Screening for Elder Abuse in the Veterans Health Administration: Varied Approaches Across a National Health System.

BACKGROUND: Elder abuse (EA) is common and has devastating health consequences yet is rarely detected by healthcare professionals. While EA screening tools exist, little is known about if and how these tools are implemented in real-world clinical settings. The Veterans Health Administration (VHA) has experience screening for, and resources to respond to, other forms of interpersonal violence and may provide valuable insights into approaches for EA screening. OBJECTIVE: Describe EA screening practices across a national integrated healthcare system serving a large population of older adults at risk for EA. DESIGN: Survey of all 139 VHA medical centers from January to August 2021. PARTICIPANTS: Surveys were completed by the Social Work Chief, or delegate, at each site. MAIN MEASURES: The survey assessed the presence and characteristics of EA-specific screening practices as well as general abuse/neglect screening conducted with patients of all ages, including older adults. Follow-up emails were sent to sites that reported screening requesting additional details not included in the initial survey. KEY RESULTS: Overall, 130 sites (94%) responded. Among respondents, 5 (4%) reported screening older adults for EA using a previously published tool, while 6 (5%) reported screening for EA with an unstudied or locally developed tool. Forty-eight percent reported screening patients of all ages for general abuse/neglect using unstudied questions/tools, and 44% reported no EA screening at their site. Characteristics of screening programs (e.g., frequency, clinical setting, provider type) varied widely between sites, as did respondents' understanding of the definition of screening. CONCLUSIONS: High variability in screening practices for abuse/neglect and lack of EA-specific screening in a system that has successfully deployed other standardized screening approaches present an important opportunity to standardize and improve EA detection practices. Lessons learned in VHA could help advance the evidence base for EA screening more broadly to increase overall detection rates for EA nationally.

The impact of dual VA-Medicare use on a data-driven clinical management tool for older Veterans with multimorbidity.

BACKGROUND: Healthcare systems are increasingly turning to data-driven approaches, such as clustering techniques, to inform interventions for medically complex older adults. However, patients seeking care in multiple healthcare systems may have missing diagnoses across systems, leading to misclassification of resulting groups. We evaluated the impact of multi-system use on the accuracy and composition of multimorbidity groups among older adults in the Veterans Health Administration (VA). METHODS: Eligible patients were VA primary care users aged ≥65 years and in the top decile of predicted 1-year hospitalization risk in 2018 (n = 558,864). Diagnoses of 26 chronic conditions were coded using a 24-month lookback period and input into latent class analysis (LCA) models. In a random 10% sample (n = 56,008), we compared the resulting model fit, class profiles, and patient assignments from models using only VA system data versus VA with Medicare data. RESULTS: LCA identified six patient comorbidity groups using VA system data. We labeled groups based on diagnoses with higher within-group prevalence relative to the average: Substance Use Disorders (7% of patients), Mental Health (15%), Heart Disease (22%), Diabetes (16%), Tumor (14%), and High Complexity (10%). VA with Medicare data showed improved model fit and assigned more patients with high accuracy. Over 70% of patients assigned to the Substance, Mental Health, High Complexity, and Tumor groups using VA data were assigned to the same group in VA with Medicare data. However, 41.9% of the Heart Disease group and 14.7% of the Diabetes group were reassigned to a new group characterized by multiple cardiometabolic conditions. CONCLUSIONS: The addition of Medicare data to VA data for older high-risk adults improved clustering model accuracy and altered the clinical profiles of groups. Accessing or accounting for multi-system data is key to the success of interventions based on empiric grouping in populations with dual-system use.

Patterns of Telemedicine Use and Glycemic Outcomes of Endocrinology Care for Patients With Type 2 Diabetes.

