title: Potentially avoidable hospitalizations for elderly long-stay residents in nursing homes.
abstract: BACKGROUND
  Hospitalizations of long-stay nursing home (NH) residents are common. The high estimates of potentially avoidable hospitalizations in NHs suggest that efforts to reduce avoidable hospitalizations may be effective in lowering health care expenditures as well as improving the quality of care for NH residents.
  
  
  OBJECTIVE
  To determine the relationship between clinical risk factors, facility characteristics and State policy variables, and both avoidable and unavoidable hospitalizations.
  
  
  METHODS
  Hospitalization risk is estimated using competing risks proportional hazards regressions. Three hospitalization measures were constructed: (1) ambulatory care-sensitive conditions (ACSCs); (2) additional NH-sensitive avoidable conditions (ANHACs); and (3) nursing home "unavoidable" conditions (NHUCs). In all models, we include clinical risk factors, facility characteristics, and State policy variables that may influence the decision to hospitalize.
  
  
  METHODS
  The population of interest is a cohort of long-stay NH residents. Data are from the Nursing Home Stay file, a sample of residents in 10% of certified NHs in the United States (2006-2008).
  
  
  RESULTS
  Three fifths of hospitalizations were potentially avoidable and the majority was for infections, injuries, and congestive heart failure. Clinical risk factors include renal disease, diabetes, and a high number of medications among others. Staffing, quality, and reimbursement affect avoidable, but not unavoidable hospitalizations.
  
  
  CONCLUSIONS
  A NH-sensitive measure of avoidable hospitalizations identifies both clinical facility and policy risk factors, emphasizing the potential for both reimbursement and clinical strategies to reduce hospitalizations from NHs.
authors.affiliation: Agency for Healthcare Research & Quality, Rockville, MD 20850, USA. William.Spector@ahrq.hhs.gov
authors.forename: William D
authors.initials: WD
authors.lastname: Spector
authors.forename: Rhona
authors.initials: R
authors.lastname: Limcangco
authors.forename: Christianna
authors.initials: C
authors.lastname: Williams
authors.forename: William
authors.initials: W
authors.lastname: Rhodes
authors.forename: Donna
authors.initials: D
authors.lastname: Hurd
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015897:Comorbidity; D005260:Female; D015577:Geriatric Assessment; D006291:Health Policy; D006707:Homes for the Aged / Q000458:organization & administration / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D009735:Nursing Homes / Q000458:organization & administration / Q000706:statistics & numerical data*; D062072:Patient Acuity; D016016:Proportional Hazards Models; D012307:Risk Factors; D013219:State Government; D013997:Time Factors; D014481:United States