title: Improving the home health acute-care hospitalization quality measure.
abstract: OBJECTIVE
  (1) To demonstrate average length of service (ALOS) bias in the currently used acute-care hospitalization (ACH) home health quality measure, limiting comparability across agencies, and (2) to propose alternative ACH measures.
  
  
  METHODS
  Secondary analysis of Medicare home health service data 2004-2007; convenience sample of Medicare fee-for-service hospital discharges.
  
  
  METHODS
  Cross-sectional analysis and patient-level simulation.
  
  
  METHODS
  We aggregated outcome and ALOS data from 2,347 larger Medicare-certified home health agencies (HHAs) in the United States between 2004 and 2007, and calculated risk-adjusted monthly ACH rates. We used multiple regression to identify agency characteristics associated with ACH. We simulated ACH during and immediately after home health care using patient and agency characteristics similar to those in the actual data, comparing the existing measure with alternative fixed-interval measures.
  
  
  RESULTS
  Of agency characteristics studied, ALOS had by far the highest partial correlation with the current ACH measure (r(2)=0.218, p<.0001). We replicated the correlation between ACH and ALOS in the patient-level simulation. We found no correlation between ALOS and the alternative measures.
  
  
  CONCLUSIONS
  Alternative measures do not exhibit ALOS bias and would be appropriate for comparing HHA ACH rates with one another or over time.
authors.affiliation: West Virginia Medical Institute, 3001 Chesterfield Ave., Charleston, WV 25304, USA. cschade@wvmi.org
authors.forename: Charles P
authors.initials: CP
authors.lastname: Schade
authors.forename: John G
authors.initials: JG
authors.lastname: Brehm
mesh_terms: D000208:Acute Disease; D000704:Analysis of Variance; D015982:Bias; D003430:Cross-Sectional Studies; D017050:Episode of Care; D018588:Fee-for-Service Plans; D006302:Health Services Research; D006699:Home Care Services / Q000458:organization & administration*; D006801:Humans; D007344:Insurance Claim Reporting; D007902:Length of Stay / Q000706:statistics & numerical data*; D016014:Linear Models; D016015:Logistic Models; D006278:Medicare; D017063:Outcome Assessment, Health Care; D010351:Patient Discharge; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011237:Predictive Value of Tests; D019984:Quality Indicators, Health Care / Q000458:organization & administration*; D020379:Risk Adjustment / Q000458:organization & administration*; D013997:Time Factors; D017749:Total Quality Management; D014481:United States
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