Importance: Telemedicine can increase access to endocrinology care for people with type 2 diabetes (T2D), but patterns of use and outcomes of telemedicine specialty care for adults with T2D beyond initial uptake in 2020 are not known. Objective: To evaluate patterns of telemedicine use and their association with glycemic control among adults with varying clinical complexity receiving endocrinology care for T2D. Design, Setting, and Participants: Retrospective cohort study in a single large integrated US health system. Participants were adults who had a telemedicine endocrinology visit for T2D from May to October 2020. Data were analyzed from June 2022 to October 2023. Exposure: Patients were followed up through May 2022 and assigned to telemedicine-only, in-person, or mixed care (both telemedicine and in-person) cohorts according to visit modality. Main Outcomes and Measures: Multivariable regression models were used to estimate hemoglobin A1c (HbA1c) change at 12 months within each cohort and the association of factors indicating clinical complexity (insulin regimen and cardiovascular and psychological comorbidities) with HbA1c change across cohorts. Subgroup analysis was performed for patients with baseline HbA1c of 8% or higher. Results: Of 11 498 potentially eligible patients, 3778 were included in the final cohort (81 Asian participants [2%], 300 Black participants [8%], and 3332 White participants [88%]); 1182 used telemedicine only (mean [SD] age 57.4 [12.9] years; 743 female participants [63%]), 1049 used in-person care (mean [SD] age 63.0 [12.2] years; 577 female participants [55%]), and 1547 used mixed care (mean [SD] age 60.7 [12.5] years; 881 female participants [57%]). Among telemedicine-only patients, there was no significant change in adjusted HbA1c at 12 months (-0.06%; 95% CI, -0.26% to 0.14%; P = .55) while in-person and mixed cohorts had improvements of 0.37% (95% CI, 0.15% to 0.59%; P < .001) and 0.22% (95% CI, 0.07% to 0.38%; P = .004), respectively. Patients with a baseline HbA1c of 8% or higher had a similar pattern of glycemic outcomes. For patients prescribed multiple daily injections vs no insulin, the 12-month estimated change in HbA1c was 0.25% higher (95% CI, 0.02% to 0.47%; P = .03) for telemedicine vs in-person care. Comorbidities were not associated with HbA1c change in any cohort. Conclusions and Relevance: In this cohort study of adults with T2D receiving endocrinology care, patients using telemedicine alone had inferior glycemic outcomes compared with patients who used in-person or mixed care. Additional strategies may be needed to support adults with T2D who rely on telemedicine alone to access endocrinology care, especially for those with complex treatment or elevated HbA1c.

Unhealthy alcohol use and brief intervention rates among high and low complexity veterans seeking primary care services in the Veterans Health Administration.

INTRODUCTION: Brief intervention (BI) is recommended for all primary care (PC) patients who screen positive for unhealthy alcohol use; however, patients with multiple chronic health conditions who are at high-risk of hospitalization (i.e., "high complexity" patients) may face disparities in receiving BIs in PC. The current study investigated whether high complexity and low complexity patients in the Veterans Health Administration (VHA) differed regarding screening positive for unhealthy alcohol use, alcohol-use severity, and receipt of BI for those with unhealthy alcohol use. METHODS: Patients were veterans receiving PC services at the VHA in a mid-Atlantic region of the United States. The study extracted VHA administrative and clinical data for a total of 282,242 patients who had ≥1 PC visits between 1/1/2014 and 12/31/2014, during which they were screened for unhealthy alcohol use by the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C). The study defined high complexity patients as those within and above the 90th percentile of risk for hospitalization per the VHA's Care Assessment Need Score. Logistic regression models assessed if being a high complexity patient was associated with screening positive for unhealthy alcohol use (AUDIT-C ≥ 5), severity of unhealthy alcohol use in those who screened positive (AUDIT-C score range 5-12), and receipt of BI in those who screened positive. RESULTS: Our sample was 94.5% male, 83% White, 13% Black, 4% other race, and 1.7% Hispanic. A total of 10,813 (3.8%) patients screened positive for unhealthy alcohol use from which we identified 569 (5.3%) high complexity and 10,128 (93.6%) low complexity patients (n = 116 removed due to missing complexity data). Relative to low complexity patients, high complexity patients were less likely to screen positive for unhealthy alcohol use (3.3% vs. 4.1%, AOR = 0.59, p < .001); however, in patients who screened positive, high complexity patients had higher AUDIT-C scores (Mean AUDIT-C = 7.75 vs. 6.87, AOR = 1.46, p < .001) and were less likely to receive a BI (78.0% vs. 92.6%, AOR = 0.42, p < .001). CONCLUSIONS: Disparities in BI exist for highly complex patients despite having more severe unhealthy alcohol use. Future research should examine the specific patient- and/or clinic-level factors impeding BI delivery for complex patients.

Changes in Primary Care Quality Associated With Implementation of the Veterans Health Administration Preventive Health Inventory.

