Managing Multiple Chronic Conditions during COVID-19 Among Patients with Social Health Risks.

BACKGROUND: Optimal care for persons with multiple chronic conditions (MCC) requires primary and specialty care continuity, access to multiple providers, social risk assessment, and self-management support. The COVID-19 pandemic abruptly changed primary care delivery to increase reliance on telehealth and virtual care. We report on the experiences of individuals with MCC and their family caregivers on managing their health and receiving health care during the initial pandemic. METHODS: Semistructured qualitative interviews with 30 patients (19 English speaking, 11 Spanish speaking) plus 9 accompanying care partners, who had 2+ primary care encounters between March 1, 2020, and November 30, 2020, 2+ chronic conditions, and 1 or more self-reported social risks. Questions focused on access to and experiences with care, roles for care partners, and self-management during the first 6 months of the pandemic. RESULTS: Participants experienced substantial changes in care delivery. The most commonly reported changes were a shift to more virtual relative to in-person care and shifting roles for care partners. Changes fostered new perspectives on self-management and an appreciation of personal resilience and self-reliance. Virtual care was an acceptable complement to in-person care, though not a substitute for periodic in-person visits. It was more acceptable for English speakers and with a usual provider. CONCLUSION: New models of care delivery that recognize patient and family resilience and resourcefulness, emphasize provider continuity, and combine virtual and in-person care may support self-management for individuals with MCC and social needs.

Current use of estrogen-containing oral contraceptives or hormone therapy and risk of COVID-19 infection and hospitalization: a population-based cohort study.

This population-based cohort study evaluated the association between current use of oral contraceptives (OC) among women under 50 years (n=306,541), and hormone therapy (HT) among women aged 50 or older (n=323,203), and COVID-19 infection and hospitalization. Current OC/HT use was recorded monthly using prescription dispensing data. COVID-19 infections were identified March 2020-February 2021. COVID-19 infection and hospitalization were identified through diagnosis codes and laboratory tests. Weighted generalized estimating equations models estimated multivariable-adjusted odds ratios (aORs) for COVID-19 infection associated with time-varying OC/HT use. Among women with COVID-19, logistic regression models evaluated OC/HT use and COVID-19 hospitalization. Over 12 months, 11,727 (3.8%) women <50 years and 8,661 (2.7%) women ≥50 years experienced COVID-19 infections. There was no evidence of an association between OC use and infection (aOR=1.05; 95%CI: 0.97, 1.12). There was a modest association between HT use and infection (aOR=1.19; 95%CI: 1.03, 1.38). Women using OC had a 39% lower risk of hospitalization (aOR=0.61; 95%CI: 0.38, 1.00), but there was no association of HT use with hospitalization (aOR=0.89; 95%CI: 0.51, 1.53). These findings do not suggest a meaningfully greater risk of COVID-19 infection associated with OC or HT use. OC use may be associated with lower COVID-19 hospitalization risk.

Evaluating the Safety of an Educational Deprescribing Intervention: Lessons from the Optimize Trial.

