Mortality Among US Veterans Admitted to Community vs Veterans Health Administration Hospitals for COVID-19.

Importance: Veterans Health Administration (VHA) enrollees receive care for COVID-19 in both VHA and non-VHA (ie, community) hospitals, but little is known about the frequency or outcomes of care for veterans with COVID-19 in VHA vs community hospitals. Objective: To compare outcomes among veterans admitted for COVID-19 in VHA vs community hospitals. Design, Setting, and Participants: This retrospective cohort study used VHA and Medicare data from March 1, 2020, to December 31, 2021, on hospitalizations for COVID-19 in 121 VHA and 4369 community hospitals in the US among a national cohort of veterans (aged ≥65 years) enrolled in both the VHA and Medicare with VHA care in the year prior to hospitalization for COVID-19 based on the primary diagnosis code. Exposure: Admission to VHA vs community hospitals. Main Outcomes and Measures: The main outcomes were 30-day mortality and 30-day readmission. Inverse probability of treatment weighting was used to balance observable patient characteristics (eg, demographic characteristics, comorbidity, mechanical ventilation on admission, area-level social vulnerability, distance to VHA vs community hospitals, and date of admission) between VHA and community hospitals. Results: The cohort included 64 856 veterans (mean [SD] age, 77.6 [8.0] years; 63 562 men [98.0%]) dually enrolled in the VHA and Medicare who were hospitalized for COVID-19. Most (47 821 [73.7%]) were admitted to community hospitals (36 362 [56.1%] admitted to community hospitals via Medicare, 11 459 [17.7%] admitted to community hospitals reimbursed via VHA's Care in the Community program, and 17 035 [26.3%] admitted to VHA hospitals). Admission to community hospitals was associated with higher unadjusted and risk-adjusted 30-day mortality compared with admission to VHA hospitals (crude mortality, 12 951 of 47 821 [27.1%] vs 3021 of 17 035 [17.7%]; P < .001; risk-adjusted odds ratio, 1.37 [95% CI, 1.21-1.55]; P < .001). Readmission within 30 days was less common after admission to community compared with VHA hospitals (4898 of 38 576 [12.7%] vs 2006 of 14 357 [14.0%]; risk-adjusted hazard ratio, 0.89 [95% CI, 0.86-0.92]; P < .001). Conclusions and Relevance: This study found that most hospitalizations for COVID-19 among VHA enrollees aged 65 years or older were in community hospitals and that veterans experienced higher mortality in community hospitals than in VHA hospitals. The VHA must understand the sources of the mortality difference to plan care for VHA enrollees during future COVID-19 surges and the next pandemic.

Factors affecting the implementation of employee whole health in the veterans health administration: a qualitative evaluation.

BACKGROUND: There is increasing recognition of the need to focus on the health and well-being of healthcare employees given high rates of burnout and turnover. Employee wellness programs are effective at addressing these issues; however, participation in these programs is often a challenge and requires large scale organizational transformation. The Veterans Health Administration (VA) has begun to roll out their own employee wellness program-Employee Whole Health (EWH)-focused on the holistic needs of all employees. This evaluation's goal was to use the Lean Enterprise Transformation (LET) model for organizational transformation to identify key factors-facilitators and barriers-affecting the implementation of VA EWH. METHODS: This cross-sectional qualitative evaluation based on the action research model reflects on the organizational implementation of EWH. Semi-structured 60-minute phone interviews were conducted in February-April 2021 with 27 key informants (e.g., EWH coordinator, wellness/occupational health staff) knowledgeable about EWH implementation across 10 VA medical centers. Operational partner provided a list of potential participants, eligible because of their involvement in EWH implementation at their site. The interview guide was informed by the LET model. Interviews were recorded and professionally transcribed. Constant comparative review with a combination of a priori coding based on the model and emergent thematic analysis was used to identify themes from transcripts. Matrix analysis and rapid turnaround qualitative methods were used to identify cross-site factors to EWH implementation. RESULTS: Eight common factors in the conceptual model were found to facilitate and/or hinder EWH implementation efforts: [1] EWH initiatives, [2] multilevel leadership support, [3] alignment, [4] integration, [5] employee engagement, [6] communication, [7] staffing, and [8] culture. An emergent factor was [9] the impact of the COVID-19 pandemic on EWH implementation. CONCLUSIONS: As VA expands its EWH cultural transformation nationwide, evaluation findings can (a) enable existing programs to address known implementation barriers, and (b) inform new sites to capitalize on known facilitators, anticipate and address barriers, and leverage evaluation recommendations through concerted implementation at the organization, process, and employee levels to jump-start their EWH program implementation.