Importance: The COVID-19 pandemic caused significant disruptions in primary care delivery. The Veterans Health Administration (VHA) launched the Preventive Health Inventory (PHI) program-a multicomponent care management intervention, including a clinical dashboard and templated electronic health record note-to support primary care in delivering chronic disease care and preventive care that had been delayed by the pandemic. Objectives: To describe patient, clinician, and clinic correlates of PHI use in primary care clinics and to examine associations between PHI adoption and clinical quality measures. Design, Setting, and Participants: This quality improvement study used VHA administrative data from February 1, 2021, through February 28, 2022, from a national cohort of 216 VHA primary care clinics that have implemented the PHI. Participants comprised 829 527 veterans enrolled in primary care in clinics with the highest and lowest decile of PHI use as of February 2021. Exposure: Templated electronic health record note documenting use of the PHI. Main Outcomes and Measures: Diabetes and blood pressure clinical quality measures were the primary outcomes. Interrupted time series models were applied to estimate changes in diabetes and hypertension quality measures associated with PHI implementation. Low vs high PHI use was stratified at the facility level to measure whether systematic differences in uptake were associated with quality. Results: A total of 216 primary clinics caring for 829 527 unique veterans (mean [SD] age, 64.1 [16.9] years; 755 158 of 829 527 [91%] were men) formed the study cohort. Use of the PHI varied considerably across clinics. The clinics in the highest decile of PHI use completed a mean (SD) of 32 997.4 (14 019.3) notes in the electronic health record per 100 000 veterans compared with 56.5 (35.3) notes per 100 000 veterans at the clinics in the lowest decile of use (P < .001). Compared with the clinics with the lowest use of the PHI, clinics with the highest use had a larger mean (SD) clinic size (12 072 [7895] patients vs 5713 [5825] patients; P < .001), were more likely to be urban (91% vs 57%; P < .001), and served more non-Hispanic Black veterans (16% vs 5%; P < .001) and Hispanic veterans (14% vs 4%; P < .001). Staffing did not differ meaningfully between high- and low-use clinics (mean [SD] ratio of full-time equivalent staff to clinician, 3.4 [1.2] vs 3.4 [0.8], respectively; P < .001). After PHI implementation, compared with the clinics with the lowest use, those with the highest use had fewer veterans with a hemoglobin A1c greater than 9% or missing (mean [SD], 6577 [3216] per 100 000 veterans at low-use clinics; 9928 [4236] per 100 000 veterans at high-use clinics), more veterans with an annual hemoglobin A1c measurement (mean [SD], 13 181 [5625] per 100 000 veterans at high-use clinics; 8307 [3539] per 100 000 veterans at low-use clinics), and more veterans with adequate blood pressure control (mean [SD], 20 582 [12 201] per 100 000 veterans at high-use clinics; 12 276 [6850] per 100 000 veterans at low-use clinics). Conclusions and Relevance: This quality improvement study of the implementation of the VHA PHI suggests that higher use of a multicomponent care management intervention was associated with improved quality-of-care metrics. The study also found significant variation in PHI uptake, with higher uptake associated with clinics with more racial and ethnic diversity and larger, urban clinic sites.

Specialist Perspectives on Delivering High-Quality Telemedicine for Diabetes: A Mixed Methods Survey Study.

Background: Recent recommendations guiding appropriate use of telemedicine for endocrinology care have largely relied on expert opinion due to limited evidence on factors that increase quality of telemedicine care. In this study, we assessed the perspectives of front-line specialists on factors and strategies perceived to increase quality of diabetes care delivered via telemedicine after more than 2 years of widespread use. Methods: Adult diabetes specialists in 2 academic health systems who recently used video-based telemedicine to provide diabetes care were invited to participate in an online survey study between March and April 2022. Likert-style questions, followed by related open-ended questions, assessed perspectives on availability of key resources, factors affecting quality, and anticipated benefits from telemedicine for diabetes. Results: Response rate was 52% (56/111). More than half (54%) of participants reported better overall quality of diabetes care with face-to-face care vs telemedicine. Participants reported clinical data supporting high-quality care, such as home blood glucose readings and vital signs, were often not available with telemedicine. Patient factors, including comorbidities and communication barriers, reduced anticipated benefit from telemedicine, while geographic and mobility barriers increased expected benefit. Providers described multiple health care setting resources that could promote high-quality telemedicine diabetes care, including greater support for sharing patient-generated health data and coordinating multidisciplinary care. Conclusions: After 2 years of sustained use, diabetes specialists identified telemedicine as an important way to enhance access to care. However, specialists identified additional supports needed to increase appropriate use and delivery of high-quality telemedicine care for patients with complex clinical needs.

