Medicaid Bed-Hold Policies and Hospitalization of Long-Stay Nursing Home Residents

Weill Cornell Medical College, 425 East 61st Street, Suite 301, New York, NY, 10065.
Health Services Research (Impact Factor: 2.78). 03/2013; 48(5). DOI: 10.1111/1475-6773.12054
Source: PubMed


To evaluate the effect of Medicaid bed-hold policies on hospitalization of long-stay nursing home residents. Data SourcesA nationwide random sample of long-stay nursing home residents with data elements from Medicare claims and enrollment files, the Minimum Data Set, the Online Survey Certification and Reporting System, and Area Resource File. The sample consisted of 22,200,089 person-quarters from 754,592 individuals who became long-stay residents in 17,149 nursing homes over the period beginning January 1, 2000 through December 31, 2005. Study DesignLinear regression models using a pre/post design adjusted for resident, nursing home, market, and state characteristics. Nursing home and year-quarter fixed effects were included to control for time-invariant facility influences and temporal trends associated with hospitalization of long-stay residents. Principal FindingsAdoption of a Medicaid bed-hold policy was associated with an absolute increase of 0.493 percentage points (95% CI: 0.039-0.946) in hospitalizations of long-stay nursing home residents, representing a 3.883 percent relative increase over the baseline mean. Conclusions
Medicaid bed-hold policies may increase the likelihood of hospitalization of long-stay nursing home residents and increase costs for the federal Medicare program.

27 Reads
  • [Show abstract] [Hide abstract]
    ABSTRACT: To analyze the relationship between length of stay and rehospitalization. Retrospective cohort study. Six thousand five hundred thirty-seven hospitals nationwide from January 1999 through September 2005. Medicare fee-for-service beneficiaries associated with 2,101,481 hospitalizations. Thirty-day rehospitalization derived from Medicare hospital claims using the implementation of Medicare's post-acute care transfer policy as a quasi-experiment. Medicare's post-acute care transfer policy led to immediate declines in length of stay. A 1-day decrease in length of stay was associated with an absolute increase in 30-day rehospitalization of 1.56 percentage points (95% confidence interval (CI) = 0.30-2.82) for acute myocardial infarction (AMI) with major complications and 0.81 percentage points (95% CI = 0.03-1.60) for kidney infection or urinary tract infection (UTI) without major complications. Individuals hospitalized for AMI without major complications, heart failure, or kidney infection or UTI with major complications had no increase in 30-day rehospitalization. A 1-day reduction in hospital length of stay was not consistently associated with a higher rate of rehospitalization.
    Journal of the American Geriatrics Society 08/2013; 61(9). DOI:10.1111/jgs.12411 · 4.57 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Hospitalizations among nursing home residents are frequent, expensive, and often associated with further deterioration of resident condition. The literature indicates that a substantial fraction of admissions is potentially preventable and that nonprofit nursing homes are less likely to hospitalize their residents. However, the correlation between ownership and hospitalization might reflect unobserved resident differences rather than a causal relationship. Using national minimum data set assessments linked with Medicare claims, we use a national cohort of long-stay residents who were newly admitted to nursing homes within an 18-month period spanning January 1, 2004 and June 30, 2005. After instrumenting for ownership status, we found that IV estimates of the effect of nonprofit ownership on hospitalization are at least as large as the non-instrumented effects, indicating that selection bias does not explain the observed relationship. We also found evidence suggesting the lower rate of hospitalizations among nonprofits was due to a different threshold for transfer.
    International Journal of Health Care Finance and Economics 11/2013; 14(1). DOI:10.1007/s10754-013-9136-3 · 0.49 Impact Factor