Excess Mortality at Veterans Health Administration Facilities During the COVID-19 Pandemic.

IMPORTANCE: The COVID-19 pandemic resulted in excess mortality among the general US population and at Veterans Health Administration (VHA) facilities. It is critical to understand the characteristics of facilities that experienced the highest and lowest pandemic-related mortality to inform future mitigation efforts. OBJECTIVE: To identify facility-level excess mortality during the pandemic and to correlate these estimates with facility characteristics and community-wide rates of COVID-19 burden. DESIGN: We used pre-pandemic data to estimate mortality risk prediction models using 5-fold cross-validation and Poisson quasi-likelihood regression. We then estimated excess mortality and observed versus expected (O/E) mortality ratios by the VHA facility from March to December 2020. We examined facility-level characteristics by excess mortality quartile. PARTICIPANTS: Overall, there were 11.4 million VHA enrollees during 2016 and 2020. MAIN MEASURES: Facility-level O/E mortality ratios and excess all-cause mortality. RESULT: VHA-enrolled veterans experienced 52,038 excess deaths from March to December 2020, equating to 16.8% excess mortality. Facility-specific rates ranged from -5.5% to +63.7%. Facilities in the lowest quartile for excess mortality experienced fewer COVID-19 deaths (0.7-1.51, P <0.001) and cases (52.0-63.0, P =0.002) per 1,000 population compared with the highest quartile. The highest quartile facilities had more hospital beds (276.7-187.6, P =0.024) and a higher percent change in the share of visits conducted via telehealth from 2019 to 2020 (183%-133%, P <0.008). CONCLUSIONS: There was a large variation in mortality across VHA facilities during the pandemic, which was only partially explained by the local COVID-19 burden. Our work provides a framework for large health care systems to identify changes in facility-level mortality during a public health emergency.

Primary Care Team Perspectives on the Suitability of Telehealth Modality (Phone vs Video) at the Veterans Health Administration.

INTRODUCTION: Telehealth has the potential to improve access and timeliness of care, enabling primary care teams to deliver hybrid (virtual/in-person) services that will likely extend beyond the COVID-19 pandemic. To optimize its use and sustainability, it is imperative to understand how primary care teams perceive the suitability of telehealth services, including appropriate choice of mode (telephone or video). However, there is limited research on providers' decision-making processes surrounding telehealth use in primary care, including whether to use telephone or video, which this VA-focused study addresses. We examined how primary care (PC) team members determine whether to use telehealth and the mode of delivery, in the care of patients. METHODS: Qualitative case study that included 15 semi-structured interviews with employees who provided or supported telehealth care at primary care clinics at the Veterans Health Administration. We used a team-based rapid analysis approach to identify experiences using telehealth soon after COVID-19's emergence, consisting of the creation of structured summaries of each transcribed interview. The lead author then identified and compiled themes and sub-themes related to the suitability of telehealth in primary care, as well as associated quotes from transcripts. Resulting themes and quotes were reviewed and validated by 2 members of the project team. RESULTS: Primary care team members considered several factors when assessing both the suitability of telehealth for appointments, and mode of use. They were largely guided by patient-related factors including patient preferences, specific health issues, and access to technology. Additional considerations centered on team members' personal preferences and factors that supported the wellbeing of the team, such as the flexibility to work from home (work-life balance) and protection from infection. Generally, participants viewed the option of both telephone and video telehealth modalities as useful tools in the care of patients although a few respondents emphasized its inferiority to in-person care. CONCLUSIONS: Determining the suitability of telehealth services, including appropriate choice of mode is complex. Its suitability is tied to a variety of factors related to multilevel resources, preferences, and timing. When appropriate, telehealth should be considered a useful tool in the care of patients and for employee well-being.