Adherence to Diabetes Medications and Health Care Use During the COVID-19 Pandemic Among High-Risk Patients.

INTRODUCTION: The COVID-19 pandemic caused potentially disruptive shocks to chronic condition care. We examined how diabetes medication adherence, related hospitalizations, and primary care use changed in high-risk veterans prepandemic and postpandemic. METHODS: We conducted longitudinal analyses on a cohort of high-risk diabetes patients in the Veterans Affairs (VA) health care system. Primary care visits by modality, medication adherence, and VA acute hospitalizations and emergency department (ED) visits were measured. We also estimated differences for subgroups of patients by race/ethnicity, age, and rural/urban location. RESULTS: Patients were 95% male with mean age 68 years. Prepandemic patients received a mean per quarter of 1.5 in-person primary care visits and 1.3 virtual visits, 0.10 hospitalizations, and 0.22 ED visits, with mean adherence of 0.82. The early pandemic was associated with fewer in-person primary care visits, more virtual visits, fewer hospitalizations and ED visits per patient, and no change in adherence; there were no midpandemic versus prepandemic differences in hospitalizations or adherence. Black and nonelderly patients had lower adherence during the pandemic. CONCLUSION: Adherence to diabetes medications and primary care use remained high for most patients even though virtual care replaced in-person care. Black and nonelderly patients may require additional intervention to address lower adherence.

Frailty predicts referral for elder abuse evaluation in a nationwide healthcare system-Results from a case-control study.

BACKGROUND: Elder abuse (EA) is common and has devastating health impacts. Frailty may increase susceptibility to and consequences of EA for older adults, making healthcare system detection more likely, but this relationship has been difficult to study. We examined the association between a recently validated frailty index and referral to social work (SW) for EA evaluation in the Veterans Administration (VA) healthcare system. METHODS: We conducted a case-control study of veterans aged ≥60 years evaluated by SW for suspected EA between 2010 and 2018 (n = 14,723) and controls receiving VA primary care services in the same 60-day window (n = 58,369). We used VA and Medicare claims data to measure frailty (VA Frailty Index) and comorbidity burden (the Elixhauser Comorbidity Index) in the 2 years prior to the index. We used adjusted logistic regression models to examine the association of frailty or comorbidity burden with referral to SW for EA evaluation. We used Akaike Information Criterion (AIC) values to evaluate model fit and likelihood ratio (LR) tests to assess the statistical significance of including frailty and comorbidity in the same model. RESULTS: The sample (n = 73,092) had a mean age 72 years; 14% were Black, and 6% were Hispanic. More cases (67%) than controls (36%) were frail. LR tests comparing the nested models were highly significant (p < 0.001), and AIC values indicated superior model fit when including both frailty and comorbidity in the same model. In a model adjusting for comorbidity and all covariates, pre-frailty (aOR vs. robust 1.7; 95% CI 1.5-1.8) and frailty (aOR vs. robust 3.6; 95% CI 3.3-3.9) were independently associated with referral for EA evaluation. CONCLUSIONS: A claims-based measure of frailty predicted referral to SW for EA evaluation in a national healthcare system, independent of comorbidity burden. Electronic health record measures of frailty may facilitate EA risk assessment and detection for this important but under-recognized phenomenon.

High-Risk Patient Experiences Associated With an Intensive Primary Care Management Program in the Veterans Health Administration.

Intensive management programs may improve health care experiences among high-risk and complex patients. We assessed patient experience among (1) prior enrollees (n = 59) of an intensive management program (2014-2018); (2) nonenrollees (n = 356) at program sites; and (3) nonprogram site patients (n = 728), using a patient survey based on the Consumer Assessment of Healthcare Providers and Systems in 2019. Outcomes included patient ratings of patient-centered care; overall health care experience; and satisfaction with their usual outpatient care provider. In multivariate models, enrollees were more satisfied with their current provider versus nonenrollees within program sites (adjusted odds ratio 2.36; 95% confidence interval 1.15-4.85).

Effectiveness of a Health Coaching Intervention for Patient-Family Dyads to Improve Outcomes Among Adults With Diabetes: A Randomized Clinical Trial.