BACKGROUND: Patients, family members, and clinicians express concerns about potential adverse drug withdrawal events (ADWEs) following medication discontinuation or fears of upsetting a stable medical equilibrium as key barriers to deprescribing. Currently, there are limited methods to pragmatically assess the safety of deprescribing and ascertain ADWEs. We report the methods and results of safety monitoring for the OPTIMIZE trial of deprescribing education for patients, family members, and clinicians. METHODS: This was a pragmatic cluster randomized trial with multivariable Poisson regression comparing outcome rates between study arms. We conducted clinical record review and adjudication of sampled records to assess potential causal relationships between medication discontinuation and outcomes. This study included adults aged 65+ with dementia or mild cognitive impairment, one or more additional chronic conditions, and prescribed 5+ chronic medications. The intervention included an educational brochure on deprescribing that was mailed to patients prior to primary care visits, a clinician notification about individual brochure mailings, and an educational tip sheets was provided monthly to primary care clinicians. The outcomes of the safety monitoring were rates of hospitalizations and mortality during the 4 months following brochure mailings and results of record review and adjudication. The adjudication process was conducted throughout the trial and included classifications: likely, possibly, and unlikely. RESULTS: There was a total of 3012 (1433 intervention and 1579 control) participants. There were 420 total hospitalizations involving 269 (18.8%) people in the intervention versus 517 total hospitalizations involving 317 (20.1%) people in the control groups. Adjusted risk ratios comparing intervention to control groups were 0.92 [95% confidence interval (CI) 0.72, 1.16] for hospitalization and 1.19 (95% CI 0.67, 2.11) for mortality. Both groups had zero deaths "likely" attributed to a medication change prior to the event. A total of 3 out of 30 (10%) intervention group hospitalizations and 7 out of 35 (20%) control group hospitalizations were considered "likely" due to a medication change. CONCLUSIONS: Population-based deprescribing education is safe in the older adult population with cognitive impairment in our study. Pragmatic methods for safety monitoring are needed to further inform deprescribing interventions. TRIAL REGISTRATION: NCT03984396. Registered on 13 June 2019.

Ethical Aspects of Physician Decision-Making for Deprescribing Among Older Adults With Dementia.

Importance: Physicians endorse deprescribing of risky or unnecessary medications for older adults (aged ≥65 years) with dementia, but there is a lack of information on what influences decisions to deprescribe in this population. Objective: To understand how physicians make decisions to deprescribe for older adults with moderate dementia and ethical and pragmatic concerns influencing those decisions. Design, Setting, and Participants: A cross-sectional national mailed survey study of a random sample of 3000 primary care physicians from the American Medical Association Physician Masterfile who care for older adults was conducted from January 15 to December 31, 2021. Main Outcomes and Measures: The study randomized participants to consider 2 clinical scenarios in which a physician may decide to deprescribe a medication for older adults with moderate dementia: 1 in which the medication could cause an adverse drug event if continued and the other in which there is no evidence of benefit. Participants ranked 9 factors related to possible ethical and pragmatic concerns through best-worst scaling methods (from greatest barrier to smallest barrier to deprescribing). Conditional logit regression quantified the relative importance for each factor as a barrier to deprescribing. Results: A total of 890 physicians (35.0%) returned surveys; 511 (57.4%) were male, and the mean (SD) years since graduation was 26.0 (11.7). Most physicians had a primary specialty in family practice (50.4% [449 of 890]) and internal medicine (43.5% [387 of 890]). A total of 689 surveys were sufficiently complete to analyze. In both clinical scenarios, the 2 greatest barriers to deprescribing were (1) the patient or family reporting symptomatic benefit from the medication (beneficence and autonomy) and (2) the medication having been prescribed by another physician (autonomy and nonmaleficence). The least influential factor was ease of paying for the medication (justice). Conclusions and Relevance: Findings from this national survey study of primary care physicians suggests that understanding ethical aspects of physician decision-making can inform clinician education about medication management and deprescribing decisions for older adults with moderate dementia.

Telehealth During COVID-19 for Adults with Multiple Chronic Conditions: Associations with Self-Reported Food Insecurity and with Physical Limitations.

Background: Adults with chronic medical conditions complicated by food insecurity or physical limitations may have higher barriers to accessing telehealth implemented during the COVID-19 pandemic. Objective: To examine the relationships of self-reported food insecurity and physical limitations with changes in health care utilization and medication adherence comparing the year before (March 2019-February 2020) and the first year of the COVID-19 pandemic (April 2020-March 2021) among patients with chronic conditions insured by Medicaid or Medicare Advantage. Methods: A prospective cohort study of 10,452 Kaiser Permanente Northern California members insured by Medicaid and 52,890 Kaiser Permanente Colorado members insured by Medicare Advantage was conducted. Difference-in-differences (DID) between the pre-COVID and COVID years in telehealth versus in-person health care utilization and adherence to chronic disease medicines by food insecurity and by physical limitation status were measured. Results: Food insecurity and physical limitations were each associated with small but significantly greater shifts from in-person to telehealth. Medicare Advantage members with physical limitations also had significantly greater decline in adherence to chronic medications from year to year compared with those without physical limitations (DID from pre-COVID year to COVID year ranged from 0.7% to 3.6% greater decline by medication class, p < 0.01). Conclusions: Food insecurity and physical limitations did not present significant barriers to the transition to telehealth during the COVID pandemic. The greater decrease in medication adherence among older patients with physical limitations suggests that care systems must further address the needs of this high-risk population.