COVID-19 mortality among veterans with serious mental illness in the veterans health administration.

OBJECTIVE: Persons with serious mental illness (SMI: schizophrenia-spectrum disorders, bipolar disorder) experience increased risk of mortality after contracting COVID-19 based on the results of several international evaluations. However, information about COVID-19 mortality risk among patients with SMI in the Veterans Health Administration (VHA) has been limited, precluding identification of protective factors. The current evaluation was conducted to assess COVID-19 mortality risk among VHA patients with SMI and to evaluate potential protective factors in mitigating mortality risk following a positive COVID-19 diagnosis. METHODS: National VHA administrative data was used to identify all patients (N = 52,916) who received a positive COVID-19 test result between March 1, 2020, and September 30, 2020. Mortality risk was assessed by SMI status via bivariate comparisons and multivariate regression analyses. RESULTS: In unadjusted analyses, VHA patients with SMI overall and patients with bipolar disorder in particular did not experience increased mortality risk in the 30 days following a positive COVID test, although patients with schizophrenia had increased risk. Within adjusted analyses, patients with schizophrenia remained at increased mortality risk (OR = 1.38), but at reduced levels relative to previous evaluations in other healthcare settings. CONCLUSIONS: Within VHA, patients with schizophrenia, but not those with bipolar disorder, experience increased mortality risk in the 30 days following a positive COVID-19 test. Large integrated healthcare settings such as VHA may offer services which may protect against COVID-19 mortality for vulnerable groups such as persons with SMI. Additional work is needed to identify practices which may reduce the risk of COVID-19 mortality among persons with SMI.

Changes in Burnout and Moral Distress Among Veterans Health Administration (VA) Physicians Before and During the COVID-19 Pandemic.

BACKGROUND: We investigated the impacts of workload, resources, organizational satisfaction, and psychological safety on changes in physician burnout and moral distress among physicians during the early pandemic. METHODS: We obtained national administrative and survey data on burnout, moral distress, organizational satisfaction, psychological safety, COVID-19 burden, and state-level restrictions for 11,877-14,246 Veterans Health Administration (VA) physicians from 2019 and 2020. We regressed the changes in burnout and moral distress on the changes in reasonable workload, appropriate job resources, organizational satisfaction, and psychological safety, controlling for COVID-19 burden and restrictions, and individual and medical center characteristics. RESULTS: Burnout and moral distress were not related to COVID-19 cases or restrictions but were reduced by improvements in workload, organizational satisfaction, and psychological safety. CONCLUSIONS: Health systems should be conscious of factors that can harm or improve physician well-being, especially in the context of external stressors.

Delays in Care During the COVID-19 Pandemic in the Veterans Health Administration.

OBJECTIVES: The purpose of this study was to review patient safety reports in the Veterans Health Administration (VHA) related to delays during an 11-month period that included months of the COVID-19 pandemic. DESIGN: A retrospective descriptive analysis of COVID-19 patient safety reports related to delays that were submitted in the Joint Patient Safety Event Reporting System database to the VHA National Center of Patient Safety from January 01, 2020 to November 15, 2020 was conducted. There were 897 COVID-19 patient safety events related to delays; 200 cases were randomly selected for analysis, with 148 meeting inclusion criteria. RESULTS: The results showed delays in laboratory results, level of care, treatment and interventional procedures, specific aspects of care, radiology treatment, and diagnosis. Causes for delays included poor communication between staff, problems in getting laboratory results, confusion over policy, and misunderstanding of COVID-19-specific rules. CONCLUSIONS: Healthcare delays can be reduced during a pandemic by proactively standardizing medical processes/procedures when testing for infection, improving staff to staff communication teaching the SBAR (situation, background, assessment, and recommendations) communication model, and using simulation to identify latent safety issues and educating medical personnel on new protocols related to the pandemic. Simulation can be used to test new protocols developed during the pandemic.