Importance: More than 75% of US adults with diabetes do not meet treatment goals. More effective support from family and friends ("supporters") may improve diabetes management and outcomes. Objective: To determine if the Caring Others Increasing Engagement in Patient Aligned Care Teams (CO-IMPACT) intervention improves patient activation, diabetes management, and outcomes compared with standard care. Design, Setting, and Participants: This randomized clinical trial was conducted from November 2016 to August 2019 among participants recruited from 2 Veterans Health Administration primary care sites. All patient participants were adults aged 30 to 70 years with diabetes who had hemoglobin A1c (HbA1c) levels greater than 8% of total hemoglobin (to convert to proportion of total hemoglobin, multiply by 0.01) or systolic blood pressure (SBP) higher than 150 mm Hg; each participating patient had an adult supporter. Of 1119 recruited, 239 patient-supporter dyads were enrolled between November 2016 and May 2018, randomized 1:1 to receive the CO-IMPACT intervention or standard care, and followed up for 12 to 15 months. Investigators and analysts were blinded to group assignment. Interventions: Patient-supporter dyads received a health coaching session focused on dyadic information sharing and positive support techniques, then 12 months of biweekly automated monitoring telephone calls to prompt dyadic actions to meet diabetes goals, coaching calls to help dyads prepare for primary care visits, and after-visit summaries. Standard-care dyads received general diabetes education materials only. Main Outcomes and Measures: Intent-to-treat analyses were conducted according to baseline dyad assignment. Primary prespecified outcomes were 12-month changes in Patient Activation Measure-13 (PAM-13) and UK Prospective Diabetes Study (UKPDS) 5-year diabetes-specific cardiac event risk scores. Secondary outcomes included 12-month changes in HbA1c levels, SBP, diabetes self-management behaviors, diabetes distress, diabetes management self-efficacy, and satisfaction with health system support for the involvement of family supporters. Changes in outcome measures between baseline and 12 months were analyzed using linear regression models. Results: A total of 239 dyads enrolled; among patient participants, the mean (SD) age was 60 (8.9) years, and 231 (96.7%) were male. The mean (SD) baseline HbA1c level was 8.5% (1.6%) and SBP was 140.2 mm Hg (18.4 mm Hg). A total of 168 patients (70.3%) lived with their enrolled supporter; 229 patients (95.8%) had complete 12-month outcome data. In intention-to-treat analyses vs standard care, CO-IMPACT patients had greater 12-month improvements in PAM-13 scores (intervention effect, 2.60 points; 95% CI, 0.02-5.18 points; P = .048) but nonsignificant differences in UKPDS 5-year cardiac risk (intervention effect, 1.01 points; 95% CI, -0.74 to 2.77 points; P = .26). Patients in the CO-IMPACT arm also had greater 12-month improvements in healthy eating (intervention effect, 0.71 d/wk; 95% CI, 0.20-1.22 d/wk; P = .007), diabetes self-efficacy (intervention effect, 0.40 points; 95% CI, 0.09-0.71 points; P = .01), and satisfaction with health system support for the family supporter participants' involvement (intervention effect, 0.28 points; 95% CI, 0.07-0.49 points; P = .009); however, the 2 arms had similar improvements in HbA1c levels and in other measures. Conclusions and Relevance: In this randomized clinical trial, the CO-IMPACT intervention successfully engaged patient-supporter dyads and led to improved patient activation and self-efficacy. Physiological outcomes improved similarly in both arms. More intensive direct coaching of supporters, or targeting patients with less preexisting support or fewer diabetes management resources, may have greater impact. Trial Registration: ClinicalTrials.gov Identifier: NCT02328326.

Primary Care Physician Perspectives on the Influence of Patient Values, Health Priorities, and Preferences on Clinical Decision-Making for Complex Patients with Multimorbidity: A Qualitative Study.

Introduction: The prevalence of patients with multimorbidity (ie, multiple chronic conditions) is increasing. Clinical decision-making guided by patients' values, health priorities and goals, and treatment preferences is particularly important in the context of interacting diseases and psychosocial needs. Physicians face challenges incorporating patient perspectives into care plans. We examined primary care physician (PCP) views on the influence of patients' values, health priorities and goals, and preferences on clinical decisions for patients with multimorbidity and increased psychosocial complexity. Methods: We conducted semi-structured telephone interviews with 23 PCPs within patient-centered medical home teams in a nationally integrated health system in the United States between May and July 2020. Data were analyzed via thematic analysis with deductive and inductive coding. Results: Three major themes emerged: 1. Patient personal values were rarely explicitly discussed in routine clinical encounters but informed more commonly discussed concepts of patient priorities, goals, and preferences; 2. Patient values, health priorities and goals, and preferences were sources of divergent views about care plans between healthcare teams, patients, and families; 3. Physicians used explicit strategies to communicate and negotiate about patient values, health priorities and goals, and preferences when developing care plans, including trust-building; devoting extra effort to individualizing care; connecting patient values to healthcare recommendations; deliberate elicitation and acknowledgement of patient concerns; providing "space" for patient perspectives; incorporating family into care planning; pairing physician to patient priorities; and collaborative teamwork. Conclusion: Primary care physicians perceive patient values, health priorities and goals, and preferences as influential during clinical decision-making for complex patients with multimorbidity. Participants used concrete strategies to negotiate alignment of these aspects when physician-patient divergence occurred. While rarely discussed directly in clinical encounters, personal values affected patient health priorities, goals, and preferences during care planning, suggesting a clinical role for more deliberate elicitation and discussion of patient values for this population.