Association Between Diabetes Severity and Risks of COVID-19 Infection and Outcomes.

BACKGROUND: Little is known about whether diabetes increases the risk of COVID-19 infection and whether measures of diabetes severity are related to COVID-19 outcomes. OBJECTIVE: Investigate diabetes severity measures as potential risk factors for COVID-19 infection and COVID-19 outcomes. DESIGN, PARTICIPANTS, MEASURES: In integrated healthcare systems in Colorado, Oregon, and Washington, we identified a cohort of adults on February 29, 2020 (n = 1,086,918) and conducted follow-up through February 28, 2021. Electronic health data and death certificates were used to identify markers of diabetes severity, covariates, and outcomes. Outcomes were COVID-19 infection (positive nucleic acid antigen test, COVID-19 hospitalization, or COVID-19 death) and severe COVID-19 (invasive mechanical ventilation or COVID-19 death). Individuals with diabetes (n = 142,340) and categories of diabetes severity measures were compared with a referent group with no diabetes (n = 944,578), adjusting for demographic variables, neighborhood deprivation index, body mass index, and comorbidities. RESULTS: Of 30,935 patients with COVID-19 infection, 996 met the criteria for severe COVID-19. Type 1 (odds ratio [OR] 1.41, 95% CI 1.27-1.57) and type 2 diabetes (OR 1.27, 95% CI 1.23-1.31) were associated with increased risk of COVID-19 infection. Insulin treatment was associated with greater COVID-19 infection risk (OR 1.43, 95% CI 1.34-1.52) than treatment with non-insulin drugs (OR 1.26, 95% 1.20-1.33) or no treatment (OR 1.24; 1.18-1.29). The relationship between glycemic control and COVID-19 infection risk was dose-dependent: from an OR of 1.21 (95% CI 1.15-1.26) for hemoglobin A1c (HbA1c) < 7% to an OR of 1.62 (95% CI 1.51-1.75) for HbA1c ≥ 9%. Risk factors for severe COVID-19 were type 1 diabetes (OR 2.87; 95% CI 1.99-4.15), type 2 diabetes (OR 1.80; 95% CI 1.55-2.09), insulin treatment (OR 2.65; 95% CI 2.13-3.28), and HbA1c ≥ 9% (OR 2.61; 95% CI 1.94-3.52). CONCLUSIONS: Diabetes and greater diabetes severity were associated with increased risks of COVID-19 infection and worse COVID-19 outcomes.

Willingness of older people living with dementia and mild cognitive impairment and their caregivers to have medications deprescribed.

BACKGROUND: people living with cognitive impairment commonly take multiple medications including potentially inappropriate medications (PIMs), which puts them at risk of medication related harms. AIMS: to explore willingness to have a medication deprescribed of older people living with cognitive impairment (dementia or mild cognitive impairment) and multiple chronic conditions and assess the relationship between willingness, patient characteristics and belief about medications. METHODS: cross-sectional study using results from the revised Patients' Attitudes Towards Deprescribing questionnaire (rPATDcog) collected as baseline data in the OPTIMIZE study, a pragmatic, cluster-randomised trial educating patients and clinicians about deprescribing. Eligible participants were 65+, diagnosed with dementia or mild cognitive impairment, and prescribed at least five-long-term medications. RESULTS: the questionnaire was mailed to 1,409 intervention patients and 553 (39%) were returned and included in analysis. Participants had a mean age of 80.1 (SD 7.4) and 52.4% were female. About 78.5% (431/549) of participants said that they would be willing to have one of their medications stopped if their doctor said it was possible. Willingness to deprescribe was negatively associated with getting stressed when changes are made and with previously having a bad experience with stopping a medication (P < 0.001 for both). CONCLUSION: most older people living with cognitive impairment are willing to deprescribe. Addressing previous bad experiences with stopping a medication and stress when changes are made to medications may be key points to discuss during deprescribing conversations.