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.

VA's implementation of universal screening and evaluation for the suicide risk identification program in November 2020 -Implications for Veterans with prior mental health needs.

IMPORTANCE: United States Veterans are at higher risk for suicide than non-Veterans. Veterans in rural areas are at higher risk than their urban counterparts. The coronavirus pandemic intensified risk factors for suicide, especially in rural areas. OBJECTIVE: To examine associations between Veterans Health Administration's (VA's) universal suicide risk screening, implemented November 2020, and likelihood of Veterans being screened, and receiving follow-up evaluations, as well as post-screening suicidal behavior among patients who used VA mental health services in 2019. METHODS: VA's Suicide Risk Identification Strategy (Risk ID), implemented October 2018, is a national, standardized process for suicide risk screening and evaluation. In November 2020, VA expanded Risk ID, requiring annual universal suicide screening. As such, we are evaluating outcomes of interest before and after the start of the policy among Veterans who had ≥1 VA mental health care visit in 2019 (n = 1,654,180; rural n = 485,592, urban n = 1,168,588). Regression-adjusted outcomes were compared 6 months pre-universal screening and 6, 12 and 13 months post-universal screening implementation. MEASURES: Item-9 on the Patient Health Questionnaire (I-9, VA's historic suicide screener), Columbia- Suicide Severity Risk Scale (C-SSRS) Screener, VA's Comprehensive Suicide Risk Evaluation (CSRE), and Suicide Behavior and Overdose Report (SBOR). RESULTS: 12 months post-universal screening implementation, 1.3 million Veterans (80% of the study cohort) were screened or evaluated for suicide risk, with 91% the sub-cohort who had at least one mental health visit in the 12 months post-universal screening implementation period were screened or evaluated. At least 20% of the study cohort was screened outside of mental health care settings. Among Veterans with positive screens, 80% received follow-up CSREs. Covariate-adjusted models indicated that an additional 89,160 Veterans were screened per month via the C-SSRS and an additional 30,106 Veterans/month screened via either C-SSRS or I-9 post-universal screening implementation. Compared to their urban counterparts, 7,720 additional rural Veterans/month were screened via the C-SSRS and 9,226 additional rural Veterans/month were screened via either the C-SSRS or I-9. CONCLUSION: VA's universal screening requirement via VA's Risk ID program increased screening for suicide risk among Veterans with mental health care needs. A universal approach to screening may be particularly advantageous for rural Veterans, who are typically at higher risk for suicide but have fewer interactions with the health care system, particularly within specialty care settings, due to higher barriers to accessing care. Insights from this program offer valuable insights for health systems nationwide.

Inclusion of Race and Ethnicity With Neighborhood Socioeconomic Deprivation When Assessing COVID-19 Hospitalization Risk Among California Veterans Health Administration Users.

