Physicians and Specialties in the Veterans Health Administration's Community Care Network.

This cross-sectional study of data from the US Veterans Health Administration examines the availability of services provided through community care networks by specialty and clinical characteristics.

Injuries From Legal Interventions Involving Conducted Energy Devices.

This cross-sectional study evaluates emergency department visits for physical injuries from use of conducted energy devices by police departments.

Clinical Outreach Training and Supportive Supervision Quality-of-Care Analysis: Impact of Readiness Factors on Health Worker Competencies in Malaria Case Management in Cameroon, Mali, and Niger.

Improving the quality of malaria clinical case management in health facilities is key to improving health outcomes in patients. The U.S. President's Malaria Initiative Impact Malaria Project has supported implementation of the Outreach Training and Supportive Supervision (OTSS) approach in 11 African countries to improve the quality of malaria care in health facilities through the collection and analysis of observation-based data on health facility readiness and health provider competency in malaria case management. We conducted a secondary analysis of longitudinal data collected during routine supervision in Cameroon (April 2021-March 2022), Mali (October 2020-December 2021), and Niger (November 2020-September 2021) using digitized checklists to assess how service readiness affects health worker competencies in managing patients with fever correctly and providing those with confirmed uncomplicated malaria cases with appropriate treatment and referral. Linear or logistic regression analyses were conducted to assess the effect of facility readiness and its components on observed health worker competencies. All countries demonstrated significant associations between health facility readiness and malaria case management competencies. Data from three rounds of OTSS visits in Cameroon, Mali, and Niger showed a statistically significant positive association between greater facility readiness scores (including the availability of commodities, materials, and trained staff) and health worker competency in case management. These findings provide evidence that health worker performance is likely affected by the tools and training available to them. These results reinforce the need for necessary tools and properly trained staff if high-quality malaria case management services are to be delivered at health facilities.

Engagement with Traditional Healers for Early Detection of Plague in Uganda.

In rural Uganda, many people who are ill consult traditional healers prior to visiting the formal healthcare system. Traditional healers provide supportive care for common illnesses, but their care may delay diagnosis and management of illnesses that can increase morbidity and mortality, hinder early detection of epidemic-prone diseases, and increase occupational risk to traditional healers. We conducted open-ended, semi-structured interviews with a convenience sample of 11 traditional healers in the plague-endemic West Nile region of northwestern Uganda to assess their knowledge, practices, and attitudes regarding plague and the local healthcare system. Most were generally knowledgeable about plague transmission and its clinical presentation and expressed willingness to refer patients to the formal healthcare system. We initiated a public health outreach program to further improve engagement between traditional healers and local health centers to foster trust in the formal healthcare system and improve early identification and referral of patients with plaguelike symptoms, which can reflect numerous other infectious and noninfectious conditions. During 2010-2019, 65 traditional healers were involved in the outreach program; 52 traditional healers referred 788 patients to area health centers. The diagnosis was available for 775 patients; malaria (37%) and respiratory tract infections (23%) were the most common diagnoses. One patient had confirmed bubonic plague. Outreach to improve communication and trust between traditional healers and local healthcare settings may result in improved early case detection and intervention not only for plague but also for other serious conditions.

Trends in U.S. self-reported health and self-care behaviors during the COVID-19 pandemic.

