Concurrent Review / Q000379:methods*; D005260:Female; D005858:Germany; D006285:Health Planning; D006300:Health Services Misuse / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data*; D006784:Hospitals, Teaching / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D020380:Needs Assessment / Q000592:standards*; D015588:Observer Variation; D010343:Patient Admission / Q000706:statistics & numerical data; D015397:Program Evaluation / Q000592:standards; D011594:Psychometrics; D017678:Sex Distribution