Importance: Despite complexities of racial and ethnic residential segregation (hereinafter referred to as segregation) and neighborhood socioeconomic deprivation, public health studies, including those on COVID-19 racial and ethnic disparities, often rely on composite neighborhood indices that do not account for residential segregation. Objective: To examine the associations by race and ethnicity among California's Healthy Places Index (HPI), Black and Hispanic segregation, Social Vulnerability Index (SVI), and COVID-19-related hospitalization. Design, Setting, and Participants: This cohort study included veterans with positive test results for COVID-19 living in California who used Veterans Health Administration services between March 1, 2020, and October 31, 2021. Main Outcomes and Measures: Rates of COVID-19-related hospitalization among veterans with COVID-19. Results: The sample available for analysis included 19 495 veterans with COVID-19 (mean [SD] age, 57.21 [17.68] years), of whom 91.0% were men, 27.7% were Hispanic, 16.1% were non-Hispanic Black, and 45.0% were non-Hispanic White. For Black veterans, living in lower-HPI (ie, less healthy) neighborhoods was associated with higher rates of hospitalization (odds ratio [OR], 1.07 [95% CI, 1.03-1.12]), even after accounting for Black segregation (OR, 1.06 [95% CI, 1.02-1.11]). Among Hispanic veterans, living in lower-HPI neighborhoods was not associated with hospitalization with (OR, 1.04 [95% CI, 0.99-1.09]) and without (OR, 1.03 [95% CI, 1.00-1.08]) Hispanic segregation adjustment. For non-Hispanic White veterans, lower HPI was associated with more frequent hospitalization (OR, 1.03 [95% CI, 1.00-1.06]). The HPI was no longer associated with hospitalization after accounting for Black (OR, 1.02 [95% CI, 0.99-1.05]) or Hispanic (OR, 0.98 [95% CI, 0.95-1.02]) segregation. Hospitalization was higher for White (OR, 4.42 [95% CI, 1.62-12.08]) and Hispanic (OR, 2.90 [95% CI, 1.02-8.23]) veterans living in neighborhoods with greater Black segregation and for White veterans in more Hispanic-segregated neighborhoods (OR, 2.81 [95% CI, 1.96-4.03]), adjusting for HPI. Living in higher SVI (ie, more vulnerable) neighborhoods was associated with greater hospitalization for Black (OR, 1.06 [95% CI, 1.02-1.10]) and non-Hispanic White (OR, 1.04 [95% CI, 1.01-1.06]) veterans. Conclusions and Relevance: In this cohort study of US veterans with COVID-19, HPI captured neighborhood-level risk for COVID-19-related hospitalization for Black, Hispanic, and White veterans comparably with SVI. These findings have implications for the use of HPI and other composite neighborhood deprivation indices that do not explicitly account for segregation. Understanding associations between place and health requires ensuring composite measures accurately account for multiple aspects of neighborhood deprivation and, importantly, variation by race and ethnicity.

Developing and Implementing Predictive Models in a Learning Healthcare System: Traditional and Artificial Intelligence Approaches in the Veterans Health Administration.

Predicting clinical risk is an important part of healthcare and can inform decisions about treatments, preventive interventions, and provision of extra services. The field of predictive models has been revolutionized over the past two decades by electronic health record data; the ability to link such data with other demographic, socioeconomic, and geographic information; the availability of high-capacity computing; and new machine learning and artificial intelligence methods for extracting insights from complex datasets. These advances have produced a new generation of computerized predictive models, but debate continues about their development, reporting, validation, evaluation, and implementation. In this review we reflect on more than 10 years of experience at the Veterans Health Administration, the largest integrated healthcare system in the United States, in developing, testing, and implementing such models at scale. We report lessons from the implementation of national risk prediction models and suggest an agenda for research.

The impact of COVID-19 on trends in alcohol use disorder treatment in Veterans Health Administration.

BACKGROUND AND AIMS: The COVID-19 pandemic disrupted health-care provision in the United States and prompted increases in telehealth-delivery of care. This study measured alcohol use disorder (AUD) treatment trends across visit modalities before and during COVID-19. DESIGN, SETTING, PARTICIPANTS AND MEASUREMENTS: We conducted a national, retrospective cohort study with interrupted time-series models to estimate the impact of COVID-19 on AUD treatment in the Veterans Health Administration (VHA) in the United States during pre-COVID-19 (March 2019 to February 2020) and COVID-19 (March 2020 to February 2021) periods. We analyzed monthly trends in telephone, video and in-person visits for AUD treatment and compared patient and treatment characteristics of patients receiving AUD treatment between the pre-COVID-19 and COVID-19 periods. AUD was defined using International Classification of Diseases, 10th revision (ICD-10) codes for alcohol abuse (F10.1) and alcohol dependence (F10.2), which have previously been used to study AUD in VHA. FINDINGS: The predicted percentage of VHA patients with an AUD diagnosis receiving any AUD treatment at the beginning of the pre-COVID period was 13.8% (n = 49 494). The predicted percentage decreased by 4.3% (P = 0.001) immediately at the start of the COVID-19 period due to a decline in AUD psychotherapy. Despite an increase of 0.3% per month (P = 0.026) following the start of COVID-19, the predicted percentage of VHA patients with an AUD diagnosis receiving any AUD treatment at the end of the study period remained below the pre-COVID-19 period. In February 2021, AUD psychotherapy visits were primarily delivered by video (50%, 58 748), followed by in-person (36.6%, 43 251) and telephone (13.8%, 16 299), while AUD pharmacotherapy visits were delivered by telephone (38.9%, 3623) followed by in-person (34.3%, 3193) and video (26.8%, 2498) modalities. Characteristics of VHA patients receiving AUD treatment were largely similar between pre-COVID-19 and COVID-19 periods. CONCLUSIONS: Despite increased telehealth use, the percentage of United States Veterans Health Administration patients with an alcohol use disorder (AUD) diagnosis receiving AUD treatment declined during COVID-19 (March 2020 to February 2021) mainly due to a decrease in psychotherapy.

