Browse
Submit Data
Databases
API
Help

Dataset Information

20 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A Bayesian procedure for estimating the causal effects of nursing home bed-hold policy.

ABSTRACT: Nursing home bed-hold policies provide continuity of care for Medicaid beneficiaries by paying nursing homes to reserve beds so residents can return to their facility of occupancy following an acute hospitalization. In 2001, Michigan implemented bed-hold policies in nursing homes. We investigated the impact of these policies on mortality and hospitalizations using 1999-2004 quarterly data from nursing homes in Michigan and nursing homes in 11 states that did not implement such policies. Synthetic Control has been used to estimate the effects of policies by accounting for changes over time unrelated to the intervention. Synthetic Control is intended for scalar continuous outcome at each period, and assumes a single treated unit and multiple control units. We propose a Bayesian procedure to overcome these limitations. It imputes the outcomes of nursing homes in Michigan if they were not exposed to the policy by matching to non-exposed nursing homes that are associated with the exposed ones in the pre-policy period. Because sampling from a Bayesian model is computationally challenging, we describe an approximation procedure that can be implemented using existing software. Our approach can be applied to other studies that examine the impact of policies.

SUBMITTER: Gutman R

PROVIDER: S-EPMC6180940 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Medicaid bed-hold policy and Medicare skilled nursing facility rehospitalizations.

Project description:ObjectiveTo analyze the effect of states' Medicaid bed-hold policies on the 30-day rehospitalization of Medicare postacute skilled nursing facility (SNF) residents.Data sourcesMinimum data set assessments were merged with Medicare claims and eligibility files for all first-time SNF admissions (N = 3,322,088) over the period 2000 through 2005; states' Medicaid bed-hold policies were obtained via survey.Study designRegression specification incorporating facility fixed effects to examine changes in Medicaid bed-hold policies on the likelihood of a 30-day SNF rehospitalization.Principal findingsUsing a continuous measure of bed-hold generosity, state Medicaid bed-hold was positively related to Medicare SNF rehospitalization. Specifically, the introduction of a bed-hold policy with average generosity increases Medicare rehospitalizations by 1.8 percent, representing roughly 12,000 SNF rehospitalizations at a cost to Medicare of approximately U.S.$100 million over our study period.ConclusionsAlthough facilities do not receive a Medicaid bed-hold payment for Medicare SNF stays, we found that the adoption of more generous policies led to greater SNF rehospitalizations. This type of spillover is largely ignored in current discussions of Medicare payment reforms such as bundled payment. Neither Medicare nor Medicaid has an incentive to internalize the risks and benefits of its actions as they affect the other.

| S-EPMC3029851 | biostudies-literature

Medicaid bed-hold policies and hospitalization of long-stay nursing home residents.

Project description:ObjectiveTo 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.ConclusionsMedicaid bed-hold policies may increase the likelihood of hospitalization of long-stay nursing home residents and increase costs for the federal Medicare program.

| S-EPMC3737418 | biostudies-literature

Maintaining continuity of care for nursing home residents: effect of states' Medicaid bed-hold policies and reimbursement rates.

Project description:Recent public concern in response to states' intended repeal of Medicaid bed-hold policies and report of their association with higher hospitalization rates prompts examination of these policies in ensuring continuity of care within the broader context of Medicaid policies.Minimum Data Set assessments of long-stay nursing home residents in April-June 2000 linked to Medicare claims enabled tracking residents' hospitalizations during the ensuing 5 months and determining hospital discharge destination. Multinomial multilevel models estimated the effect of state policies on discharge destination controlling for resident, hospitalization, nursing home, and market characteristics.Among 77,955 hospitalizations, 5,797 (7.4 percent) were not discharged back to the baseline nursing home. Bed-hold policies were associated with lower odds of transfer to another nursing home (AOR=0.55, 95 percent CI 0.52-0.58) and higher odds of hospitalization (AOR=1.36), translating to 9.5 fewer nursing home transfers and 77.9 more hospitalizations per 1,000 residents annually, and costing Medicaid programs about $201,311. Higher Medicaid reimbursement rates were associated with lower odds of transfer.Bed-hold policies were associated with greater continuity of NH care; however, their high cost compared with their small impact on transfer but large impact on increased hospitalizations suggests that they may not be effective.

| S-EPMC2669621 | biostudies-literature

Nursing home study

Project description:Prevalence of multidrug resistant organisms (MDRO) in nursing homes in Ireland and the Netherlands

| PRJEB31196 | ENA

A MULTIPLE IMPUTATION PROCEDURE FOR RECORD LINKAGE AND CAUSAL INFERENCE TO ESTIMATE THE EFFECTS OF HOME-DELIVERED MEALS

Project description:Causal analysis of observational studies requires data that comprise of a

| S-EPMC9222523 | biostudies-literature

Nursing home aversion post-pandemic: Implications for savings and long-term care policy.

