Potentially avoidable hospitalizations for elderly long-stay residents in nursing homes

Med Care. 2013 Aug;51(8):673-81. doi: 10.1097/MLR.0b013e3182984bff.


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.

Method: 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.

Subjects: 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.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Comorbidity
  • Female
  • Geriatric Assessment
  • Health Policy
  • Homes for the Aged / organization & administration
  • Homes for the Aged / statistics & numerical data*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Male
  • Nursing Homes / organization & administration
  • Nursing Homes / statistics & numerical data*
  • Patient Acuity*
  • Proportional Hazards Models
  • Risk Factors
  • State Government
  • Time Factors
  • United States