Helping the Helpers: Adaptation and Evaluation of Stress First Aid for Healthcare Workers in the Veterans Health Administration During the COVID-19 Pandemic.

BACKGROUND: Early interventions are needed to support the behavioral health of healthcare staff in the context of the COVID-19 pandemic. Stress First Aid (SFA) is a self-care and peer support model for reducing burnout and stress that is designed for use in high-stress occupations. METHODS: We conducted a mixed-methods evaluation of an SFA program in the Veterans Health Administration (VHA). This brief, multi-session, didactic program was adapted for hospital workgroups. Program attendees completed a survey assessing implementation outcomes, burnout, stress, mood, and SFA skills at the beginning (N = 246) and end (n = 94) of the SFA program and a subgroup (n = 11) completed qualitative feedback interviews. FINDINGS: Program acceptability, appropriateness, and feasibility were rated highly. From pre- to post-SFA, the impact of the pandemic on stress and anxiety, as well as proficiency in supporting peers increased. Qualitative findings suggest the program provided a shared language to discuss stress, normalized stress reactions, met a need for stress management tools, and helped staff feel valued, empowered, connected with each other. Staff reported being more aware of their stress, but SFA was insufficient to address many of the systemic sources of burnout and stress. CONCLUSIONS AND APPLICATIONS TO PRACTICE: While the SFA program was well received, the impact of brief programs is likely to be modest when implemented in the middle of an ongoing pandemic and when burnout arises from chiefly from systemic sources. Lessons learned during the program implementation that may guide future efforts are discussed.

Association of Adequacy of Broadband Internet Service With Access to Primary Care in the Veterans Health Administration Before and During the COVID-19 Pandemic.

Importance: Although telemedicine expanded rapidly during the COVID-19 pandemic and is widely available for primary care, required broadband internet speeds may limit access. Objective: To identify disparities in primary care access in the Veterans Health Administration based on the association between broadband availability and primary care visit modality. Design, Setting, and Participants: This cohort study used administrative data on veterans enrolled in Veterans Health Administration primary care to identify visits at 937 primary care clinics providing telemedicine and in-person clinical visits before the COVID-19 pandemic (October 1, 2016, to February 28, 2020) and after the onset of the pandemic (March 1, 2020, to June 30, 2021). Exposures: Federal Communications Commission-reported broadband availability was classified as inadequate (download speed, ≤25 MB/s; upload speed, ≤3 MB/s), adequate (download speed, ≥25 <100 MB/s; upload speed, ≥5 and <100 MB/s), or optimal (download and upload speeds, ≥100 MB/s) based on data reported at the census block by internet providers and was spatially merged to the latitude and longitude of each veteran's home address using US Census Bureau shapefiles. Main Outcomes and Measures: All visits were coded as in-person or virtual (ie, telephone or video) and counted for each patient, quarterly by visit modality. Poisson models with Huber-White robust errors clustered at the census block estimated the association between a patient's broadband availability category and the quarterly primary care visit count by visit type, adjusted for covariates. Results: In primary care, 6 995 545 veterans (91.8% men; mean [SD] age, 63.9 [17.2] years; 71.9% White; and 63.0% residing in an urban area) were seen. Adjusted regression analyses estimated the change after the onset of the pandemic vs before the pandemic in patients' quarterly primary care visit count; patients living in census blocks with optimal vs inadequate broadband had increased video visit use (incidence rate ratio [IRR], 1.33; 95% CI, 1.21-1.46; P < .001) and decreased in-person visits (IRR, 0.84; 95% CI, 0.84-0.84; P < .001). The increase in the rate of video visits before vs after the onset of the pandemic was greatest among patients in the lowest Area Deprivation Index category (indicating least social disadvantage) with availability of optimal vs inadequate broadband (IRR, 1.73; 95% CI, 1.42-2.09). Conclusions and Relevance: This cohort study found that patients with optimal vs inadequate broadband availability had more video-based primary care visits and fewer in-person primary care visits after the onset of the COVID-19 pandemic, suggesting that broadband availability was associated with video-based telemedicine use. Future work should assess the association of telemedicine access with clinical outcomes.