Intervention design in cognitively impaired populations-Lessons learned from the OPTIMIZE deprescribing pragmatic trial.

BACKGROUND: Polypharmacy is common in older adults with cognitive impairment and multiple chronic conditions, increasing risks of adverse drug events, hospitalization, and death. Deprescribing, the process of reducing or stopping potentially inappropriate medications, may improve outcomes. The OPTIMIZE pragmatic trial examined whether educating and activating patients, family members and clinicians about deprescribing reduces number of chronic medications and potentially inappropriate medications. Acceptability and challenges of intervention delivery in cognitively impaired older adults are not well understood. METHODS: We explored mechanisms of intervention implementation through post hoc qualitative interviews and surveys with stakeholder groups of 15 patients, 7 caregivers, and 28 clinicians. We assessed the context in which the intervention was delivered, its implementation, and mechanisms of impact. RESULTS: Acceptance of the intervention was affected by contextual factors including cognition, prior knowledge of deprescribing, communication, and time constraints. All stakeholder groups endorsed the acceptability, importance, and delivery of the intervention. Positive mechanisms of impact included patients scheduling specific appointments to discuss deprescribing and providers being prompted to consider deprescribing. Recollection of intervention materials was inconsistent but most likely shortly after intervention delivery. Short visit times remained the largest provider barrier to deprescribing. CONCLUSIONS: Our work identifies key learnings in intervention delivery that can guide future scaling of deprescribing interventions in this population. We highlight the critical roles of timing and repetition in intervention delivery to cognitively impaired populations and the barrier posed by short consultation times. The acceptability of the intervention to patients and family members highlights the potential to incorporate deprescribing education into routine clinical practice and expand proven interventions to other vulnerable populations.

Increased COVID-19 Infection Risk Drives Racial and Ethnic Disparities in Severe COVID-19 Outcomes.

COVID-19 inequities have been well-documented. We evaluated whether higher rates of severe COVID-19 in racial and ethnic minority groups were driven by higher infection rates by evaluating if disparities remained when analyses were restricted to people with infection. We conducted a retrospective cohort study of adults insured through Kaiser Permanente (Colorado, Northwest, Washington), follow-up in March-September 2020. Laboratory results and hospitalization diagnosis codes identified individuals with COVID-19. Severe COVID-19 was defined as invasive mechanical ventilation or mortality. Self-reported race and ethnicity, demographics, and medical comorbidities were extracted from health records. Modified Poisson regression estimated adjusted relative risks (aRRs) of severe COVID-19 in full cohort and among individuals with infection. Our cohort included 1,052,774 individuals, representing diverse racial and ethnic minority groups (e.g., 68,887 Asian, 41,243 Black/African American, 93,580 Hispanic or Latino/a individuals). Among 7,399 infections, 442 individuals experienced severe COVID-19. In the full cohort, severe COVID-19 aRRs for Asian, Black/African American, and Hispanic individuals were 2.09 (95% CI: 1.36, 3.21), 2.02 (1.39, 2.93), and 2.09 (1.57, 2.78), respectively, compared to non-Hispanic Whites. In analyses restricted to individuals with COVID-19, all aRRs were near 1, except among Asian Americans (aRR 1.82 [1.23, 2.68]). These results indicate increased incidence of severe COVID-19 among Black/African American and Hispanic individuals is due to higher infection rates, not increased susceptibility to progression. COVID-19 disparities most likely result from social, not biological, factors. Future work should explore reasons for increased severe COVID-19 risk among Asian Americans. Our findings highlight the importance of equity in vaccine distribution.

Recommendations for outcome measurement for deprescribing intervention studies.

