The Metrics Matter: Improving Comparisons of COVID-19 Outbreaks in Nursing Homes.

OBJECTIVES: In the United States, nursing facility residents comprise fewer than 1% of the population but more than 40% of deaths due to Coronavirus Disease 2019 (COVID-19). Mitigating the enormous risk of COVID-19 to nursing home residents requires adequate data. The widely used Centers for Medicare & Medicaid Services (CMS) COVID-19 Nursing Home Dataset contains 2 derived statistics: Total Resident Confirmed COVID-19 Cases per 1000 Residents and Total Resident COVID-19 Deaths per 1000 Residents. These metrics provide a misleading picture, as facilities report cumulative counts of cases and deaths over different time periods but use a point-in-time measure as proxy for number of residents (number of occupied beds in a week), resulting in inflated statistics. We propose an alternative statistic to better illustrate the burden of COVID-19 cases and deaths across nursing facilities. DESIGN: Retrospective cohort study. SETTING AND PARTICIPANTS: Using the CMS Nursing Home Compare and COVID-19 Nursing Home Datasets, we examined facilities with star ratings and COVID-19 data passing quality assurance checks for each reporting period from May 31 to August 16, 2020 (n = 11,115). METHODS: We derived an alternative measure of the number of COVID-19 cases per 1000 residents using the net change in weekly census. For each measure, we compared predicted number of cases/deaths by overall star rating using negative binomial regression with constant dispersion, controlling for county-level cases per capita and nursing home characteristics. RESULTS: The average number of cases per 1000 estimated residents using our method is lower compared with the metric using occupied beds as proxy for number of residents (44.8 compared with 66.6). We find similar results when examining number of COVID-19 deaths per 1000 residents. CONCLUSIONS AND IMPLICATIONS: Future research should estimate the number of residents served in nursing facilities when comparing COVID-19 cases/deaths in nursing facilities. Identifying appropriate metrics for facility-level comparisons is critical to protecting nursing home residents as the pandemic continues.

Factors Associated With Racial Differences in Deaths Among Nursing Home Residents With COVID-19 Infection in the US.

Importance: It is important to understand differences in coronavirus disease 2019 (COVID-19) deaths by nursing home racial composition and the potential reasons for these differences so that limited resources can be distributed equitably. Objective: To describe differences in the number of COVID-19 deaths by nursing home racial composition and examine the factors associated with these differences. Design, Setting, and Participants: This cross-sectional study of 13 312 nursing homes in the US used the Nursing Home COVID-19 Public File from the Centers for Medicare and Medicaid Services, which contains COVID-19 cases and deaths among nursing home residents as self-reported by nursing homes beginning between January 1, 2020, and May 24, 2020, and ending on September 13, 2020. Data were analyzed from July 28 to December 18, 2020. Exposures: Confirmed or suspected COVID-19 infection. Confirmed cases were defined as COVID-19 infection confirmed by a diagnostic laboratory test. Suspected cases were defined as signs and/or symptoms of COVID-19 infection or patient-specific transmission-based precautions for COVID-19 infection. Main Outcomes and Measures: Deaths associated with COVID-19 among nursing home residents. Death counts were compared by nursing home racial composition, which was measured as the proportion of White residents. Results: Among 13 312 nursing homes included in the study, the overall mean (SD) age of residents was 79.5 (6.7) years. A total of 51 606 COVID-19-associated deaths among residents were reported, with a mean (SD) of 3.9 (8.0) deaths per facility. The mean (SD) number of deaths in nursing homes with the lowest proportion of White residents (quintile 1) vs nursing homes with the highest proportions of White residents (quintile 5) were 5.6 (9.2) and 1.7 (4.8), respectively. Facilities in quintile 1 experienced a mean (SE) of 3.9 (0.2) more deaths than those in quintile 5, representing a 3.3-fold higher number of deaths in quintile 1 compared with quintile 5. Adjustment for the number of certified beds reduced the mean (SE) difference between these 2 nursing home groups to 2.2 (0.2) deaths. Controlling for case mix measures and other nursing home characteristics did not modify this association. Adjustment for county-level COVID-19 prevalence further reduced the mean (SE) difference to 1.0 (0.2) death. Conclusions and Relevance: In this study, nursing homes with the highest proportions of non-White residents experienced COVID-19 death counts that were 3.3-fold higher than those of facilities with the highest proportions of White residents. These differences were associated with factors such as larger nursing home size and higher infection burden in counties in which nursing homes with high proportions of non-White residents were located. Focusing limited available resources on facilities with high proportions of non-White residents is needed to support nursing homes during potential future outbreaks.

Outcomes of Medicaid home- and community-based long-term services relative to nursing home care among dual eligibles.

OBJECTIVE: To 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 SOURCES: We 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 DESIGN: We 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 STUDIED: 1,312,498 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 FINDINGS: HCBS 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. CONCLUSIONS: Shifting 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.

Staffing Levels and COVID-19 Cases and Outbreaks in U.S. Nursing Homes.