Association of Race and Ethnicity With Prescription of SGLT2 Inhibitors and GLP1 Receptor Agonists Among Patients With Type 2 Diabetes in the Veterans Health Administration System.

Importance: Novel therapies for type 2 diabetes can reduce the risk of cardiovascular disease and chronic kidney disease progression. The equitability of these agents' prescription across racial and ethnic groups has not been well-evaluated. Objective: To investigate differences in the prescription of sodium-glucose cotransporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1 RA) among adult patients with type 2 diabetes by racial and ethnic groups. Design, Setting, and Participants: Cross-sectional analysis of data from the US Veterans Health Administration's Corporate Data Warehouse. The sample included adult patients with type 2 diabetes and at least 2 primary care clinic visits from January 1, 2019, to December 31, 2020. Exposures: Self-identified race and self-identified ethnicity. Main Outcomes and Measures: The primary outcomes were prevalent SGLT2i or GLP-1 RA prescription, defined as any active prescription during the study period. Results: Among 1 197 914 patients (mean age, 68 years; 96% men; 1% American Indian or Alaska Native, 2% Asian, Native Hawaiian, or Other Pacific Islander, 20% Black or African American, 71% White, and 7% of Hispanic or Latino ethnicity), 10.7% and 7.7% were prescribed an SGLT2i or a GLP-1 RA, respectively. Prescription rates for SGLT2i and GLP-1 RA, respectively, were 11% and 8.4% among American Indian or Alaska Native patients; 11.8% and 8% among Asian, Native Hawaiian, or Other Pacific Islander patients; 8.8% and 6.1% among Black or African American patients; and 11.3% and 8.2% among White patients, respectively. Prescription rates for SGLT2i and GLP-1 RA, respectively, were 11% and 7.1% among Hispanic or Latino patients and 10.7% and 7.8% among non-Hispanic or Latino patients. After accounting for patient- and system-level factors, all racial groups had significantly lower odds of SGLT2i and GLP-1 RA prescription compared with White patients. Black patients had the lowest odds of prescription compared with White patients (adjusted odds ratio, 0.72 [95% CI, 0.71-0.74] for SGLT2i and 0.64 [95% CI, 0.63-0.66] for GLP-1 RA). Patients of Hispanic or Latino ethnicity had significantly lower odds of prescription (0.90 [95% CI, 0.88-0.93] for SGLT2i and 0.88 [95% CI, 0.85-0.91] for GLP-1 RA) compared with non-Hispanic or Latino patients. Conclusions and Relevance: Among patients with type 2 diabetes in the Veterans Health Administration system during 2019 and 2020, prescription rates of SGLT2i and GLP-1 RA medications were low, and individuals of several different racial groups and those of Hispanic ethnicity had statistically significantly lower odds of receiving prescriptions for these medications compared with individuals of White race and non-Hispanic ethnicity. Further research is needed to understand the mechanisms underlying these differences in rates of prescribing and the potential relationship with differences in clinical outcomes.