title: Variation in length of stay and outcomes among hospitalized patients attributable to hospitals and hospitalists.
abstract: BACKGROUND
  There have been no prior population-based studies of variation in performance of hospitalists.
  
  
  OBJECTIVE
  To measure the variation in performance of hospitalists.
  
  
  METHODS
  Retrospective research design of 100 % Texas Medicare data using multilevel, multivariable models.
  
  
  METHODS
  131,710 hospitalized patients cared for by 1,099 hospitalists in 268 hospitals from 2006-2009.
  
  
  METHODS
  We calculated, for each hospitalist, adjusted for patient and disease factors (case mix), their patients' average length of stay, rate of discharge home or to skilled nursing facility (SNF) and rate of 30-day mortality, readmissions and emergency room (ER) visits.
  
  
  RESULTS
  In two-level models (admission and hospitalist), there was significant variation in average length of stay and discharge location among hospitalists, but very little variation in 30-day mortality, readmission or emergency room visit rates. There was stability over time (2008-2009 vs. 2006-2007) in hospitalist performance. In three-level models including admissions, hospitalists and hospitals, the variation among hospitalists was substantially reduced. For example, hospitals, hospitalists and case mix contributed 1.02 %, 0.75 % and 42.15 % of the total variance in 30-day mortality rates, respectively.
  
  
  CONCLUSIONS
  There is significant variation among hospitalists in length of stay and discharge destination of their patients, but much of the variation is attributable to the hospitals where they practice. The very low variation among hospitalists in 30-day readmission rates suggests that hospitalists are not important contributors to variations in those rates among hospitals.
authors.affiliation: Department of Medicine and Sealy Center on Aging, University of Texas Medical Branch, Galveston, TX, USA. jsgoodwi@utmb.edu
authors.forename: James S
authors.initials: JS
authors.lastname: Goodwin
authors.forename: Yu-Li
authors.initials: YL
authors.lastname: Lin
authors.forename: Siddhartha
authors.initials: S
authors.lastname: Singh
authors.forename: Yong-Fang
authors.initials: YF
authors.lastname: Kuo
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002983:Clinical Competence; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D005260:Female; D006302:Health Services Research / Q000379:methods; D020445:Hospitalists / Q000592:standards*; D006760:Hospitalization / Q000706:statistics & numerical data; D006761:Hospitals / Q000592:standards* / Q000706:statistics & numerical data; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data; D008875:Middle Aged; D009026:Mortality; D017063:Outcome Assessment, Health Care / Q000379:methods; D010351:Patient Discharge / Q000706:statistics & numerical data; D010359:Patient Readmission / Q000706:statistics & numerical data; D012189:Retrospective Studies; D020379:Risk Adjustment; D013781:Texas / Q000453:epidemiology; D014481:United States