Interpreting results from deprescribing interventions to generate actionable evidence is challenging owing to inconsistent and heterogeneous outcome definitions between studies. We sought to characterize deprescribing intervention outcomes and recommend approaches to measure outcomes for future studies. A scoping literature review focused on deprescribing interventions for polypharmacy and informed a series of expert panel discussions and recommendations. Twelve experts in deprescribing research, policy, and clinical practice interventions participating in the Measures Workgroup of the US Deprescribing Research Network sought to characterize deprescribing outcomes and recommend approaches to measure outcomes for future studies. The scoping review identified 125 papers reflecting 107 deprescribing studies. Common outcomes included medication discontinuation, medication appropriateness, and a broad range of clinical outcomes potentially resulting from medication reduction. Panel recommendations included clearly defining clinically meaningful medication outcomes (e.g., number of chronic medications, dose reductions), ensuring adequate sample size and follow-up time to capture clinical outcomes resulting from medication discontinuation (e.g., quality of life [QOL]), and selecting appropriate and feasible data sources. A new conceptual model illustrates how downstream clinical outcomes (e.g., reduction in falls) should be interpreted in the context of initial changes in medication measures (e.g., reduction in mean total medications). Areas needing further development include implementation outcomes specific to deprescribing interventions and measures of adverse drug withdrawal events. Generating evidence to guide deprescribing is essential to address patient, caregiver, and clinician concerns about the benefits and harms of medication discontinuation. This article provides recommendations and an initial conceptual framework for selecting and applying appropriate intervention outcomes to support deprescribing research.

Associations Between Different Self-reported Social Risks and Neighborhood-level Resources in Medicaid Patients.

BACKGROUND: Adverse social conditions are a key contributor to health disparities. Improved understanding of how social risk factors interact with each other and with neighborhood characteristics may inform efforts to reduce health disparities. DATA: A questionnaire of 29,281 patients was collected through the enrollment of Medicaid beneficiaries in a large Northern California integrated health care delivery system between May 2016 and February 2020. EXPOSURES: Living in the least resourced quartile of neighborhoods as measured by a census-tract level Neighborhood Deprivation Index score. MAIN OUTCOMES: Five self-reported social risk factors: financial need, food insecurity, housing barriers, transportation barriers, and functional limitations. RESULTS: Nearly half (42.0%) of patients reported at least 1 social risk factor; 22.4% reported 2 or more. Mean correlation coefficient between social risk factors was ρ=0.30. Multivariable logistic models controlling for age, race/ethnicity, sex, count of chronic conditions, and insurance source estimated that living in the least resourced neighborhoods was associated with greater odds of food insecurity (adjusted odds ratio=1.07, 95% confidence interval: 1.00-1.13) and transportation barriers (adjusted odds ratio=1.20, 95% confidence interval: 1.11-1.30), but not financial stress, housing barriers, or functional limitations. CONCLUSIONS AND RELEVANCE: We found that among 5 commonly associated social risk factors, Medicaid patients in a large Northern California health system typically reported only a single factor and that these factors did not correlate strongly with each other. We found only modestly greater social risk reported by patients in the least resourced neighborhoods. These results suggest that individual-level interventions should be targeted to specific needs whereas community-level interventions may be similarly important across diverse neighborhoods.

Prevalence of adverse childhood experiences and post traumatic stress disorder symptoms in a primary care safety-net population: Implications for healthcare service needs.

OBJECTIVE: We characterized the prevalence and associated characteristics of Adverse Childhood Experiences (ACEs) and Post-traumatic stress disorder (PTSD) in a safety net system and assessed patient preferences for trauma informed care. METHODS: We performed a cross-sectional survey among adult patients attending primary care at three urban federally qualified healthcare centers. We used a method of recruitment that included both convenience and systemic sampling. The survey included the ACEs Questionnaire, the PTSD for DSM 5 (PC-PTSD5), and trauma-informed care preferences. We accessed Electronic Health Records for demographic and clinical data. We used descriptive and multivariable statistical analyses. RESULTS: 303 of 481 (63%) patients that were approached participated. Most participants (81%) had one or more ACEs and 38% had four or more. 88 (29%) patients screened positive for current PTSD. ACEs was associated with a diagnosis of mental illness (p = 0.0125) and substance use disorders (p = 0.01). Patients with ACEs >/=4 or positive PC-PTSD reported stress in attending medical visits and that trauma-informed provider behaviors would make their visits less stressful. CONCLUSIONS: Rates of ACES and current PTSD symptoms were high in this population and support the need for research to evaluate universal trauma-informed care strategies for safety-net healthcare systems.