BACKGROUND/OBJECTIVES: Nursing homes have experienced a disproportionate share of COVID-19 cases and deaths. Early analyses indicated that baseline quality was not predictive of nursing home cases, but a more nuanced study of the role of nurse staffing is needed to target resources and better respond to future outbreaks. We sought to understand whether baseline nurse staffing is associated with the presence of COVID-19 in nursing homes and whether staffing impacts outbreak severity. DESIGN: We analyzed Centers for Medicare & Medicaid Services (CMS) facility-level data on COVID-19 cases and deaths merged with nursing home and county characteristics. We used logistic regressions to examine the associations of staffing levels from Nursing Home Compare with the outcomes of any COVID-19 cases and, conditional on at least one case, an outbreak. Among facilities with at least one case, we modeled count of deaths using hurdle negative binomial-2 regressions. SETTING: All nursing homes in the CMS COVID-19 Nursing Home Dataset with reports that passed the CMS Quality Assurance Check as of June 25, 2020. PARTICIPANTS: Residents of nursing homes that met COVID-19 reporting requirements. MEASUREMENTS: A nursing home is defined as having at least one case is if one or more confirmed or suspected COVID-19 case among residents or staff is reported. Conditional on at least one case, we examine two outcomes: an outbreak, defined as confirmed cases/certified beds >10% or total confirmed and suspected cases/beds >20% or >10 deaths, and the total number of deaths attributed to COVID-19 among residents and staff. RESULTS: A total of 71% of the 13,167 nursing homes that reported COVID-19 data as of June 14 had at least one case among residents and/or staff. Of those, 27% experienced an outbreak. Higher registered nurse-hours are associated with a higher probability of experiencing any cases. However, among facilities with at least one case, higher nurse aide (NA) hours and total nursing hours are associated with a lower probability of experiencing an outbreak and with fewer deaths. The strongest predictor of cases and outbreaks in nursing homes is per capita cases in the county. CONCLUSION: The prevalence of COVID-19 in the community remains the strongest predictor of COVID-19 cases and deaths in nursing homes, but higher NA hours and total nursing hours may help contain the number of cases and deaths.

A National Examination Of Long-Term Care Setting, Outcomes, And Disparities Among Elderly Dual Eligibles.

The benefits of expanding funding for Medicaid long-term care home and community-based services (HCBS) relative to institutional care are often taken as self-evident. However, little is known about the outcomes of these services, especially for racial and ethnic minority groups, whose members tend to use the services more than whites do, and for people with dementia who may need high-intensity care. Using national Medicaid claims data on older adults enrolled in both Medicare and Medicaid, we found that overall hospitalization rates were similar for HCBS and nursing facility users, although nursing facility users were generally sicker as reflected in their claims history. Among HCBS users, blacks were more likely to be hospitalized than non-Hispanic whites were, and the gap widened among blacks and whites with dementia. Also, conditional on receiving HCBS, Medicaid HCBS spending was higher for whites than for nonwhites, and higher Medicare and Medicaid hospital spending for blacks and Hispanics did not offset this difference. Our findings suggest that home and community-based services need to be carefully targeted to avoid adverse outcomes and that the racial/ethnic disparities in access to high-quality institutional long-term care are also present in HCBS. Policy makers should consider the full costs and benefits of shifting care from nursing facilities to home and community settings and the potential implications for equity.

Identifying Older Adults with Serious Illness: A Critical Step toward Improving the Value of Health Care.

OBJECTIVE: To create and test three prospective, increasingly restrictive definitions of serious illness. DATA SOURCES: Health and Retirement Study, 2000-2012. STUDY DESIGN: We evaluated subjects' 1-year outcomes from the interview date when they first met each definition: (A) one or more severe medical conditions (Condition) and/or receiving assistance with activities of daily living (Functional Limitation); (B) Condition and/or Functional Limitation and hospital admission in the last 12 months and/or residing in a nursing home (Utilization); and (C) Condition and Functional Limitation and Utilization. Definitions are increasingly restrictive, but not mutually exclusive. DATA COLLECTION: Of 11,577 eligible subjects, 5,297 met definition A; 3,151 definition B; and 1,447 definition C. PRINCIPAL FINDINGS: One-year outcomes were as follows: hospitalization 33 percent (A), 44 percent (B), 47 percent (C); total average Medicare costs $20,566 (A), $26,349 (B), and $30,828 (C); and mortality 13 percent (A), 19 percent (B), 28 percent (C). In comparison, among those meeting no definition, 12 percent had hospitalizations, total Medicare costs averaged $7,789, and 2 percent died. CONCLUSIONS: Prospective identification of older adults with serious illness is feasible using clinically accessible criteria and may be a critical step toward improving health care value. These definitions may aid clinicians and health systems in targeting patients who could benefit from additional services.

Predictors of Mortality Up to 1 Year After Emergency Major Abdominal Surgery in Older Adults.

OBJECTIVES: To identify factors associated with mortality in older adults 30, 180, and 365 days after emergency major abdominal surgery. DESIGN: A retrospective study linked to Medicare claims from 2000 to 2010. SETTING: Health and Retirement Study (HRS). PARTICIPANTS: Medicare beneficiaries aged 65.5 enrolled in the HRS from 2000 to 2010 with at least one urgent or emergency major abdominal surgery and a core interview from the HRS within 3 years before surgery. MEASUREMENTS: Survival analysis was used to describe all-cause mortality 30, 180, and 365 days after surgery. Complementary log-log regression was used to identify participant characteristics and postoperative events associated with poorer survival. RESULTS: Four hundred individuals had one of the urgent or emergency surgeries of interest, 24% of whom were aged 85 and older, 50% had coronary artery disease, 48% had cancer, 33% had congestive heart failure, and 37% experienced a postoperative complication. Postoperative mortality was 20% at 30 days, 31% at 180 days, and 34% at 365 days. Of those aged 85 and older, 50% were dead 1 year after surgery. After multivariate adjustment including postoperative complications, dementia (hazard ratio (HR) = 2.02, 95% confidence interval (CI) = 1.24-3.31), hospitalization within 6 months before surgery (HR = 1.63, 95% CI = 1.12-2.28), and complications (HR = 3.45, 95% CI = 2.32-5.13) were independently associated with worse 1-year survival. CONCLUSION: Overall mortality is high in many older adults up to 1 year after undergoing emergency major abdominal surgery. The occurrence of a complication is the clinical factor most strongly associated with worse survival.