Two-year change in latent classes of comorbidity among high-risk Veterans in primary care: a brief report.

BACKGROUND: Segmentation models such as latent class analysis are an increasingly popular approach to inform group-tailored interventions for high-risk complex patients. Multiple studies have identified clinically meaningful high-risk segments, but few have evaluated change in groupings over time. OBJECTIVES: To describe population-level and individual change over time in latent comorbidity groups among Veterans at high-risk of hospitalization in the Veterans Health Administration (VA). RESEARCH DESIGN: Using a repeated cross-sectional design, we conducted a latent class analysis of chronic condition diagnoses. We compared latent class composition, patient high-risk status, and patient class assignment in 2018 to 2020. SUBJECTS: Two cohorts of eligible patients were selected: those active in VA primary care and in the top decile of predicted one-year hospitalization risk in 2018 (n = 951,771) or 2020 (n = 978,771). MEASURES: Medical record data were observed from January 2016-December 2020. Latent classes were modeled using indicators for 26 chronic health conditions measured with a 2-year lookback period from study entry. RESULTS: Five groups were identified in both years, labeled based on high prevalence conditions: Cardiometabolic (23% in 2018), Mental Health (18%), Substance Use Disorders (16%), Low Diagnosis (25%), and High Complexity (10%). The remaining 8% of 2018 patients were not assigned to a group due to low predicted probability. Condition prevalence overall and within groups was stable between years. However, among the 563,725 patients identified as high risk in both years, 40.8% (n = 230,185) had a different group assignment in 2018 versus 2020. CONCLUSIONS: In a repeated latent class analysis of nearly 1 million Veterans at high-risk for hospitalization, population-level groups were stable over two years, but individuals often moved between groups. Interventions tailored to latent groups need to account for change in patient status and group assignment over time.

Comparing the effectiveness of Family Support for Health Action (FAM-ACT) with traditional community health worker-led interventions to improve adult diabetes management and outcomes: study protocol for a randomized controlled trial.

BACKGROUND: Diabetes self-management education and support (DSMES) programs have struggled to deliver sustainable, effective support for adults with diabetes (AWDs) to improve self-management behaviors, achieve glycemic goals, and reduce risk for complications. One largely untapped resource for this support is AWDs' social networks. Fifty to 75% of AWDs have an unpaid family member or friend ("support person") who provides ongoing help with diabetes management. However, DSMES interventions to date lack structured and effective approaches to directly engage support persons in AWDs' diabetes management. METHODS: This parallel arm randomized trial is designed to determine the effectiveness of Family Support for Health Action (FAM-ACT), a novel community health worker (CHW)-delivered program focused on educating and supporting patients with type 2 diabetes (T2D) and their support persons (SPs), relative to an established, CHW-delivered, individual patient-focused DSMES and care management (I-DSMES) intervention. Both interventions were developed using a community-based participatory research (CBPR) approach. The study will be conducted in partnership with an urban Federally Qualified Health Center (FQHC) serving a low-income, Latino/a community, with target enrollment of 268 dyads consisting of an FQHC patient with T2D with high HbA1c and an SP. Patient-SP dyads will be randomized to receive FAM-ACT or I-DSMES over 6 months. The primary outcome is change in patient HbA1c from baseline to 6 months. Secondary patient outcomes include 12-month change in HbA1c, changes in patient blood pressure, diabetes self-management behaviors, diabetes distress, patient activation, diabetes self-efficacy, and perceptions of and satisfaction with SP support for diabetes. Secondary SP outcomes include self-efficacy for helping the patient with diabetes management and SP distress about the patient's diabetes. We also will assess the effect of the COVID-19 pandemic on patient's ability to manage diabetes. DISCUSSION: This study will inform scalable, evidence-based approaches that leverage family support to help AWDs improve and sustain self-management strategies that underpin optimal management of multiple diabetes complication risk factors. The protocol is designed for and evaluated with a low-income and predominantly Latino/a community, which may increase applicability to other similar communities. The COVID-19 pandemic presented several challenges to study protocol and intervention delivery; modifications made to address these challenges are described. TRIAL REGISTRATION: ClinicalTrials.gov NCT03812614. Registered on 18 January 2019.

