Dataset Information

Do Medicaid wage pass-through payments increase nursing home staffing?

ABSTRACT:

Objective

To assess the impact of state Medicaid wage pass-through policy on direct-care staffing levels in U.S. nursing homes.

Data sources

Online Survey Certification and Reporting (OSCAR) data, and state Medicaid nursing home reimbursement policies over the period 1996-2004.

Study design

A fixed-effects panel model with two-step feasible-generalized least squares estimates is used to examine the effect of pass-through adoption on direct-care staff hours per resident day (HPRD) in nursing homes.

Data collection/extraction methods

A panel data file tracking annual OSCAR surveys per facility over the study period is linked with annual information on state Medicaid wage pass-through and related policies.

Principal findings

Among the states introducing wage pass-through over the study period, the policy is associated with between 3.0 and 4.0 percent net increases in certified nurse aide (CNA) HPRD in the years following adoption. No discernable pass-through effect is observed on either registered nurse or licensed practical nurse HPRD.

Conclusions

State Medicaid wage pass-through programs offer a potentially effective policy tool to boost direct-care CNA staffing in nursing homes, at least in the short term.

SUBMITTER: Feng Z

PROVIDER: S-EPMC2875757 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Publications

Do Medicaid wage pass-through payments increase nursing home staffing?

Feng Zhanlian Z Lee Yong Suk YS Kuo Sylvia S Intrator Orna O Foster Andrew A Mor Vincent V

Health services research 20100406 3

<h4>Objective</h4>To assess the impact of state Medicaid wage pass-through policy on direct-care staffing levels in U.S. nursing homes.<h4>Data sources</h4>Online Survey Certification and Reporting (OSCAR) data, and state Medicaid nursing home reimbursement policies over the period 1996-2004.<h4>Study design</h4>A fixed-effects panel model with two-step feasible-generalized least squares estimates is used to examine the effect of pass-through adoption on direct-care staff hours per resident day ...[more]

PMID: 20403054

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Project description:BackgroundLow nursing home staffing in the United States is a growing safety concern. Socioeconomic deprivation in the local areas surrounding a nursing home may be a barrier to improving staffing rates but has been poorly studied. Thus, the objective of this paper was to assess the relationship between neighborhood deprivation and nursing home staffing in the United States.MethodsThis cross-sectional study used 2018 daily payroll-based staffing records and address data for 12,609 nursing homes in the United States linked with resident assessment data. Our primary exposure of interest was severe economic deprivation at the census block group (neighborhood) level, defined as an area deprivation index score ≥85/100. The primary outcome was hours worked per resident-day among nursing home employees providing direct resident care. Marginal linear regression models and generalized estimating equations with robust sandwich-type standard errors were used to estimate associations between severe neighborhood deprivation and staffing rates.ResultsCompared to less deprived neighborhoods, unadjusted staffing rates in facilities located within severely deprived neighborhoods were 38% lower for physical and occupational therapists, 30% lower for registered nurses (RNs), and 5% lower for certified nursing assistants. No disparities in licensed practical nurse (LPN) staffing were observed. In models with state-level and rurality fixed effects and clustered on the county, a similar pattern of disparities was observed. Specifically, RN staffing per 100 resident-days was significantly lower in facilities located within severely deprived neighborhoods as compared to those in less deprived areas (mean difference: 5.6 fewer hours, 95% confidence interval [CI] 4.2-6.9). Disparities of lower magnitude were observed for other clinical disciplines except for LPNs.ConclusionsSignificant staffing disparities were observed within facilities located in severely deprived neighborhoods. Targeted interventions, including workforce recruitment and retention efforts, may be needed to improve staffing levels for nursing homes in deprived neighborhoods.

Project description:ObjectiveTo provide the first plausibly causal national estimates of health outcomes for older dual-eligible recipients of Medicaid HCBS relative to nursing home care and to explore possible mechanisms for the effect.Data sourcesWe use 2005 and 2012 Medicaid Analytic eXtract (MAX), a national compilation of Medicaid claims, merged with Medicare claims to identify hospital admissions, our main outcome variable.Study designWe model the effects of HCBS using a longitudinal instrumental variables framework. To address the endogeneity of HCBS receipt, we instrument for it using the county percentage of nonelderly long-term care users who receive HCBS. The percentage of nonelderly users is highly predictive of HCBS use for an elderly beneficiary, but because the instrument was derived from a separate population, the exclusion restriction is unlikely to be violated.Population studied1,312,498 older adults (65+) dually enrolled in Medicaid and Medicare and are using long-term care. We also examine heterogeneity of effects by race/ethnicity and the presence of dementia.Principal findingsHCBS users have 10 percentage points higher (P < .01) annual rates of hospitalization than their nursing home counterparts when selection bias is addressed; rates of potentially avoidable hospitalizations are 3 percentage points higher (P < .01). These differences persist across races, dementia status, and intensity of HCBS spending.ConclusionsShifting Medicaid long-term care funding for older adults from nursing homes to HCBS, while well-motivated, results in the unintended consequence of substantially higher hospitalization rates for older dual eligibles. The quality and/or quantity of services may be inadequate for some HCBS recipients. Hospitalizations are costly to Medicare but also to the HCBS recipient in terms of stress and risks. Although consumer preferences to remain at home may outweigh poor outcomes of HCBS, the full costs and benefits need to be considered. HCBS outcomes-not just expansion-need more attention.

Project description:BackgroundWide variations in facility staffing may lead to differences in care, and consequently, adverse outcomes such as hospitalizations. However, few studies focused on types of occupations. Therefore, we aimed to examine the association between a wide variety of facility staffing and potentially avoidable hospitalizations of nursing home residents in Japan.MethodsIn this retrospective cohort study using long-term care and medical insurance claims data in Ibaraki Prefecture from April 2018 to March 2019, we identified individuals aged 65 years and above who were newly admitted to nursing homes. In addition, facility characteristic data were obtained from the long-term care insurance service disclosure system. Subsequently, we conducted a multivariable Cox regression analysis and evaluated the association between facility staffing and potentially avoidable hospitalizations.ResultsA total of 2909 residents from 235 nursing homes were included. The cumulative incidence of potentially avoidable hospitalizations at 180 days was 14.2% (95% confidence interval [CI] 12.7-15.8). Facilities with full-time physicians (adjusted hazard ratio [HR]: 0.59, 95% CI: 0.37-0.94) and a higher number of dietitians (HR: 0.72, 95% CI: 0.54-0.97) were significantly associated with a lower likelihood of potentially avoidable hospitalizations. In contrast, having nurses or trained caregivers during the night shift (HR: 1.72, 95% CI: 1.25-2.36) and a higher number of care managers (HR: 1.37, 95% CI: 1.03-1.83) were significantly associated with a high probability of potentially avoidable hospitalizations.ConclusionsWe revealed that variations in facility staffing were associated with potentially avoidable hospitalizations. The results suggest that optimal allocation of human resources, such as dietitians and physicians, may be essential to reduce potentially avoidable hospitalizations. To provide appropriate care to nursing home residents, it is necessary to establish a system to effectively allocate limited resources. Further research is warranted on the causal relationship between staff allocation and unnecessary hospitalizations, considering the confounding factors.

Dataset Information

Do Medicaid wage pass-through payments increase nursing home staffing?

Objective

Data sources

Study design

Data collection/extraction methods

Principal findings

Conclusions

Publications

Do Medicaid wage pass-through payments increase nursing home staffing?

Similar Datasets

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