Clinical Factors Associated With Nonadherence to Chronic Medications in People With Cognitive Impairment.

Objective To study assessed adherence to 11 chronic medications and one medication class with high medical necessity in people with cognitive impairment (CIM) and identified clinical characteristics associated with nonadherence. Design This was a retrospective cohort study. 180-day adherence was calculated as the percent of days covered (PDC). Multi-variable logistic regression modeling was used to identify clinical factors associated with a PDC less than 80% (ie, nonadherence) to one or more studied chronic medication(s). Setting Primary care in an integrated health care delivery system. Patients People with CIM 65 years of age or older who were dispensed five or more chronic medications in one month between March 1, 2019, and October 31, 2019. Results Overall, the 1,109 patients included were older (mean age = 79.8 years of age), female (54.1%), White (78.6%), had a high burden of chronic disease, and 396 (35.7%) were nonadherent to one or more study medication(s). Two medications (tiotropium and venlafaxine) and one medication class (direct oral anticoagulants) had a mean PDC less than 80%. Alzheimer's disease and related dementias (ADRD), chronic pain, chronic obstructive pulmonary disease (COPD), male, nonwhite race, and one or more mental health visits were associated independently with nonadherence. Conclusions Chronic pain, COPD, ADRD, male sex, nonwhite race, and mental health care use were associated with nonadherence. These findings can help guide clinicians as they navigate medication therapy in people with CIM.

Deprescribing Education vs Usual Care for Patients With Cognitive Impairment and Primary Care Clinicians: The OPTIMIZE Pragmatic Cluster Randomized Trial.

Background: Individuals with dementia or mild cognitive impairment frequently have multiple chronic conditions (defined as ≥2 chronic medical conditions) and take multiple medications, increasing their risk for adverse outcomes. Deprescribing (reducing or stopping medications for which potential harms outweigh potential benefits) may decrease their risk of adverse outcomes. Objective: To examine the effectiveness of increasing patient and clinician awareness about the potential to deprescribe unnecessary or risky medications among patients with dementia or mild cognitive impairment. Design, Setting, and Participants: This pragmatic, patient-centered, 12-month cluster randomized clinical trial was conducted from April 1, 2019, to March 31, 2020, at 18 primary care clinics in a not-for-profit integrated health care delivery system. The study included 3012 adults aged 65 years or older with dementia or mild cognitive impairment who had 1 or more additional chronic medical conditions and were taking 5 or more long-term medications. Interventions: An educational brochure and a questionnaire on attitudes toward deprescribing were mailed to patients prior to a primary care visit, clinicians were notified about the mailing, and deprescribing tip sheets were distributed to clinicians at monthly clinic meetings. Main Outcomes and Measures: The number of prescribed long-term medications and the percentage of individuals prescribed 1 or more potentially inappropriate medications (PIMs). Analysis was performed on an intention-to-treat basis. Results: This study comprised 1433 individuals (806 women [56.2%]; mean [SD] age, 80.1 [7.2] years) in 9 intervention clinics and 1579 individuals (874 women [55.4%]; mean [SD] age, 79.9 [7.5] years) in 9 control clinics who met the eligibility criteria. At baseline, both groups were prescribed a similar mean (SD) number of long-term medications (7.0 [2.1] in the intervention group and 7.0 [2.2] in the control group), and a similar proportion of individuals in both groups were taking 1 or more PIMs (437 of 1433 individuals [30.5%] in the intervention group and 467 of 1579 individuals [29.6%] in the control group). At 6 months, the adjusted mean number of long-term medications was similar in the intervention and control groups (6.4 [95% CI, 6.3-6.5] vs 6.5 [95% CI, 6.4-6.6]; P = .14). The estimated percentages of patients in the intervention and control groups taking 1 or more PIMs were similar (17.8% [95% CI, 15.4%-20.5%] vs 20.9% [95% CI, 18.4%-23.6%]; P = .08). In preplanned subgroup analyses, adjusted differences between the intervention and control groups were -0.16 (95% CI, -0.34 to 0.01) for individuals prescribed 7 or more long-term medications at baseline (n = 1434) and -0.03 (95% CI, -0.20 to 0.13) for those prescribed 5 to 6 medications (n = 1578) (P = .28 for interaction; P = .19 for subgroup interaction for PIMs). Conclusions and Relevance: This large-scale educational deprescribing intervention for older adults with cognitive impairment taking 5 or more long-term medications and their primary care clinicians demonstrated small effect sizes and did not significantly reduce the number of long-term medications and PIMs. Such interventions should target older adults taking relatively more medications. Trial Registration: ClinicalTrials.gov Identifier: NCT03984396.

