Post-Acute Care Trends and Disparities After Joint Replacements in the United States, 1991-2018: A Systematic Review.

OBJECTIVE: To review evidence on post-acute care (PAC) use and disparities related to race and ethnicity and rurality in the United States over the past 2 decades among individuals who underwent major joint replacement (MJR). DESIGN: Systematic review. SETTING AND PARTICIPANTS: We included studies that examined US PAC trends and racial and ethnic and/or urban vs rural differences among individuals who are aged ≥18 years with hospitalization after MJR. METHODS: We searched large academic databases (PubMed, CINAHL, Embase, Web of Science, and Scopus) for peer-reviewed, English language articles from January 1, 2000, and January 26, 2022. RESULTS: Seventeen studies were reviewed. Studies (n = 16) consistently demonstrated that discharges post-MJR to skilled nursing facilities (SNFs) or nursing homes (NHs) decreased over time, whereas evidence on discharges to inpatient rehab facilities (IRFs), home health care (HHC), and home without HHC services were mixed. Most studies (n = 12) found that racial and ethnic minority individuals, especially Black individuals, were more frequently discharged to PAC institutions than white individuals. Demographic factors (ie, age, sex, comorbidities) and marital status were not only independently associated with discharges to institutional PAC, but also among racial and ethnic minority individuals. Only one study found urban-rural differences in PAC use, indicating that urban-dwelling individuals were more often discharged to both SNF/NH and HHC than their rural counterparts. CONCLUSIONS AND IMPLICATIONS: Despite declines in institutional PAC use post-MJR over time, racial and minority individuals continue to experience higher rates of institutional PAC discharges compared with white individuals. To address these disparities, policymakers should consider measures that target multimorbidity and the lack of social and structural support among socially vulnerable individuals. Policymakers should also consider initiatives that address the economic and structural barriers experienced in rural areas by expanding access to telehealth and through improved care coordination.

Potentially Avoidable Hospitalizations Among Historically Marginalized Nursing Home Residents.

Importance: Nursing home (NH) transfers to hospitals are common and have been associated with cognitive decline; approximately 45% of NH hospital transfers are potentially avoidable hospitalizations (PAHs). Objective: To determine PAH incidence for historically marginalized NH residents with severe cognitive impairment compared with non-Hispanic White residents. Design, Setting, and Participants: This cross-sectional study merged 2018 Centers for Medicaid & Medicare Services datasets and LTCFocus, a public dataset on US NH care, for US NH residents aged 65 years and older who had a hospitalization. Analyses were performed from January to May 2022. Exposure: Race and ethnicity of NH residents. Main Outcomes and Measures: Racial and ethnic differences in resident-level annual rates of PAHs were estimated for residents with and without severe cognitive impairment (measured using the Cognitive Function Scale), controlling for resident characteristics, comorbidities, dual eligibility, and time at risk. PAHs were defined as NH hospital transfers that resulted from neglectful NH care or for which NH treatment would have been appropriate. Results: Of 2 098 385 NH residents nationwide included in the study, 7151 (0.3%) were American Indian or Alaska Native, 39 873 (1.9%) were Asian, 229 112 (10.9%) were Black or African American, 99 304 (4.7%) were Hispanic, 2785 (0.1%) were Native Hawaiian or Pacific Islander, 1 713 670 (81.7%) were White, and 6490 (0.3%) were multiracial; 1 355 143 (64.6%) were female; 128 997 (6.2%) were severely cognitively impaired; and the mean (SD) age was 81.8 (8.7) years. PAH incidence rate ratios (IRRs) were significantly greater for residents with severe cognitive impairment compared with those without. In unadjusted analyses comparing historically marginalized residents with severe cognitive impairment vs non-Hispanic White residents with severe cognitive impairment, American Indian or Alaska Native residents had a 49% higher PAH incidence (IRR, 1.49 [95% CI, 1.10-2.01]), Black or African American residents had a 64% higher incidence (IRR, 1.64 [95% CI, 1.48-1.81]), and Hispanic residents had a 45% higher incidence (IRR, 1.45 [95% CI, 1.29-1.62]). Higher incidences persisted for historically marginalized residents with severe cognitive impairment vs non-Hispanic White residents with severe cognitive impairment in adjusted analyses. Asian residents had a 24% higher PAH incidence (IRR, 1.24 [95% CI, 1.06-1.45]), Black or African American residents had a 48% higher incidence (IRR, 1.48 [95% CI, 1.36-1.60]), and Hispanic residents had a 27% higher incidence (IRR, 1.27 [95% CI, 1.16-1.39]). Conclusions and Relevance: In this cross-sectional study of PAHs, compared with non-Hispanic White NH residents, historically marginalized residents had increased PAH incidence. In the presence of severe cognitive impairment, incidence rates increased significantly compared with rates for residents without severe cognitive impairment. These results suggest that identification of residents with severe cognitive impairment and proper NH care may help prevent further cognitive decline by avoiding PAHs.