IMPORTANCE: The COVID-19 pandemic represents a unique stressor in Americans' daily lives and access to health services. However, it remains unclear how the pandemic impacted perceived health status and engagement in health-related behaviors. OBJECTIVE: To assess changes in self-reported health outcomes during the COVID-19 pandemic, and to explore trends in health-related behaviors that may underlie the observed health changes. DESIGN: Interrupted time series stratified by age, gender, race/ethnicity, educational attainment, household income, and employment status. SETTING: United States. PARTICIPANTS: All adult respondents to the 2016-2020 Behavioral Risk Factor Surveillance System (N = 2,146,384). EXPOSURE: Survey completion following the U.S. public health emergency declaration (March-December 2020). January 2019 to February 2020 served as our reference period. MAIN OUTCOMES AND MEASURES: Self-reported health outcomes included the number of days per month that respondents spent in poor mental health, physical health, or when poor health prevented their usual activities of daily living. Self-reported health behaviors included the number of hours slept per day, number of days in the past month where alcohol was consumed, participation in any exercise, and current smoking status. RESULTS: The national rate of days spent in poor physical health decreased overall (-1.00 days, 95% CI: -1.10 to -0.90) and for all analyzed subgroups. The rate of poor mental health days or days when poor health prevented usual activities did not change overall but exhibited substantial heterogeneity by subgroup. We also observed overall increases in mean sleep hours per day (+0.09, 95% CI 0.05 to 0.13), the percentage of adults who report any exercise activity (+3.28%, 95% CI 2.48 to 4.09), increased alcohol consumption days (0.27, 95% CI 0.18 to 0.37), and decreased smoking prevalence (-1.11%, 95% CI -1.39 to -0.83). CONCLUSIONS AND RELEVANCE: The COVID-19 pandemic had deleterious but heterogeneous effects on mental health, days when poor health prevented usual activities, and alcohol consumption. In contrast, the pandemic's onset was associated with improvements in physical health, mean hours of sleep per day, exercise participation, and smoking status. These findings highlight the need for targeted outreach and interventions to improve mental health in individuals who may be disproportionately affected by the pandemic.

Impact of notification policy on patient-before-clinician review of immediately released test results.

The 21st Century Cures Act mandates immediate availability of test results upon request. The Cures Act does not require that patients be informed of results, but many organizations send notifications when results become available. Our medical center implemented 2 sequential policies: immediate notifications for all results, and notifications only to patients who opt in. We used over 2 years of data from Vanderbilt University Medical Center to measure the effect of these policies on rates of patient-before-clinician result review and patient-initiated messaging using interrupted time series analysis. When releasing test results with immediate notification, the proportion of patient-before-clinician review increased 4-fold and the proportion of patients who sent messages rose 3%. After transition to opt-in notifications, patient-before-clinician review decreased 2.4% and patient-initiated messaging decreased 0.4%. Replacing automated notifications with an opt-in policy provides patients flexibility to indicate their preferences but may not substantially alleviate clinicians' messaging workload.

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.

Using antenatal care as a platform for malaria surveillance data collection: study protocol.

BACKGROUND: While many malaria-endemic countries have health management information systems that can measure and report malaria trends in a timely manner, these routine systems have limitations. Periodic community cross-sectional household surveys are used to estimate malaria prevalence and intervention coverage but lack geographic granularity and are resource intensive. Incorporating malaria testing for all women at their first antenatal care (ANC) visit (i.e., ANC1) could provide a more timely and granular source of data for monitoring trends in malaria burden and intervention coverage. This article describes a protocol designed to assess if ANC-based surveillance could be a pragmatic tool to monitor malaria. METHODS: This is an observational, cross-sectional study conducted in Benin, Burkina Faso, Mozambique, Nigeria, Tanzania, and Zambia. Pregnant women attending ANC1 in selected health facilities will be tested for malaria infection by rapid diagnostic test and administered a brief questionnaire to capture key indicators of malaria control intervention coverage and care-seeking behaviour. In each location, contemporaneous cross-sectional household surveys will be leveraged to assess correlations between estimates obtained using each method, and the use of ANC data as a tool to track trends in malaria burden and intervention coverage will be validated. RESULTS: This study will assess malaria prevalence at ANC1 aggregated at health facility and district levels, and by gravidity relative to current pregnancy (i.e., gravida 1, gravida 2, and gravida 3 +). ANC1 malaria prevalence will be presented as monthly trends. Additionally, correlation between ANC1 and household survey-derived estimates of malaria prevalence, bed net ownership and use, and care-seeking will be assessed. CONCLUSION: ANC1-based surveillance has the potential to provide a cost-effective, localized measure of malaria prevalence that is representative of the general population and useful for tracking monthly changes in parasite prevalence, as well as providing population-representative estimates of intervention coverage and care-seeking behavior. This study will evaluate the representativeness of these measures and collect information on operational feasibility, usefulness for programmatic decision-making, and potential for scale-up of malaria ANC1 surveillance.

Plan Selection, Enrollee Risk, and Health Spending on the Patient Protection and Affordable Care Act Individual Marketplaces, 2019.

