title: Preventable Admissions on a General Medicine Service: Prevalence, Causes and Comparison with AHRQ Prevention Quality Indicators-A Cross-Sectional Analysis.
abstract: Rates of preventable admissions will soon be publicly reported and used in calculating performance-based payments. The current method of assessing preventable admissions, the Agency of Healthcare Research and Quality (AHRQ) Preventable Quality Indicators (PQI) rate, is drawn from claims data and was originally designed to assess population-level access to care.
  
  
  
  To identify the prevalence and causes of preventable admissions by attending physician review and to compare its performance with the PQI tool in identifying preventable admissions.
  
  
  
  Cross-sectional survey.
  
  
  
  General medicine service at an academic medical center.
  
  
  
  Consecutive inpatient admissions from December 1-15, 2013.
  
  
  
  Survey of inpatient attending physicians regarding the preventability of the admissions, primary contributing factors and feasibility of prevention. For the same patients, the PQI tool was applied to determine the claims-derived preventable admission rate.
  
  
  
  Physicians rated all 322 admissions and classified 122 (38 %) as preventable, of which 31 (25 %) were readmissions. Readmissions were more likely to be rated preventable than other admissions (49 % vs. 35 %, p = 0.04). Application of the AHRQ PQI methodology identified 75 (23 %) preventable admissions. Thirty-one admissions (10 %) were classified as preventable by both methods, and the majority of admissions considered preventable by the AHRQ PQI method (44/78) were not considered preventable by physician assessment (K = 0.04). Of the preventable admissions, physicians assigned patient factors in 54 (44 %), clinician factors in 36 (30 %) and system factors in 32 (26 %).
  
  
  
  A large proportion of admissions to a general medicine service appeared preventable, but AHRQ's PQI tool was unable to identify these admissions. Before initiation of the PQI rate for use in pay-for-performance programs, further study is warranted.
authors.affiliation: Department of Internal Medicine, Medicine Institute, Cleveland Clinic Foundation, Ohio, 9500 Euclid Avenue, Mail Code: NA 10, Cleveland, OH, 44195, USA. patelk11@ccf.org.
authors.forename: Krishna K
authors.initials: KK
authors.lastname: Patel
authors.affiliation: Department of Internal Medicine, Medicine Institute, Cleveland Clinic Foundation, Ohio, 9500 Euclid Avenue, Mail Code: NA 10, Cleveland, OH, 44195, USA.
authors.forename: Nirav
authors.initials: N
authors.lastname: Vakharia
authors.affiliation: Department of Internal Medicine, Medicine Institute, Cleveland Clinic Foundation, Ohio, 9500 Euclid Avenue, Mail Code: NA 10, Cleveland, OH, 44195, USA.
authors.forename: James
authors.initials: J
authors.lastname: Pile
authors.affiliation: Department of Internal Medicine, Medicine Institute, Cleveland Clinic Foundation, Ohio, 9500 Euclid Avenue, Mail Code: NA 10, Cleveland, OH, 44195, USA.|Department of Cardiology, University of Rochester, Rochester, NY, USA.
authors.forename: Erik H
authors.initials: EH
authors.lastname: Howell
authors.affiliation: Department of Internal Medicine, Medicine Institute, Cleveland Clinic Foundation, Ohio, 9500 Euclid Avenue, Mail Code: NA 10, Cleveland, OH, 44195, USA.|Center for Value-Based Care Research, Medicine Institute, Cleveland Clinic, Cleveland, OH, USA.
authors.forename: Michael B
authors.initials: MB
authors.lastname: Rothberg
mesh_terms: D000046:Academic Medical Centers / Q000191:economics / Q000592:standards / Q000706:statistics & numerical data; D000328:Adult; D000368:Aged; D003430:Cross-Sectional Studies; D005240:Feasibility Studies; D005260:Female; D006300:Health Services Misuse / Q000517:prevention & control* / Q000706:statistics & numerical data*; D006302:Health Services Research / Q000379:methods; D006760:Hospitalization / Q000191:economics / Q000706:statistics & numerical data; D006801:Humans; D007388:Internal Medicine / Q000191:economics / Q000592:standards; D008297:Male; D008875:Middle Aged; D010343:Patient Admission / Q000592:standards* / Q000706:statistics & numerical data; D010359:Patient Readmission / Q000592:standards / Q000706:statistics & numerical data; D015995:Prevalence; D019984:Quality Indicators, Health Care; D012052:Reimbursement, Incentive; D062505:Value-Based Purchasing
keywords: preventable admissions; quality indicators; value-based purchasing