Cross-cultural serious neurological illness communication: qualitative analysis of multidisciplinary perspectives.

BACKGROUND: Cultural competence is important in approaching serious illness communication with diverse patients about goals of care. Culture colors patients' perspectives on many healthcare issues, including end-of-life care, and impacts how clinicians make decisions with patients. Communication about serious neurological illnesses can be additionally challenging due to disease impact on patients' cognition and decision-making abilities. We aim to understand provider experiences regarding cross-cultural serious neurological illness communication with diverse patients and families. METHODS: Using non-stratified purposive and snowball sampling, we conducted semi-structured interviews with 17 multidisciplinary participants, including neurosurgeons, neurologists, and social workers, who provide care for patients diagnosed with serious neurological disorders, at three hospital settings between 2021 and 2022. We used standard qualitative content analysis methods with dual review. RESULTS: Five themes reflected provider perspectives about serious neurological illness communication with diverse patients and families. Theme 1: providers recognize that patients' personal biases and lived experiences impact attitudes about healthcare and communication. Theme 2: challenges in communication can arise when providers miss chances to identify important cultural values. Theme 3: understanding how to engage with family members is important for effective communication about serious neurological illness. Theme 4: providers want to accommodate patients. Theme 5: cultivating trust builds a strong patientprovider partnership, even when racial or cultural discordance is present. CONCLUSIONS: Our study highlights elements of cross-cultural communication and opportunities for providers to approach diverse patients and families within a racial or culturally discordant context. Effective communication, fostered through respecting individual experiences and variation, eliciting cultural perspectives, engaging family, and cultivating trust reflects processes and learned skills required of highquality teams caring for patients with serious neurological conditions.

HbA1c variability associated with dementia risk in people with type 2 diabetes.

INTRODUCTION: Although poor glycemic control is associated with dementia, it is unknown if variability in glycemic control, even in those with optimal glycosylated hemoglobin A1c (HbA1c) levels, increases dementia risk. METHODS: Among 171,964 people with type 2 diabetes, we evaluated the hazard of dementia association with long-term HbA1c variability using five operationalizations, including standard deviation (SD), adjusting for demographics and comorbidities. RESULTS: The mean baseline age was 61 years (48% women). Greater HbA1c SD was associated with greater dementia hazard (adjusted hazard ratio = 1.15 [95% confidence interval: 1.12, 1.17]). In stratified analyses, higher HbA1c SD quintiles were associated with greater dementia hazard among those with a mean HbA1c < 6% (P = 0.0004) or 6% to 8% (P < 0.0001) but not among those with mean HbA1c ≥ 8% (P = 0.42). DISCUSSION: Greater HbA1c variability is associated with greater dementia risk, even among those with HbA1c concentrations at ideal clinical targets. These findings add to the importance and clinical impact of recommendations to minimize glycemic variability. HIGHLIGHTS: We observed a cohort of 171,964 people with type 2 diabetes (mean age 61 years). This cohort was based in Northern California between 1996 and 2018. We examined the association between glycosylated hemoglobin A1c (HbA1c) variability and dementia risk. Greater HbA1c variability was associated with greater dementia hazard. This was most evident among those with normal-low mean HbA1c concentrations.

Representativeness of Patients With Lung Cancer in an Integrated Health Care Delivery System.

INTRODUCTION: Observational research is important for understanding the real-world benefits of advancements in lung cancer care. Integrated health care systems, such as Kaiser Permanente Northern California, have extensive electronic health records suitable for such research, but the generalizability of their populations is often questioned. METHODS: Leveraging data from the California Cancer Registry, the authors compared distributions of demographic and clinical characteristics, in addition to neighborhood and environmental conditions, between patients diagnosed with lung cancer from 2015 through 2019 at Kaiser Permanente Northern California, National Cancer Institute-designated cancer centers (NCICCs), and all other non-NCICC hospitals within the same catchment area. RESULTS: Of 20,178 included patients, 30% were from Kaiser Permanente Northern California, 8% from NCICCs, and 62% from other non-NCICC hospitals. Compared to NCICC patients, Kaiser Permanente Northern California patients were more similar to other non-NCICC patients on most characteristics. Compared to other non-NCICC patients, Kaiser Permanente Northern California patients were slightly older, more likely to be female, and less likely to be Hispanic or Asian/Pacific Islander and to reside in lower socioeconomic status (SES) neighborhoods. In contrast, NCICC patients were younger, less likely to be female or from non-Asian/Pacific Islander minoritized racial groups, and more likely to present with early-stage disease and adenocarcinoma and to reside in neighborhoods with higher SES and lower air pollution than Kaiser Permanente Northern California or other non-NCICC patients. DISCUSSION: Patients from Kaiser Permanente Northern California, compared to NCICCs, are more broadly representative of the underlying patient population with lung cancer. CONCLUSION: Research using electronic health record data from integrated health care systems can contribute generalizable real-world evidence to benchmark and improve lung cancer care.