Accounting for Social Risk Does not Eliminate Race/Ethnic Disparities in COVID-19 Infection Among Insured Adults: a Cohort Study.

BACKGROUND: Communities of color have been disproportionately impacted by the COVID-19 epidemic in the USA. OBJECTIVES: To examine the relationship of self-reported social health needs with SARS-COV-2 infection by race/ethnicity among insured adults with access to high-quality health care. DESIGN AND PARTICIPANTS: A prospective cohort study of 26,741 adult Kaiser Permanente Northern California members insured by Medicaid and 58,802 Kaiser Permanente Colorado members insured by Medicare Advantage who completed social risk assessments prior to the onset of the COVID-19 pandemic. MAIN MEASURES: We examined the independent relationships of demographic, medical, and social factors on SARS-COV-2 testing and positivity between March 1, 2020, and November 30, 2020, by race/ethnicity. KEY RESULTS: Findings were similar in the two cohorts, with Latino (16-18%), Asian (11-14%), and Black (11-12%) members having the highest prevalence of SARS-COV-2 infection (ORs adjusted for age, gender, and use of interpreter ranging from 1.68 to 2.23 compared to White member [7-8%], p < 0.001). Further adjustment for medical comorbidity (e.g., obesity, diabetes, chronic lung disease); neighborhood measures; and self-reported social risk factors (e.g., trouble paying for basics, food insecurity, housing concerns, transportation barriers) did not appreciably change these results. CONCLUSIONS: Compared to non-Latino White members, members of other race/ethnic groups had higher positivity rates that were only minimally reduced after controlling for medical and neighborhood conditions and self-reported social risk factors. These findings suggest that traditional infection transmission factors such as essential work roles and household size that have disproportionate representation among communities of color may be important contributors to SARS-COV-2 infection among insured adults.

Aligning care with the personal values of patients with complex care needs.

OBJECTIVE: To identify opportunities to align care with the personal values of patients from three distinct groups with complex medical, behavioral, and social needs. DATA SOURCES/STUDY SETTING: Between June and August 2019, we conducted semi-structured interviews with individuals with complex care needs in two integrated health care delivery systems. STUDY DESIGN: Qualitative study using semi-structured interviews. DATA COLLECTION METHODS: We interviewed three groups of patients at Kaiser Permanente Washington and Kaiser Permanente Colorado representing three distinct profiles of complex care needs: Group A ("obesity, opioid prescription, and low-resourced neighborhood"), Group B ("older, high medical morbidity, emergency department, and hospital use"), and Group C ("older, mental and physical health concerns, and low-resourced neighborhood"). These profiles were identified based on prior work and prioritized by internal primary care stakeholders. Interview transcripts were analyzed using thematic analysis. PRINCIPAL FINDINGS: Twenty-four patients participated; eight from each complex needs profile. Mean age across groups was 71 (range 48-86) years. We identified five themes common across the three groups that captured patients' views regarding values-aligned care. These themes focused on the importance of care teams exploring and acknowledging a patient's values, providing access to nonphysician providers who have different perspectives on care delivery, offering values-aligned mental health care, ensuring connection to community-based resources that support values and address needs, and providing care that supports the patient plus their family and caregivers. CONCLUSIONS: Our results suggest several opportunities to improve how care is delivered to patients with different complex medical, behavioral, and social needs. Future research is needed to better understand how to incorporate these opportunities into health care.