Natural Language Processing to Identify Home Health Care Patients at Risk for Becoming Incapacitated With No Evident Advance Directives or Surrogates.

OBJECTIVES: Home health care patients who are at risk for becoming Incapacitated with No Evident Advance Directives or Surrogates (INEADS) may benefit from timely intervention to assist them with advance care planning. This study aimed to develop natural language processing algorithms for identifying home care patients who do not have advance directives, family members, or close social contacts who can serve as surrogate decision-makers in the event that they lose decisional capacity. DESIGN: Cross-sectional study of electronic health records. SETTING AND PARTICIPANTS: Patients receiving post-acute care discharge services from a large home health agency in New York City in 2019 (n = 45,390 enrollment episodes). METHODS: We developed a natural language processing algorithm for identifying information documented in free-text clinical notes (n = 1,429,030 notes) related to 4 categories: evidence of close relationships, evidence of advance directives, evidence suggesting lack of close relationships, and evidence suggesting lack of advance directives. We validated the algorithm against Gold Standard clinician review for 50 patients (n = 314 notes) to calculate precision, recall, and F-score. RESULTS: Algorithm performance for identifying text related to the 4 categories was excellent (average F-score = 0.91), with the best results for "evidence of close relationships" (F-score = 0.99) and the worst results for "evidence of advance directives" (F-score = 0.86). The algorithm identified 22% of all clinical notes (313,290 of 1,429,030) as having text related to 1 or more categories. More than 98% of enrollment episodes (48,164 of 49,141) included at least 1 clinical note containing text related to 1 or more categories. CONCLUSIONS AND IMPLICATIONS: This study establishes the feasibility of creating an automated screening algorithm to aid home health care agencies with identifying patients at risk of becoming INEADS. This screening algorithm can be applied as part of a multipronged approach to facilitate clinician support for advance care planning with patients at risk of becoming INEADS.

State- and Territory-Level Nursing Home and Home Health Care COVID-19 Policies and Disease Burden.

This cross-sectional study creates a dataset and dashboard of US state- and territory-level COVID-19 policies specific to nursing homes and home health care agencies.

Insurance-based Disparities in Outcomes and Extracorporeal Membrane Oxygenation Utilization for Hospitalized COVID-19 Patients.

BACKGROUND: The objective of this study was to examine insurance-based disparities in mortality, nonhome discharges, and extracorporeal membrane oxygenation utilization in patients hospitalized with COVID-19. METHODS: Using a national database of U.S. academic medical centers and their affiliated hospitals, the risk-adjusted association between mortality, nonhome discharge, and extracorporeal membrane oxygenation utilization and (1) the type of insurance coverage (private insurance, Medicare, dual enrollment in Medicare and Medicaid, and no insurance) and (2) the weekly hospital COVID-19 burden (0 to 5.0%; 5.1 to 10%, 10.1 to 20%, 20.1 to 30%, and 30.1% and greater) was evaluated. Modeling was expanded to include an interaction between payer status and the weekly hospital COVID-19 burden to examine whether the lack of private insurance was associated with increases in disparities as the COVID-19 burden increased. RESULTS: Among 760,846 patients hospitalized with COVID-19, 214,992 had private insurance, 318,624 had Medicare, 96,192 were dually enrolled in Medicare and Medicaid, 107,548 had Medicaid, and 23,560 had no insurance. Overall, 76,250 died, 211,702 had nonhome discharges, 75,703 were mechanically ventilated, and 2,642 underwent extracorporeal membrane oxygenation. The adjusted odds of death were higher in patients with Medicare (adjusted odds ratio, 1.28 [95% CI, 1.21 to 1.35]; P < 0.0005), dually enrolled (adjusted odds ratio, 1.39 [95% CI, 1.30 to 1.50]; P < 0.0005), Medicaid (adjusted odds ratio, 1.28 [95% CI, 1.20 to 1.36]; P < 0.0005), and no insurance (adjusted odds ratio, 1.43 [95% CI, 1.26 to 1.62]; P < 0.0005) compared to patients with private insurance. Patients with Medicare (adjusted odds ratio, 0.47; [95% CI, 0.39 to 0.58]; P < 0.0005), dually enrolled (adjusted odds ratio, 0.32 [95% CI, 0.24 to 0.43]; P < 0.0005), Medicaid (adjusted odds ratio, 0.70 [95% CI, 0.62 to 0.79]; P < 0.0005), and no insurance (adjusted odds ratio, 0.40 [95% CI, 0.29 to 0.56]; P < 0.001) were less likely to be placed on extracorporeal membrane oxygenation than patients with private insurance. Mortality, nonhome discharges, and extracorporeal membrane oxygenation utilization did not change significantly more in patients with private insurance compared to patients without private insurance as the COVID-19 burden increased. CONCLUSIONS: Among patients with COVID-19, insurance-based disparities in mortality, nonhome discharges, and extracorporeal membrane oxygenation utilization were substantial, but these disparities did not increase as the hospital COVID-19 burden increased.