Interventions addressing health-related social needs among patients with cancer.

Health-related social needs are prevalent among cancer patients; associated with substantial negative health consequences; and drive pervasive inequities in cancer incidence, severity, treatment choices and decisions, and outcomes. To address the lack of clinical trial evidence to guide health-related social needs interventions among cancer patients, the National Cancer Institute Cancer Care Delivery Research Steering Committee convened experts to participate in a clinical trials planning meeting with the goal of designing studies to screen for and address health-related social needs among cancer patients. In this commentary, we discuss the rationale for, and challenges of, designing and testing health-related social needs interventions in alignment with the National Academy of Sciences, Engineering, and Medicine 5As framework. Evidence for food, housing, utilities, interpersonal safety, and transportation health-related social needs interventions is analyzed. Evidence regarding health-related social needs and delivery of health-related social needs interventions differs in maturity and applicability to cancer context, with transportation problems having the most maturity and interpersonal safety the least. We offer practical recommendations for health-related social needs interventions among cancer patients and the caregivers, families, and friends who support their health-related social needs. Cross-cutting (ie, health-related social needs agnostic) recommendations include leveraging navigation (eg, people, technology) to identify, refer, and deliver health-related social needs interventions; addressing health-related social needs through multilevel interventions; and recognizing that health-related social needs are states, not traits, that fluctuate over time. Health-related social needs-specific interventions are recommended, and pros and cons of addressing more than one health-related social needs concurrently are characterized. Considerations for collaborating with community partners are highlighted. The need for careful planning, strong partners, and funding is stressed. Finally, we outline a future research agenda to address evidence gaps.

Clinical impacts of an integrated electronic health record-based smoking cessation intervention during hospitalisation.

OBJECTIVE: To assess the effects of an electronic health record (EHR) intervention that prompts the clinician to prescribe nicotine replacement therapy (NRT) at hospital admission and discharge in a large integrated health system. DESIGN: Retrospective cohort study using interrupted time series (ITS) analysis leveraging EHR data generated before and after implementation of the 2015 EHR-based intervention. SETTING: Kaiser Permanente Northern California, a large integrated health system with 4.2 million members. PARTICIPANTS: Current smokers aged ≥18 hospitalised for any reason. EXPOSURE: EHR-based clinical decision supports that prompted the clinician to order NRT on hospital admission (implemented February 2015) and discharge (implemented September 2015). MAIN OUTCOMES AND MEASURES: Primary outcomes included the monthly percentage of admitted smokers with NRT orders during admission and at discharge. A secondary outcome assessed patient quit rates within 30 days of hospital discharge as reported during discharge follow-up outpatient visits. RESULTS: The percentage of admissions with NRT orders increased from 29.9% in the year preceding the intervention to 78.1% in the year following (41.8% change, 95% CI 38.6% to 44.9%) after implementation of the admission hard-stop intervention compared with the baseline trend (ITS estimate). The percentage of discharges with NRT orders increased acutely at the time of both interventions (admission intervention ITS estimate 15.5%, 95% CI 11% to 20%; discharge intervention ITS estimate 13.4%, 95% CI 9.1% to 17.7%). Following the implementation of the discharge intervention, there was a small increase in patient-reported quit rates (ITS estimate 5.0%, 95% CI 2.2% to 7.8%). CONCLUSIONS: An EHR-based clinical decision-making support embedded into admission and discharge documentation was associated with an increase in NRT prescriptions and improvement in quit rates. Similar systemic EHR interventions can help improve smoking cessation efforts after hospitalisation.

Disparities in Preoperative Goals of Care Documentation in Veterans.