Emerging models of care for individuals with multiple chronic conditions.

OBJECTIVE: To characterize emerging and current practice models to more effectively treat and support patients with multiple chronic conditions (MCC). DATA SOURCES/STUDY SETTING: We conducted a rapid literature scoping augmented by key informant interviews with clinicians knowledgeable about MCC care from a broad spectrum of US delivery systems and feedback from multidisciplinary experts at two virtual meetings. STUDY DESIGN: Literature findings were triangulated with data from semi-structured interviews with clinical experts. Reflections on early results were obtained from policy, research, clinical, advocacy, and patient representatives at two virtual meetings sponsored by the Agency for Healthcare Research and Quality. Emergent themes addressed were as follows: (1) more timely strategies for MCC care; and (2) trends not previously represented in the peer-reviewed literature. DATA COLLECTION/EXTRACTION METHODS: The rapid literature scoping relied on Ovid MEDLINE(R) and Epub Ahead of Print databases for the most recent 5-year period. Qualitative interviews were conducted by telephone. Virtual meetings provided oral and written (chat) captured inputs. PRINCIPAL FINDINGS: Although the literature scoping did not identify a specific set of evidence-based care models, key informant discussions identified eight themes reflecting emerging approaches to population-based MCC care. For example, addressing the needs of individuals with MCC through a complexity lens by assessing and addressing social risk factors; extending the care continuum with home-based care; understanding how to address ongoing patient and caregiver supports outside of clinical encounters; and engaging available community resources. CONCLUSIONS: Integrating care for MCC patient populations requires processes for determining different subpopulation needs in various settings and lived experiences. Innovation should be anchored at the nexus of payment systems, social risks, medical needs, and community-based resources. Our learnings suggest a need for an ongoing MCC care research agenda to inform new approaches to care delivery incorporating innovations in technology and home-based supports for patients and caregivers.

Measuring Multimorbidity: Selecting the Right Instrument for the Purpose and the Data Source.

BACKGROUND: Adults have a higher prevalence of multimorbidity-or having multiple chronic health conditions-than having a single condition in isolation. Researchers, health care providers, and health policymakers find it challenging to decide upon the most appropriate assessment tool from the many available multimorbidity measures. OBJECTIVE: The objective of this study was to describe a broad range of instruments and data sources available to assess multimorbidity and offer guidance about selecting appropriate measures. DESIGN: Instruments were reviewed and guidance developed during a special expert workshop sponsored by the National Institutes of Health on September 25-26, 2018. RESULTS: Workshop participants identified 4 common purposes for multimorbidity measurement as well as the advantages and disadvantages of 5 major data sources: medical records/clinical assessments, administrative claims, public health surveys, patient reports, and electronic health records. Participants surveyed 15 instruments and 2 public health data systems and described characteristics of the measures, validity, and other features that inform tool selection. Guidance on instrument selection includes recommendations to match the purpose of multimorbidity measurement to the measurement approach and instrument, review available data sources, and consider contextual and other related constructs to enhance the overall measurement of multimorbidity. CONCLUSIONS: The accuracy of multimorbidity measurement can be enhanced with appropriate measurement selection, combining data sources and special considerations for fully capturing multimorbidity burden in underrepresented racial/ethnic populations, children, individuals with multiple Adverse Childhood Events and older adults experiencing functional limitations, and other geriatric syndromes. The increased availability of comprehensive electronic health record systems offers new opportunities not available through other data sources.