The association of nursing home infection preventionists' training and credentialing with resident COVID 19 deaths.

BACKGROUND: Nursing home (NH) residents' vulnerability to COVID-19 underscores the importance of infection preventionists (IPs) within NHs. Our study aimed to determine whether training and credentialing of NH IPs were associated with resident COVID-19 deaths. METHODS: This retrospective observational study utilized data from the Centers for Disease Control and Prevention's National Healthcare Safety Network NH COVID-19 Module and USAFacts, from May 2020 to February 2021, linked to a 2018 national NH survey. We categorized IP personnel training and credentialing into four groups: (1) LPN without training; (2) RN/advanced clinician without training; (3) LPN with training; and (4) RN/advanced clinician with training. Multivariable linear regression models of facility-level weekly deaths per 1000 residents as a function of facility characteristics, and county-level COVID-19 burden (i.e., weekly cases or deaths per 10,000 population) were estimated. RESULTS: Our study included 857 NHs (weighted n = 14,840) across 489 counties and 50 states. Most NHs had over 100 beds, were for profit, part of chain organizations, and located in urban areas. Approximately 53% of NH IPs had infection control training and 82% were RNs/advanced clinicians. Compared with NHs employing IPs who were LPNs without training, NHs employing IPs who were RNs/advanced clinicians without training had lower weekly COVID-19 death rates (-1.04 deaths per 1000 residents; 95% CI -1.90, -0.18), and NHs employing IPs who were LPNs with training had lower COVID-19 death rates (-1.09 deaths per 1000 residents; 95% CI -2.07, -0.11) in adjusted models. CONCLUSIONS: NHs with LPN IPs without training in infection control had higher death rates than NHs with LPN IPs with training in infection control, or NHs with RN/advanced clinicians in the IP role, regardless of IP training. IP training of RN/advanced clinician IPs was not associated with death rates. These findings suggest that efforts to standardize and improve IP training may be warranted.

Nurse state legislators, 2013 to 2023.

BACKGROUND: Electing nurse legislators can help states make sound health policy. PURPOSE: To document the distribution of American nurses elected to state-level offices in 2023 and compare it to data from 2013. METHODS: We developed a directory of 2023 nurses elected to state legislatures. Data collected include state, year elected, party, committees, re-election date, and full/part-time state legislature. FINDINGS: In 2023, there were 72 nurse legislators in 36 states. These nurse legislators' affiliations were divided almost evenly between the two major parties (38 Republicans and 34 Democrats). Sixty legislators serve on health committees; 32 on finance committees. Fourteen serve in states that have full-time legislatures. The majority (n = 60) are up for re-election in 2024. In 2013, there were 97 legislators in 39 states. DISCUSSION: Over the last decade, the number of nurse legislators has declined. CONCLUSION: State legislatures play key roles in funding and regulating health policy. Identifying where nurses currently serve provides actionable information for those seeking to recruit, train, and elect nurse candidates.

Health Information Technology Adoption at U.S. Home Health Care Agencies: Results from a Multi-Methods Study.

Health information technology (HIT) holds potential to transform Home Health Care (HHC), yet, little is known about its adoption in this setting. In the context of infection prevention and control, we aimed to: (1) describe challenges associated with the adoption of HIT, for example, electronic health records (EHR) and telehealth and (2) examine HHC agency characteristics associated with HIT adoption. We conducted in-depth interviews with 41 staff from 13 U.S. HHC agencies (May-October 2018), then surveyed a stratified random sample of 1506 agencies (November 2018-December 2019), of which 35.6% participated (N = 536 HHC agencies). We applied analytic weights, generating nationally-representative estimates, and computed descriptive statistics, bivariate and multivariable analyses. Four themes were identified: (1) Reflections on providing HHC without EHR; (2) Benefits of EHR; (3) Benefits of other HIT; (4) Challenges with HIT and EHR. Overall, 10% of the agencies did not have an EHR; an additional 2% were in the process of acquiring one. Sixteen percent offered telehealth, and another 4% were in the process of acquiring telehealth services. In multivariable analysis, EHR use varied significantly by geographic location and ownership, and telehealth use varied by geographic location, ownership, and size. Although HIT use has increased, our results indicate that many HHC agencies still lack the HIT needed to implement technological solutions to improve workflow and quality of care. Future research should examine the impact of HIT on patient outcomes and the impact of the COVID-19 pandemic on HIT use in HHC.