Importance: The Patient Protection and Affordable Care Act (ACA) individual marketplaces are a source of insurance for millions of residents in the US. However, the association between enrollee risk, health spending, and metal tier selection remains unclear. Objectives: To describe individual marketplace enrollees' metal tier selections by risk score and assess enrollees' health spending by metal tier, risk score, and spending type. Design, Setting, and Participants: This retrospective, cross-sectional study analyzed claims data from the Wakely Consulting Group ACA database, a deidentified claims database built on data voluntarily submitted by insurers. Enrollees with continuous, full-year enrollment in on-exchange or off-exchange ACA-qualified health plans during the 2019 contract year were included. Data analysis was conducted from March 2021 to January 2023. Main Outcomes and Measures: Enrollment totals, total spending, and out-of-pocket cost were calculated, stratified by metal tier and the Department of Health and Human Services (HHS) Hierarchical Condition Category (HCC) risk score for 2019. Results: Enrollment and claims data were obtained for 1 317 707 enrollees (53.5% female; mean [SD] age, 46.35 [13.43] years) across all census areas, age groups, and sexes. Of these, 34.6% were on plans with cost-sharing reductions (CSRs), 75.5% did not have an assigned HCC, and 84.0% submitted at least 1 claim. Compared with enrollees in bronze plans (17.2%), enrollees were more likely to be classified in the top HHS-HCC risk quartile if they selected platinum (42.0%), gold (34.4%), or silver (29.7%) plans. The highest share of enrollees with $0 total spending was noted with the catastrophic (26.4%) and bronze (22.7%) plans, while gold plans had the lowest share (8.1%). Median total spending was lower among bronze plan enrollees ($593; IQR, $28-$2100) vs platinum ($4111; IQR, $992-$15 821) or gold ($2675; IQR, $728-$9070). Within the top risk score decile, CSR enrollees had less average total spending than any other metal tier by more than 10%. Conclusions and Relevance: In this cross-sectional study of the ACA individual marketplace, enrollees who selected plans with higher actuarial value also had greater mean HHS-HCC risk scores and health spending. The findings suggest these differences may be associated with variation in benefit generosity by metal tier, enrollee's perceptions of future health needs, or other barriers to care access.

Validation of the Clinicians' Cultural Sensitivity Survey for Use in Pediatric Primary Care Settings.

Incorporating cultural sensitivity into healthcare settings is important to deliver high-quality and equitable care, particularly for marginalized communities who are non-White, non-English speaking, or immigrants. The Clinicians' Cultural Sensitivity Survey (CCSS) was developed as a patient-reported survey assessing clinicians' recognition of cultural factors affecting care quality for older Latino patients; however, this instrument has not been adapted for use in pediatric primary care. Our objective was to examine the validity and reliability of a modified CCSS that was adapted for use with parents of pediatric patients. A convenience sampling approach was used to identify eligible parents during well-child visits at an urban pediatric primary care clinic. Parents were administered the CCSS via electronic tablet in a private location. We first conducted exploratory factor analyses (EFAs) to explore the dimensionality of survey responses in the adapted CCSS, and then conducted a series of confirmatory factor analyses (CFAs) using maximum likelihood estimation based on the results of the EFAs. Exploratory and confirmatory factor analyses (N = 212 parent surveys) supported a three-factor structure assessing racial discrimination ([Formula: see text]=0.96), culturally-affirming practices ([Formula: see text]=0.86), and causal attribution of health problems ([Formula: see text]=0.85). In CFAs, the three-factor model also outperformed other potential factor structures in terms of fit statistics including scaled root mean square error approximation (0.098), Tucker-Lewis Index (0.936), Comparative Fit Index (0.950), and demonstrated adequate fit according to the standardized root mean square residual (0.061). Our findings support the internal consistency, reliability, and construct validity of the adapted CCSS for use in a pediatric population.

Changes in Health Care Access by Race, Income, and Medicaid Expansion During the COVID-19 Pandemic.