Family caregivers navigating the health care system: Evolving roles during the COVID-19 pandemic.

INTRODUCTION: The COVID-19 pandemic has altered access to health care; it remains unclear how patients with chronic illness and disability and their family caregivers are adapting to these changes. In this study, we examined changes in family caregiver roles helping care recipients with chronic illness and disability navigate health care needs during the COVID-19 pandemic. METHODS: From April 15 to May 27, 2020, we distributed online and telephone surveys to family caregiver members of a population-based regional research registry. Caregivers reported whether they were helping "more," "less," or the "same" with ten health care activities (e.g., filling prescriptions, attending medical appointments) now, compared to before the coronavirus pandemic. Using multivariable logistic regression models, we examined caregiver and caregiving context characteristics associated with helping more with 1 or more health care activities. RESULTS: Of 561 caregiver respondents, mean age was 59 years, 76% were women, and 56% co-resided with care recipients. Many caregivers (59%) reported increased help with 1 or more health care activities since the pandemic. Caregivers reported greater help getting medical supplies (31%) and attending care recipients' phone (21%) and video (16%) medical appointments. Women (OR 1.55; 95% CI 1.02-2.36) and caregivers assisting with short-term physical conditions were more likely to help more with 1 or more health care activities (OR 2.81; 95% CI 1.20-6.59). DISCUSSION: Family caregivers reported their responsibilities helping care recipients with chronic conditions and disabilities stay engaged with health care increased since the pandemic. Providers and health systems should consider targeted strategies to support caregivers helping vulnerable patients access necessary care. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Factors Associated With Patient-Centered Medical Home Teams' Use of Resources for Identifying and Approaches for Managing Patients With Complex Needs.

Using data from a Veterans Health Administration national primary care survey, this study identified the most highly rated tools and care approaches for patients with complex needs and how preferences varied by professional role, staffing, and training. Nurses were significantly more likely to rate most tools as very important as compared with primary care providers. Having a fully staffed team was also significantly associated with a very important rating on all tools. Nurses and fully staffed teams reported a greater likeliness to use most care approaches, and those with perceived need for training reporting a lower likeliness to use.

My Goals Are Not Their Goals: Barriers and Facilitators to Delivery of Patient-Centered Care for Patients with Multimorbidity.

BACKGROUND: Patient-centered care reflecting patient preferences and needs is integral to high-quality care. Individualized care is important for psychosocially complex or high-risk patients with multiple chronic conditions (i.e., multimorbidity), given greater potential risks of interventions and reduced benefits. These patients are increasingly prevalent in primary care. Few studies have examined provision of patient-centered care from the clinician perspective, particularly from primary care physicians serving in integrated, patient-centered medical home settings within the US Veterans Health Administration. OBJECTIVE: We sought to clarify facilitators and barriers perceived by primary care physicians in the Veterans Health Administration to delivering patient-centered care for high-risk or complex patients with multimorbidity. DESIGN: We conducted semi-structured telephone interviews from April to July 2020 among physicians across 20 clinical sites. Findings were analyzed with deductive content analysis based on conceptual models of patient-centeredness and hierarchical factors affecting care delivery. PARTICIPANTS: Of 23 physicians interviewed, most were female (n = 14/23, 61%), serving in hospital-affiliated outpatient clinics (n = 14/23, 61%). Participants had a mean of 21 (SD = 11.3) years of experience. KEY RESULTS: Facilitators included the following: effective physician-patient communication to individualize care, prioritize among multiple needs, and elicit goals to improve patient engagement; access to care, enabled by interdisciplinary teams, and dictating personalized care planning; effortful but worthwhile care coordination and continuity; meeting complex needs through effective teamwork; and integrating medical and non-medical care aspects in recognition of patients' psychosocial contexts. Barriers included the following: intra- and interpersonal (e.g., perceived patient reluctance to engage in care); organizational (e.g., limited encounter time); and community or policy impediments (e.g., state decisional capacity laws) to patient-centered care. CONCLUSIONS: Physicians perceived individual physician-patient interactions were the greatest facilitators or barriers to patient-centered care. Efforts to increase primary care patient-centeredness for complex or high-risk patients with multimorbidity could focus on targeting physician-patient communication and reducing interpersonal conflict.