Importance: Preoperative goals of care discussion and documentation are important for patients undergoing surgery, a major health care stressor that incurs risk. Objective: To assess the association of race, ethnicity, and other factors, including history of mental health disability, with disparities in preoperative goals of care documentation among veterans. Design, Setting, and Participants: This retrospective cross-sectional study assessed data from the Veterans Healthcare Administration (VHA) of 229 737 veterans who underwent surgical procedures between January 1, 2017, and October 18, 2022. Exposures: Patient-level (ie, race, ethnicity, medical comorbidities, history of mental health comorbidity) and system-level (ie, facility complexity level) factors. Main Outcomes and Measures: Preoperative life-sustaining treatment (LST) note documentation or no LST note documentation within 30 days prior to or on day of surgery. The standardized mean differences were calculated to assess the magnitude of differences between groups. Odds ratios (ORs) and 95% CIs were estimated with logistic regression. Results: In this study, 13 408 patients (5.8%) completed preoperative LST from 229 737 VHA patients (209 123 [91.0%] male; 20 614 [9.0%] female; mean [SD] age, 65.5 [11.9] years) who received surgery. Compared with patients who did complete preoperative LST, patients tended to complete preoperative documentation less often if they were female (19 914 [9.2%] vs 700 [5.2%]), Black individuals (42 571 [19.7%] vs 2416 [18.0%]), Hispanic individuals (11 793 [5.5%] vs 631 [4.7%]), or from rural areas (75 637 [35.0%] vs 4273 [31.9%]); had a history of mental health disability (65 974 [30.5%] vs 4053 [30.2%]); or were seen at lowest-complexity (ie, level 3) facilities (7849 [3.6%] vs 78 [0.6%]). Over time, despite the COVID-19 pandemic, patients undergoing surgical procedures completed preoperative LST increasingly more often. Covariate-adjusted estimates of preoperative LST completion demonstrated that patients of racial or ethnic minority background (Black patients: OR, 0.79; 95% CI, 0.77-0.80; P <.001; patients selecting other race: OR, 0.78; 95% CI, 0.74-0.81; P <.001; Hispanic patients: OR, 0.78; 95% CI, 0.76-0.81; P <.001) and patients from rural regions (OR, 0.91; 95% CI, 0.90-0.93; P <.001) had lower likelihoods of completing LST compared with patients who were White or non-Hispanic and patients from urban areas. Patients with any mental health disability history also had lower likelihood of completing preoperative LST than those without a history (OR, 0.93; 95% CI, 0.92-0.94; P = .001). Conclusions and Relevance: In this cross-sectional study, disparities in documentation rates within a VHA cohort persisted based on race, ethnicity, rurality of patient residence, history of mental health disability, and access to high-volume, high-complexity facilities.

Strategies to Bridge Equitable Implementation of Telehealth.

During the COVID-19 pandemic, the rapid scaling of telehealth limited the extent to which proactive planning for equitable implementation was possible. The deployment of telehealth will persist in the postpandemic era, given patient preferences, advances in technologies, growing acceptance of telehealth, and the potential to overcome barriers to serve populations with limited access to high-quality in-person care. However, aspects and unintended consequences of telehealth may leave some groups underserved or unserved, and corrective implementation plans that address equitable access will be needed. The purposes of this paper are to (1) describe equitable implementation in telehealth and (2) integrate an equity lens into actionable equitable implementation.

Evaluation of approaches to recruitment of racially and ethnically diverse breast cancer patients from an integrated health care setting for collection of observational social network data.

PURPOSE: We compared approaches to recruitment of diverse women with breast cancer in a study designed to collect complex social network data. METHODS: We recruited 440 women from the Kaiser Permanente Northern California population newly diagnosed with breast cancer, either in person at a clinic, by email, or by mailed letter. In clinic and mail recruitment, women completed a brief 3-page paper survey (epidemiologic data only), and women had the option to complete a separate, longer (30-40 min) personal social network survey online. In email recruitment, we administered epidemiologic and personal social network measures together in a single online survey. In email and mail recruitment, we limited the sample of non-Hispanic white (NHW) women to 30% of their total. We used descriptive analysis and multinomial logistic regression to examine odds of recruitment vs. mailed letter. RESULTS: Women responded to the social network surveys on average 3.7 months post-diagnosis. Mean age was 59.3 (median = 61.0). In-person clinic recruitment was superior with a 52.1% success rate of recruitment compared with 35.6% by mail or 17.3% by email (χ2 = 65.9, p < 0.001). Email recruitment produced the highest completion rate (82.1%) of personal network data compared with clinic (36.5%) or mail (28.7%), (χ2 = 114.6, p < 0.001). Despite intentional undersampling of NHW patients, response rates for Asian, Hispanic, and Black women by email were lower. However, we found no significant differences in recruitment rates by race and ethnicity for face-to-face clinic recruitment vs. by letter. Letter recruitment produced the highest overall response. CONCLUSION: Mailed letter was the best approach to representative recruitment of diverse women with breast cancer and collection of social network data, and further yielded the highest absolute response.