BACKGROUND: The intersecting crises of the COVID-19 pandemic, job losses, and concomitant loss of employer-sponsored health insurance may have disproportionately affected health care access within minorized and lower-socioeconomic status communities. OBJECTIVE: To describe changes in access to care during the COVID-19 pandemic, stratified by race/ethnicity, household income, and state Medicaid expansion status. RESEARCH DESIGN: We used interrupted time series and difference-in-differences regression models, controlling for respondent characteristics and preexisting trends. SUBJECTS: Data were extracted for all adults aged 18-64 surveyed in the 2015-2020 Behavioral Risk Factor Surveillance System (N=1,731,699) from all 50 states and the District of Columbia. MEASURES: Our outcomes included indicators for whether respondents had any health insurance coverage or avoided seeking care because of cost within the prior year. The primary exposure was the onset of the COVID-19 pandemic in the United States in March 2020. RESULTS: The pandemic was associated with a 1.2 percentage point (pp) decline in uninsurance for Medicaid expansion states (95% CI, -1.8, -0.6); these reductions were concentrated among respondents who were Black, multiracial, or low income. The rates of uninsurance were generally stable in nonexpansion states. The rates of avoided care because of cost fell by 3.5 pp in Medicaid expansion states (95% CI, -3.9, -3.1), and by 3.6 pp (95% CI, 4.3-2.9) in nonexpansion states. These declines were concentrated among respondents who were Hispanic, Other Race, or low income. CONCLUSIONS: Our findings reinforce the value of Medicaid expansion as one tool to improve access to health insurance and care for marginalized and vulnerable populations.

Racial and ethnic disparities in excess mortality among U.S. veterans during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic disproportionately affected racial and ethnic minorities among the general population in the United States; however, little is known regarding its impact on U.S. military Veterans. In this study, our objectives were to identify the extent to which Veterans experienced increased all-cause mortality during the COVID-19 pandemic, stratified by race and ethnicity. DATA SOURCES: Administrative data from the Veterans Health Administration's Corporate Data Warehouse. STUDY DESIGN: We use pre-pandemic data to estimate mortality risk models using five-fold cross-validation and quasi-Poisson regression. Models were stratified by a combined race-ethnicity variable and included controls for major comorbidities, demographic characteristics, and county fixed effects. DATA COLLECTION: We queried data for all Veterans residing in the 50 states plus Washington D.C. during 2016-2020. Veterans were excluded from analyses if they were missing county of residence or race-ethnicity data. Data were then aggregated to the county-year level and stratified by race-ethnicity. PRINCIPAL FINDINGS: Overall, Veterans' mortality rates were 16% above normal during March-December 2020 which equates to 42,348 excess deaths. However, there was substantial variation by racial and ethnic group. Non-Hispanic White Veterans experienced the smallest relative increase in mortality (17%, 95% CI 11%-24%), while Native American Veterans had the highest increase (40%, 95% CI 17%-73%). Black Veterans (32%, 95% CI 27%-39%) and Hispanic Veterans (26%, 95% CI 17%-36%) had somewhat lower excess mortality, although these changes were significantly higher compared to White Veterans. Disparities were smaller than in the general population. CONCLUSIONS: Minoritized Veterans experienced higher rates excess of mortality during the COVID-19 pandemic compared to White Veterans, though with smaller differences than the general population. This is likely due in part to the long-standing history of structural racism in the United States that has negatively affected the health of minoritized communities via several pathways including health care access, economic, and occupational inequities.

Geographic Variation in Appointment Wait Times for US Military Veterans.