Caregiver role development in chronic disease: A qualitative study of informal caregiving for veterans with diabetes.

OBJECTIVE: Support for chronic conditions such as diabetes from friends and family positively influences health management and outcomes, but limited data exist on how and why caregivers assume specific support roles for otherwise independent aging adults. We conducted a qualitative study to examine the nature of caregivers' roles in supporting Veterans' management of a chronic condition and caregivers' reasons for assuming those roles, using Type 2 diabetes as an example. METHODS: Thirty-two interviews were conducted with Veterans with Type 2 diabetes (n = 20) and their caregivers (n = 12). Two coders independently analyzed interview transcripts using a thematic analysis approach. RESULTS: Three central roles of caregivers in diabetes management were described: direct care support, memory support/care organizer, and advocate. Three explanations for assuming caregiving roles emerged: changes in patient health, natural evolution of family roles, and caregivers' health care experience or training. DISCUSSION: Understanding what roles caregivers fill and why is critical to designing services to support caregivers in helping improve chronic health condition management for aging adults.

Changes in Self-management During the COVID-19 Pandemic Among Adults with Type 2 Diabetes at a Federally Qualified Health Center.

The COVID-19 pandemic affected how adults with diabetes perform self-management, and impacts may be greater among vulnerable populations. We assessed the impact of the pandemic on diabetes self-management among adults with type 2 diabetes at a Federally Qualified Health Center. Participants were surveyed by phone in Spanish and English from July to October of 2020. Most respondents (74%) were Latino and preferred to speak Spanish, with mean age of 54 years and mean HbA1c of 9.2%. Fifty-three percent reported less physical activity during the pandemic. While 43% had more difficulty obtaining healthy food, 38% reported eating more healthfully. Sixty-one percent had increased difficulty accessing medical care. Many felt more socially isolated (49%) and stressed (51%). Changes in diabetes self-management were both positive and negative for majority Latino patients in this low-resource community, which may require tailored approaches to mitigate negative impacts of the pandemic on physical and mental health.

Association of Integrated Mental Health Services with Physical Health Quality Among VA Primary Care Patients.

BACKGROUND: Integrated care for comorbid depression and chronic medical disease improved physical and mental health outcomes in randomized controlled trials. The Veterans Health Administration (VA) implemented Primary Care-Mental Health Integration (PC-MHI) across all primary care clinics nationally to increase access to mental/behavioral health treatment, alongside physical health management. OBJECTIVE: To examine whether widespread, pragmatic PC-MHI implementation was associated with improved care quality for chronic medical diseases. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included 828,050 primary care patients with at least one quality metric among 396 VA clinics providing PC-MHI services between October 2013 and September 2016. MAIN MEASURE(S): For outcome measures, chart abstractors rated whether diabetes and cardiovascular quality metrics were met for patients at each clinic as part of VA's established quality reporting program. The explanatory variable was the proportion of primary care patients seen by integrated mental health specialists in each clinic annually. Multilevel logistic regression models examined associations between clinic PC-MHI proportion and patient-level quality metrics, adjusting for regional, patient, and time-level effects and clinic and patient characteristics. KEY RESULTS: Median proportion of patients seen in PC-MHI per clinic was 6.4% (IQR=4.7-8.7%). Nineteen percent of patients with diabetes had poor glycemic control (hemoglobin A1c >9%). Five percent had severely elevated blood pressure (>160/100 mmHg). Each two-fold increase in clinic PC-MHI proportion was associated with 2% lower adjusted odds of poor glycemic control (95% CI=0.96-0.99; p=0.046) in diabetes. While there was no association with quality for patients diagnosed with hypertension, patients without diagnosed hypertension had 5% (CI=0.92-0.99; p=0.046) lower adjusted odds of having elevated blood pressures. CONCLUSIONS AND RELEVANCE: Primary care clinics where integrated mental health care reached a greater proportion of patients achieved modest albeit statistically significant gains in key chronic care quality metrics, providing optimism about the expected effects of large-scale PC-MHI implementation on physical health.