Glycemic Control Over Multiple Decades and Dementia Risk in People With Type 2 Diabetes.

Importance: The levels of glycemic control associated with the lowest risk of dementia in people with type 2 diabetes are unknown. This knowledge is critical to inform patient-centered glycemic target setting. Objective: To examine the associations between cumulative exposure to various ranges of glycated hemoglobin (HbA1c) concentrations with dementia risk across sex and racial and ethnic groups and the association of current therapeutic glycemic targets with dementia risk. Design, Setting, and Participants: This cohort study included members of the Kaiser Permanente Northern California integrated health care system with type 2 diabetes who were aged 50 years or older during the study period from January 1, 1996, to September 30, 2015. Individuals with fewer than 2 HbA1c measurements during the study period, prevalent dementia at baseline, or less than 3 years of follow-up were excluded. Data were analyzed from February 2020 to January 2023. Exposures: Time-updated cumulative exposure to HbA1c thresholds. At each HbA1c measurement, participants were categorized based on the percentage of their HbA1c measurements that fell into the following categories: less than 6%, 6% to less than 7%, 7% to less than 8%, 8% to less than 9%, 9% to less than 10%, and 10% or more of total hemoglobin (to convert percentage of total hemoglobin to proportion of total hemoglobin, multiply by 0.01). Main Outcomes and Measures: Dementia diagnosis was identified using International Classification of Diseases, Ninth Revision codes from inpatient and outpatient encounters. Cox proportional hazards regression models estimated the association of time-varying cumulative glycemic exposure with dementia, adjusting for age, race and ethnicity, baseline health conditions, and number of HbA1c measurements. Results: A total of 253 211 participants were included. The mean (SD) age of participants was 61.5 (9.4) years, and 53.1% were men. The mean (SD) duration of follow-up was 5.9 (4.5) years. Participants with more than 50% of HbA1c measurements at 9% to less than 10% or 10% or more had greater risk of dementia compared with those who had 50% or less of measurements in those categories (HbA1c 9% to <10%: adjusted hazard ratio [aHR], 1.31 [95% CI, 1.15-1.51]; HbA1c≥10%: aHR, 1.74 [95% CI, 1.62-1.86]). By contrast, participants with more than 50% of HbA1c concentrations less than 6%, 6% to less than 7%, or 7% to less than 8% had lower risk of dementia (HbA1c<6%: aHR, 0.92 [95% CI, 0.88-0.97]; HbA1c 6% to <7%: aHR, 0.79 [95% CI, 0.77-0.81]; HbA1c 7% to <8%: aHR, 0.93 [95% CI, 0.89-0.97]). Conclusions and Relevance: In this study dementia risk was greatest among adults with cumulative HbA1c concentrations of 9% or more. These results support currently recommended relaxed glycemic targets for older people with type 2 diabetes.

Disparities in Hemoglobin A1c Levels in the First Year After Diagnosis Among Youths With Type 1 Diabetes Offered Continuous Glucose Monitoring.