Importance: Timely access to medical care is an important determinant of health and well-being. The US Congress passed the Veterans Access, Choice, and Accountability Act in 2014 and the VA MISSION (Maintaining Systems and Strengthening Integrated Outside Networks) Act in 2018, both of which allow veterans to access care from community-based clinicians, but geographic variation in appointment wait times after the passage of these acts have not been studied. Objective: To describe geographic variation in wait times experienced by veterans for primary care, mental health, and other specialties. Design, Setting, and Participants: This is a cross-sectional study using data from the Veterans Health Administration (VHA) Corporate Data Warehouse. Participants include veterans who sought medical care from January 1, 2018, to June 30, 2021. Data analysis was performed from February to June 2022. Exposures: Referral to either VHA or community-based clinicians. Main Outcomes and Measures: Total appointment wait times (in days) for 3 care categories: primary care, mental health, and all other specialties. VHA medical centers are organized into regions called Veterans Integrated Services Networks (VISNs); wait times were aggregated to the VISN level. Results: The final sample included 22 632 918 million appointments for 4 846 892 unique veterans (77.3% male; mean [SD] age, 61.6 [15.5] years). Among non-VHA appointments, mean (SD) VISN-level appointment wait times were 38.9 (8.2) days for primary care, 43.9 (9.0) days for mental health, and 41.9 (5.9) days for all other specialties. Among VHA appointments, mean (SD) VISN-level appointment wait times were 29.0 (5.5) days for primary care, 33.6 (4.6) days for mental health, and 35.4 (2.7) days for all other specialties. There was substantial geographic variation in appointment wait times. Among non-VHA appointments, VISN-level appointment wait times ranged from 25.4 to 52.4 days for primary care, from 29.3 to 65.7 days for mental health, and from 34.7 to 54.8 days for all other specialties. Among VHA appointments, wait times ranged from 22.4 to 43.4 days for primary care, from 24.7 to 42.0 days for mental health, and from 30.3 to 41.9 days for all other specialties. There was a correlation between wait times across care categories and setting (VHA vs community care). Conclusions and Relevance: This cross-sectional study found substantial variation in wait times across care type and geography, and VHA wait times in a majority of VISNs were lower than those for community-based clinicians, even after controlling for differences in specialty mix. These findings suggest that liberalized access to community care under the Veterans Access, Choice, and Accountability Act and the VA MISSION Act may not result in lower wait times within these regions.

Local Supply Of Postdischarge Care Options Tied To Hospital Readmission Rates.

The extent to which patients' risk for readmission after a hospitalization is influenced by local availability of postdischarge care options is not currently known. We used national, hospital-level data to assess whether the supply of postdischarge care options in hospitals' catchment areas was associated with readmission rates for Medicare patients after hospitalizations for acute myocardial infarction, heart failure, or pneumonia. Overall, readmission rates were negatively associated with per capita supply of primary care physicians (-0.16 percentage points per standard deviation) and licensed nursing home beds (-0.09 percentage points per standard deviation). In contrast, readmission rates were positively associated with per capita supply of nurse practitioners (0.09 percentage points per standard deviation). Our results suggest potential modifications to the Hospital Readmissions Reduction Program to account for local health system characteristics when assigning penalties to hospitals.

Improving Access to High-Value, High-Cost Medicines: The Use of Subscription Models to Treat Hepatitis C Using Direct-Acting Antivirals in the United States.

State payers may face financial incentives to restrict use of high-cost medications. Yet, restrictions on access to high-value medications may have deleterious effects on population health. Direct-acting antivirals (DAAs), available since 2013, can cure chronic infection with hepatitis C virus (HCV). With prices upward of $90,000 for a treatment course, states have struggled to ensure access to DAAs for Medicaid beneficiaries and the incarcerated, populations with a disproportionate share of HCV. Advance purchase commitments (APCs), wherein a payer commits to purchase a certain quantity of medications at lower prices, offer payers incentives to increase access to high-value medications while also offering companies guaranteed revenue. This article discusses the use of subscription models, a type of APC, to support increased access to high-value DAAs for treating HCV. First, the authors provide background information about HCV, its treatment, and state financing of prescription medications. They then review the implementation of HCV subscription models in two states, Louisiana and Washington, and the early evidence of their impact. The article discusses challenges to evaluating state-sponsored subscription models, and it concludes by discussing implications of subscription models that target DAAs and other high-value, high-cost medicines.

A novel dataset of predictors of mortality for older Veterans living with type II diabetes.

The dataset summarized in this article includes a nationwide prevalence sample of U.S. military Veterans who were aged 65 years or older, dually enrolled in the Veterans Health Administration and traditional Medicare and had a previous diagnosis of diabetes (diabetes mellitus) as of December 2005 (N = 275,190) [1]. Our data were originally used to develop and validate prognostic indices of 5- and 10-year mortality among older Veterans with diabetes. We include various potential predictors including demographics (e.g., sex, age, marital status, and VA priority group), healthcare utilization (e.g., # of outpatient visits, # days of inpatient stays), medication history, and major comorbidities. This novel dataset provides researchers with an opportunity to study the associations between a large variety of individual-level risk factors and longevity for patients living with diabetes.