Project description:COVID-19 outbreaks at nursing homes during the recent pandemic have received ample media coverage and may have lasting negative impacts on individuals' perception of nursing homes. We argue that this could have sizable and persistent implications for savings and long-term care policies. Our theoretical model predicts that higher nursing home aversion should induce higher savings and stronger support for policies subsidizing home care. Based on a survey of Canadians aged 50 to 69, we document that higher nursing home aversion is widespread: 72% of respondents are less inclined to enter a nursing home because of the pandemic. Consistent with our model, we find that these respondents are more likely to have higher intended savings for old age because of the pandemic. We also find that they are more likely to strongly support home care subsidies.

| S-EPMC9303513 | biostudies-literature

Testing the bed-blocking hypothesis: does nursing and care home supply reduce delayed hospital discharges?

Project description:Hospital bed-blocking occurs when hospital patients are ready to be discharged to a nursing home, but no place is available, so that hospital care acts as a more costly substitute for long-term care. We investigate the extent to which greater supply of nursing home beds or lower prices can reduce hospital bed-blocking using a new Local Authority (LA) level administrative data from England on hospital delayed discharges in 2009-2013. The results suggest that delayed discharges respond to the availability of care home beds, but the effect is modest: an increase in care home beds by 10% (250 additional beds per LA) would reduce social care delayed discharges by about 6-9%. We also find strong evidence of spillover effects across LAs: more care home beds or fewer patients aged over 65?years in nearby LAs are associated with fewer delayed discharges.

| S-EPMC4406135 | biostudies-literature

Estimating the Effect of Influenza Vaccination on Nursing Home Residents' Morbidity and Mortality.

Project description:To estimate the effect of influenza vaccination on hospitalization and mortality in nursing home (NH) residents.Retrospective cohort study.Medicare claims data linked to NH Minimum Data Set assessments and Centers for Disease Control and Prevention (CDC) surveillance data from 122 U.S. cities.More than 1 million Medicare fee-for-service, long-stay NH residents between 2000 and 2009.Weekly facility outcome aggregates of NH resident pneumonia and influenza (P&I) hospitalizations and all-cause mortality and city-level P&I mortality as reported by the CDC were created. The seasonal vaccine match rate for influenza A/H1N1, A/H3N2, and B strains was calculated, and each outcome was compared in seasons of high and low match rates using facility fixed-effects regression models separately for full-year and nonsummer months.Average weekly all-cause mortality varied across seasons from 3.74 to 4.13 per 1,000 NH residents per week, and hospitalization for P&I varied from 2.05 to 2.43. Vaccine match rates were invariably high for H1N1 but variable across seasons for the other two types. The association between vaccine match and reduction in overall mortality and P&I hospitalizations was strongest for A/H3N2, the influenza strain typically responsible for the most-severe influenza cases. Given the approximately 130,000 deaths and 77,000 P&I hospitalizations of long-stay NH residents during the 32 nonsummer weeks, the model estimated that a 50-percentage-point increase in the A/H3N2 match rate (from <25% to >75%) reduced long-stay NH resident deaths by 2.0% and P&I hospitalizations by 4.2%.Well-matched influenza vaccine prevents P&I hospitalizations and mortality in NH residents.

| S-EPMC4762025 | biostudies-literature

Estimating Causal Effects of Particulate Matter Regulation on Mortality.

Project description:BackgroundEstimating the causal effect of pollution on human health is integral for evaluating returns to pollution regulation, yet separating out confounding factors remains a perennial challenge.MethodsWe use a quasi-experimental design to investigate the causal relationship between regulation of particulate matter smaller than 2.5 micrograms per cubic meter (PM2.5) and mortality among those 65 years of age and older. We exploit regulatory changes in the Clean Air Act Amendments (CAAA). Regulation in 2005 impacted areas of the United States differentially based on pre-regulation air quality levels for PM2.5. We use county-level mortality data, extracted from claims data managed by the Centers for Medicare & Medicaid Services, merged to county-level average PM2.5 readings and attainment status as classified by the Environmental Protection Agency.ResultsBased on estimates from log-linear difference-in-differences models, our results indicate after the CAAA designation for PM2.5 in 2005, PM2.5 levels decreased 1.59 micrograms per cubic meter (95% CI = 1.39, 1.80) and mortality rates among those 65 and older decreased by 0.93% (95% CI = 0.10%, 1.77%) in nonattainment counties, relative to attainment ones. Results are robust to a series of alternate models, including nearest-neighbor matching based on propensity score estimates.ConclusionThis analysis suggests large health returns to the 2005 PM2.5 designations, and provides evidence of a causal association between pollution and mortality among the Medicare population.

| S-EPMC7880579 | biostudies-literature

Optimizing matching and analysis combinations for estimating causal effects.

Project description:Matching methods are common in studies across many disciplines. However, there is limited evidence on how to optimally combine matching with subsequent analysis approaches to minimize bias and maximize efficiency for the quantity of interest. We conducted simulations to compare the performance of a wide variety of matching methods and analysis approaches in terms of bias, variance, and mean squared error (MSE). We then compared these approaches in an applied example of an employment training program. The results indicate that combining full matching with double robust analysis performed best in both the simulations and the applied example, particularly when combined with machine learning estimation methods. To reduce bias, current guidelines advise researchers to select the technique with the best post-matching covariate balance, but this work finds that such an approach does not always minimize mean squared error (MSE). These findings have important implications for future research utilizing matching. To minimize MSE, investigators should consider additional diagnostics, and use of simulations tailored to the study of interest to identify the optimal matching and analysis combination.

| S-EPMC4793248 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data