Importance: Continuous glucose monitoring (CGM) is associated with improvements in hemoglobin A1c (HbA1c) in youths with type 1 diabetes (T1D); however, youths from minoritized racial and ethnic groups and those with public insurance face greater barriers to CGM access. Early initiation of and access to CGM may reduce disparities in CGM uptake and improve diabetes outcomes. Objective: To determine whether HbA1c decreases differed by ethnicity and insurance status among a cohort of youths newly diagnosed with T1D and provided CGM. Design, Setting, and Participants: This cohort study used data from the Teamwork, Targets, Technology, and Tight Control (4T) study, a clinical research program that aims to initiate CGM within 1 month of T1D diagnosis. All youths with new-onset T1D diagnosed between July 25, 2018, and June 15, 2020, at Stanford Children's Hospital, a single-site, freestanding children's hospital in California, were approached to enroll in the Pilot-4T study and were followed for 12 months. Data analysis was performed and completed on June 3, 2022. Exposures: All eligible participants were offered CGM within 1 month of diabetes diagnosis. Main Outcomes and Measures: To assess HbA1c change over the study period, analyses were stratified by ethnicity (Hispanic vs non-Hispanic) or insurance status (public vs private) to compare the Pilot-4T cohort with a historical cohort of 272 youths diagnosed with T1D between June 1, 2014, and December 28, 2016. Results: The Pilot-4T cohort comprised 135 youths, with a median age of 9.7 years (IQR, 6.8-12.7 years) at diagnosis. There were 71 boys (52.6%) and 64 girls (47.4%). Based on self-report, participants' race was categorized as Asian or Pacific Islander (19 [14.1%]), White (62 [45.9%]), or other race (39 [28.9%]); race was missing or not reported for 15 participants (11.1%). Participants also self-reported their ethnicity as Hispanic (29 [21.5%]) or non-Hispanic (92 [68.1%]). A total of 104 participants (77.0%) had private insurance and 31 (23.0%) had public insurance. Compared with the historical cohort, similar reductions in HbA1c at 6, 9, and 12 months postdiagnosis were observed for Hispanic individuals (estimated difference, -0.26% [95% CI, -1.05% to 0.43%], -0.60% [-1.46% to 0.21%], and -0.15% [-1.48% to 0.80%]) and non-Hispanic individuals (estimated difference, -0.27% [95% CI, -0.62% to 0.10%], -0.50% [-0.81% to -0.11%], and -0.47% [-0.91% to 0.06%]) in the Pilot-4T cohort. Similar reductions in HbA1c at 6, 9, and 12 months postdiagnosis were also observed for publicly insured individuals (estimated difference, -0.52% [95% CI, -1.22% to 0.15%], -0.38% [-1.26% to 0.33%], and -0.57% [-2.08% to 0.74%]) and privately insured individuals (estimated difference, -0.34% [95% CI, -0.67% to 0.03%], -0.57% [-0.85% to -0.26%], and -0.43% [-0.85% to 0.01%]) in the Pilot-4T cohort. Hispanic youths in the Pilot-4T cohort had higher HbA1c at 6, 9, and 12 months postdiagnosis than non-Hispanic youths (estimated difference, 0.28% [95% CI, -0.46% to 0.86%], 0.63% [0.02% to 1.20%], and 1.39% [0.37% to 1.96%]), as did publicly insured youths compared with privately insured youths (estimated difference, 0.39% [95% CI, -0.23% to 0.99%], 0.95% [0.28% to 1.45%], and 1.16% [-0.09% to 2.13%]). Conclusions and Relevance: The findings of this cohort study suggest that CGM initiation soon after diagnosis is associated with similar improvements in HbA1c for Hispanic and non-Hispanic youths as well as for publicly and privately insured youths. These results further suggest that equitable access to CGM soon after T1D diagnosis may be a first step to improve HbA1c for all youths but is unlikely to eliminate disparities entirely. Trial Registration: ClinicalTrials.gov Identifier: NCT04336969.

Tobacco Smoking and Risk of SARS-CoV-2 Infection and Disease Severity Among Adults in an Integrated Healthcare System in California.