Medicaid expansion and drug overdose mortality during the COVID-19 pandemic in the United States.

BACKGROUND: The COVID-19 pandemic caused disruptions in the delivery of health services, which may have adversely affected access to substance use disorder (SUD) treatment services. Medicaid expansion has been previously associated with increased access to SUD services for low-income adults. Thus, the pandemic may have differentially impacted overdose mortality depending on expansion status. This study examined trends in overdose mortality nationally and by state Medicaid expansion status from 2013 to 2020. METHODS: State-level data on overdose mortality were obtained from the Centers for Disease Control and Prevention's WONDER database for 2013-2020 (N = 408 state-years). The primary outcomes were drug and opioid overdose deaths per 100,000 residents. The primary exposure was Medicaid expansion status as of January 1st, 2020. Difference-in-difference (DID) models were used to compare changes in outcomes between expansion and non-expansion states after the onset of the COVID-19 pandemic. RESULTS: The U.S. experienced 91,799 drug overdose deaths in 2020, a 29.9% relative increase from 2019. Expansion states experienced an adjusted increase of 7.0 drug overdose deaths per 100,000 residents (95% CI 3.3, 10.7) and non-expansion states experienced an increase of 4.3 deaths (95% CI 1.5, 8.2) from 2019 to 2020. Similar trends were observed in opioid overdose deaths. In DID models, Medicaid expansion was not associated with changes in drug (0.9 deaths, 95% CI -2.0, 3.7) or opioid overdose deaths (0.8 deaths, 95% CI -1.8, 3.5). CONCLUSIONS: The increase in drug or opioid overdose deaths experienced during the first year of the COVID-19 pandemic was similar in states with and without Medicaid expansion.

County-Level Impact of the COVID-19 Pandemic on Excess Mortality Among U.S. Veterans: A Population-Based Study.

BACKGROUND: As the novel coronavirus (COVID-19) continues to impact the world at large, Veterans of the US Armed Forces are experiencing increases in both COVID-19 and non-COVID-19 mortality. Veterans may be more susceptible to the pandemic than the general population due to their higher comorbidity burdens and older age, but no research has examined if trends in excess mortality differ between these groups. Additionally, individual-level data on demographics, comorbidities, and deaths are provided in near-real time for all enrolees of the Veterans Health Administration (VHA). These data provide a unique opportunity to identify excess mortality throughout 2020 at a subnational level, and to validate these estimates against local COVID-19 burden. METHODS: We queried VHA administrative data on demographics and comorbidities for 11.4 million enrolees during 2016-2020. Pre-pandemic data was used to develop and cross-validate eight mortality prediction models at the county-level including Poisson, Poisson quasi-likelihood, negative binomial, and generalized estimating equations. We then estimated county-level excess Veteran mortality during 2020 and correlated these estimates with local rates of COVID-19 confirmed cases and deaths. FINDINGS: All models demonstrated excellent agreement between observed and predicted mortality during 2016-2019; a Poisson quasi-likelihood with county fixed effects minimized median squared error with a calibration slope of 1.00. Veterans of the U.S. Armed Forces faced an excess mortality rate of 13% in 2020, which corresponds to 50,299 excess deaths. County-level estimates of excess mortality were correlated with both COVID-19 cases (R2=0.77) and deaths per 1,000 population (R2=0.59). INTERPRETATION: We developed sub-national estimates of excess mortality associated with the pandemic and shared our data as a resource for researchers and data journalists. Despite Veterans' greater likelihood of risk factors associated with severe COVID-19 illness, their excess mortality rate was slightly lower than the general population. Consistent access to health care and the rapid expansion of VHA telemedicine during the pandemic may explain this divergence. FUNDING: This work was supported by grants from the Department of Veterans Affairs Quality Enhancement Research Initiative [PEC 16-001]. Dr. Griffith's effort was supported in part by the Agency for Healthcare Research & Quality [K12 HS026395].