INTRODUCTION: The relationship between tobacco smoking status and SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19) severity is highly debated. We conducted a retrospective cohort study of >2.4 million adults in a large healthcare system to evaluate whether smoking is associated with SARS-CoV-2 infection and disease severity. AIMS AND METHODS: This retrospective cohort study of 2,427,293 adults in KPNC from March 5, 2020 (baseline) to December 31, 2020 (pre-vaccine) included smoking status (current, former, never), socio-demographics, and comorbidities from the electronic health record. SARS-CoV-2 infection (identified by a positive PCR test) and COVID-19 severity (hospitalization, ICU admission or death ≤ 30 days of COVID-19 diagnosis) were estimated in time-to-event analyses using Cox proportional hazard regression models adjusting for covariates. Secondary analyses examined COVID-19 severity among patients with COVID-19 using logistic regression. RESULTS: During the study, 44,270 patients had SARS-CoV-2 infection. Current smoking was associated with lower adjusted rates of SARS-CoV-2 infection (aHR = 0.64 95% CI: 0.61-0.67), COVID-19-related hospitalization (aHR = 0.48 95% CI: 0.40-0.58), ICU admission (aHR = 0.62 95% CI: 0.42-0.87), and death (aHR = 0.52 95% CI: 0.27-0.89) than never-smoking. Former smoking was associated with a lower adjusted rate of SARS-CoV-2 infection (aHR = 0.96 95% CI: 0.94-0.99) and higher adjusted rates of hospitalization (aHR = 1.10 95% CI: 1.03-1.08) and death (aHR = 1.32 95% CI: 1.11-1.56) than never-smoking. Logistic regression analyses among patients with COVID-19 found lower odds of hospitalization for current versus never-smoking and higher odds of hospitalization and death for former versus never-smoking. CONCLUSIONS: In the largest US study to date on smoking and COVID-19, current and former smoking showed lower risk of SARS-CoV-2 infection than never-smoking, while a history of smoking was associated with higher risk of severe COVID-19. IMPLICATIONS: In this cohort study of 2.4 million adults, adjusting for socio-demographics and medical comorbidities, current tobacco smoking was associated with a lower risk of both SARS-CoV-2 infection and severe COVID-19 illness compared to never-smoking. A history of smoking was associated with a slightly lower risk of SARS-CoV-2 infection and a modestly higher risk of severe COVID-19 illness compared to never-smoking. The lower observed COVID-19 risk for current versus never-smoking deserves further investigation. Results support prioritizing individuals with smoking-related comorbidities for vaccine outreach and treatments as they become available.

Advancing clinical trials in nursing homes: A proposed roadmap to success.

An effective clinical research effort in nursing homes to address prevention and treatment of COVID-19 faced overwhelming challenges. Under the Health Care Systems Research Network-Older Americans Independence Centers AGING Initiative, a multidisciplinary Stakeholder Advisory Panel was convened to develop recommendations to improve the capability of the clinical research enterprise in US nursing homes. The Panel considered the nursing home as a setting for clinical trials, reviewed the current state of clinical trials in nursing homes, and ultimately developed recommendations for the establishment of a nursing home clinical trials research network that would be centrally supported and administered. This report summarizes the Panel's recommendations, which were developed in alignment with the following core principles: build on available research infrastructure where appropriate; leverage existing productive partnerships of researchers with groups of nursing homes and nursing home corporations; encompass both efficacy and effectiveness clinical trials; be responsive to a broad range of stakeholders including nursing home residents and their care partners; be relevant to an expansive range of clinical and health care delivery research questions; be able to pivot as necessary to changing research priorities and circumstances; create a pathway for industry-sponsored research as appropriate; invest in strategies to increase diversity in study populations and the research workforce; and foster the development of the next generation of nursing home researchers.

Stakeholders' views on priorities essential for establishing a supportive environment for clinical trials in nursing homes.

BACKGROUND: The U.S. clinical research enterprise in nursing homes was unprepared to mount clinical trials in nursing homes to address urgent questions relevant to prevention and treatment during the COVID-19 pandemic. We identify priorities essential for establishing a supportive environment for future clinical trials in nursing homes. METHODS: Two cross-sectional online questionnaires were administered between January and February 2021. One was administered to nursing home providers, researchers, and policymakers; respondents rated the importance of attributes of researchers, facilities, leaders and staff for conducting clinical trials in nursing homes. Because importance may depend on trial type, respondents rated each attribute for efficacy trials (testing an intervention in ideal circumstances) and effectiveness trials (testing an intervention in "real world" circumstances). We calculated the attribute rating means and standard deviations, and used content analysis to characterize open-ended responses. The second questionnaire for resident family members and advocates included open-ended questions about nursing home research, and factors influencing willingness to participate. RESULTS: The attributes rated as most essential for conducting efficacy and effectiveness trials in nursing homes are research team attributes, that is, that researchers recognize regulatory constraints; understand and adapt to nursing home workflow; and work collaboratively with nursing home leaders to identify priorities. Resident and facility diversity emerged as essential for effectiveness trials; important dimensions included resident race, ethnicity and income, as well as nursing home urban/rural location, quality ratings, geography, staffing ratios, size, and profit status. Caregivers and resident advocates stressed the importance of communication among participants, researchers, and nursing home leadership and staff at all stages of a trial. CONCLUSION: Developing a robust U.S. clinical research enterprise capable of efficiently mounting future clinical trials in nursing homes will require a reimagining of the relationships that exist between researchers, facilities, nursing home leaders, and residents, with a research infrastructure specifically focused on supporting and fostering these connections.

Advancing Clinical Trials in Nursing Homes: A Proposed Roadmap to Success.

An effective clinical research effort in nursing homes to address prevention and treatment of COVID-19 faced overwhelming challenges. Under the Health Care Systems Research Network-Older Americans Independence Centers AGING Initiative, a multidisciplinary Stakeholder Advisory Panel was convened to develop recommendations to improve the capability of the clinical research enterprise in US nursing homes. The Panel considered the nursing home as a setting for clinical trials, reviewed the current state of clinical trials in nursing homes, and ultimately developed recommendations for the establishment of a nursing home clinical trials research network that would be centrally supported and administered. This report summarizes the Panel's recommendations, which were developed in alignment with the following core principles: build on available research infrastructure where appropriate; leverage existing productive partnerships of researchers with groups of nursing homes and nursing home corporations; encompass both efficacy and effectiveness clinical trials; be responsive to a broad range of stakeholders including nursing home residents and their care partners; be relevant to an expansive range of clinical and health care delivery research questions; be able to pivot as necessary to changing research priorities and circumstances; create a pathway for industry-sponsored research as appropriate; invest in strategies to increase diversity in study populations and the research workforce; and foster the development of the next generation of nursing home researchers.

Advancing Clinical Trials in Nursing Homes: A Proposed Roadmap to Success.

An effective clinical research effort in nursing homes to address prevention and treatment of COVID-19 faced overwhelming challenges. Under the Health Care Systems Research Network-Older Americans Independence Centers AGING Initiative, a multidisciplinary Stakeholder Advisory Panel was convened to develop recommendations to improve the capability of the clinical research enterprise in US nursing homes. The Panel considered the nursing home as a setting for clinical trials, reviewed the current state of clinical trials in nursing homes, and ultimately developed recommendations for the establishment of a nursing home clinical trials research network that would be centrally supported and administered. This report summarizes the Panel's recommendations, which were developed in alignment with the following core principles: build on available research infrastructure where appropriate; leverage existing productive partnerships of researchers with groups of nursing homes and nursing home corporations; encompass both efficacy and effectiveness clinical trials; be responsive to a broad range of stakeholders including nursing home residents and their care partners; be relevant to an expansive range of clinical and health care delivery research questions; be able to pivot as necessary to changing research priorities and circumstances; create a pathway for industry-sponsored research as appropriate; invest in strategies to increase diversity in study populations and the research workforce; and foster the development of the next generation of nursing home researchers.

Factors associated with persistent high health care utilization in managed Medicaid.

OBJECTIVES: Prior studies have had difficulty predicting which patients will have persistent high utilization past 1 year within the Medicaid population. The objective of this study was to examine the medical diagnoses at the time of enrollment of patients with persistent high health care utilization over 24 months following enrollment in Medicaid managed care in a large integrated care setting. STUDY DESIGN: Retrospective cohort study in a large integrated managed health care system. METHODS: We identified a cohort of high utilizers (top 5% of health care costs in 2014) and extracted their electronic health record data (2014-2016). Differences in baseline characteristics of high utilizers and the general Medicaid population were determined using bivariate analysis. We used multivariable regression to determine the independent association between medical comorbidities and demographics with persistent high health care utilization over the 2 years following enrollment. RESULTS: Compared with the general Medicaid managed care enrollee population, schizophrenia was the only mental health diagnosis at the time of enrollment associated with persistent high health care utilization (risk ratio [RR], 1.50; 95% CI, 1.20-1.86). Additional characteristics associated with persistent high utilization included age between 31 and 50 years (RR, 1.20; 95% CI, 1.02-1.41), dual enrollment in Medicaid and Medicare (RR, 1.26; 95% CI, 1.09-1.45), chronic pain diagnoses (RR, 1.26; 95% CI, 1.04-1.53), and multimorbidity (RR, 1.43; 95% CI, 1.25-1.63). CONCLUSIONS: Among adults newly enrolled in Medicaid managed care, certain diagnoses noted at the time of enrollment into the plan are associated with persistent high health care utilization over the first 2 years, suggesting that targeting early supportive case management to these individuals could optimize care and reduce health care costs.