ABSTRACT
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, 6â¯995â¯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.
Subject(s)
COVID-19 , COVID-19/epidemiology , Cohort Studies , Female , Humans , Internet , Male , Middle Aged , Pandemics , Primary Health Care , Veterans HealthSubject(s)
Veterans , Female , Humans , United States , United States Department of Veterans Affairs , Veterans Health , Women's HealthABSTRACT
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 1â¯197â¯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.
Subject(s)
Diabetes Mellitus, Type 2 , Glucagon-Like Peptide-1 Receptor , Healthcare Disparities , Prescriptions , Sodium-Glucose Transporter 2 Inhibitors , Veterans Health , Adult , Aged , Cross-Sectional Studies , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/ethnology , Ethnicity/statistics & numerical data , Female , Glucagon-Like Peptide-1 Receptor/agonists , Health Equity/statistics & numerical data , Healthcare Disparities/ethnology , Healthcare Disparities/statistics & numerical data , Humans , Hypoglycemic Agents/therapeutic use , Male , Practice Patterns, Physicians'/statistics & numerical data , Prescriptions/statistics & numerical data , Professional Practice/statistics & numerical data , Racial Groups/statistics & numerical data , Sodium-Glucose Transporter 2 Inhibitors/therapeutic use , United States/epidemiology , Veterans Health/ethnology , Veterans Health/statistics & numerical dataABSTRACT
BACKGROUND: Since the onset of the COVID-19 pandemic, telehealth has been an option for Veterans receiving urgent care through Veterans Health Administration Community Care (CC). OBJECTIVE: We assessed use, arrangements, Veteran decision-making, and experiences with CC urgent care delivered via telehealth. DESIGN: Convergent parallel mixed methods, combining multivariable regression analyses of claims data with semistructured Veteran interviews. SUBJECTS: Veterans residing in the Western United States and Hawaii, with CC urgent care claims March 1 to September 30, 2020. KEY RESULTS: In comparison to having in-person only visits, having a telehealth-only visit was more likely for Veterans who were non-Hispanic Black, were urban-dwelling, lived further from the clinic used, had a COVID-related visit, and did not require an in-person procedure. Predictors of having both telehealth and in-person (compared with in-person only) visits were other (non-White, non-Black) non-Hispanic race/ethnicity, urban-dwelling status, living further from the clinic used, and having had a COVID-related visit. Care arrangements varied widely; telephone-only care was common. Veteran decisions about using telehealth were driven by limitations in in-person care availability and COVID-related concerns. Veterans receiving care via telehealth generally reported high satisfaction. CONCLUSIONS: CC urgent care via telehealth played an important role in providing Veterans with care access early in the COVID-19 pandemic. Use of telehealth differed by Veteran characteristics; lack of in-person care availability was a driver. Future work should assess for changes in telehealth use with pandemic progression, geographic differences, and impact on care quality, care coordination, outcomes, and costs to ensure Veterans' optimal and equitable access to care.
Subject(s)
COVID-19 , Telemedicine , Veterans , Ambulatory Care , COVID-19/epidemiology , Humans , Pandemics , Telemedicine/methods , United States , Veterans HealthABSTRACT
BACKGROUND: Increasingly, women are serving in the military and seeking care at the Veterans Health Administration (VHA). Women veterans face unique challenges and barriers in seeking mental health (MH) care within VHA. VA Video Connect (VVC), which facilitates video-based teleconferencing between patients and providers, can reduce barriers while maintaining clinical effectiveness. OBJECTIVE: Primary aims were to examine gender differences in VVC use, describe changes in VVC use over time (including pre-COVID and 6 months following the beginning of COVID), and determine whether changes over time differed by gender. DESIGN: A retrospective cohort investigation of video-to-home telehealth for MH care utilization among veterans having at least 1 MH visit from October 2019 to September 2020. PARTICIPANTS: Veterans (236,268 women; 1,318,024 men). INTERVENTIONS (IF APPLICABLE): VVC involves face-to-face, synchronous, video-based teleconferencing between patients and providers, enabling care at home or another private location. MAIN MEASURES: Percentage of MH encounters delivered via VA Video Connect. KEY RESULTS: Women veterans were more likely than men to have at least 1 VVC encounter and had a greater percentage of MH care delivered via VVC in FY20. There was an increase in the percentage of MH encounters that were VVC over FY20, and this increase was greater for women than men. Women veterans who were younger than 55 (compared to those 55 and older), lived in urban areas (compared to those in rural areas), or were Asian (compared to other races) had a greater percentage of MH encounters that were VVC since the start of the pandemic, controlling for the mean percentage of VVC MH encounters in the 6 months pre-pandemic. CONCLUSIONS: VVC use for MH care is greater in women veterans compared to male veterans and may reduce gender-specific access barriers. Future research and VVC implementation efforts should emphasize maximizing patient choice and satisfaction.
Subject(s)
COVID-19 , Telemedicine , Veterans , COVID-19/epidemiology , Female , Humans , Male , Patient Acceptance of Health Care , Retrospective Studies , United States/epidemiology , United States Department of Veterans Affairs , Veterans/psychology , Veterans HealthABSTRACT
Importance: Despite longstanding efforts to improve health care quality for patients with complex needs who are at highest risk for hospitalization or death, to our knowledge, no guidance exists on what constitutes measurable high-quality care for this heterogeneous population. Identifying quality measures that are cross-cutting (ie, relevant to multiple chronic conditions and disease states) may enable health care professionals and health care systems to better design and report on quality improvement efforts for this patient population. Objective: To identify quality measures of care and prioritize quality-of-care concepts in the ambulatory primary care setting for patients in the Veterans Health Administration (VHA) who have complex care needs and are at high risk for adverse outcomes, such as hospitalization or death. Evidence Review: In this expert panel assessment and prioritization, relevant measure concepts for future quality measure development in 3 care categories (assessment, management, and other features of health care) were extracted from a systematic review, conducted from June 2020 to June 2021, of published studies that suggested, evaluated, or used indicators of quality care for patients at high risk of adverse outcomes. Measure concepts associated with single conditions, surgical or other specialty care settings, and inpatient care were excluded. A panel of 14 experts (10 VHA leaders and staff, 2 non-VHA physician investigators, and 2 veterans) discussed and rated the importance of the remaining set of potentially relevant measure concepts using a modified RAND/UCLA Appropriateness Method on January 15, 2021. Measure concepts were rated on a scale of 1 to 9, with 9 being the highest priority. A median rating of 7.5 or greater was used as the cutoff to identify the highest-priority items. Findings: The systematic review identified 519 measure concepts, from which 15 domains and 49 measure concepts were proposed for expert panel consideration. After panel discussions and changes to measure concepts, the expert panel rated 63 measure concepts in 13 domains. The measure concepts with the highest median ratings focused on caregiver availability and support, COVID-19 vaccination, and pneumonia vaccination (all rated 9.0); housing instability (rated 8.5); and physical function, depression symptoms, cognitive impairment, prescription regimen, primary care follow-up after an emergency department visit or hospitalization, and timely transmission of discharge information to primary care (all rated 8.0). Recommendations to improve care included timely assessment of housing instability, caregiver support, physical function, depression symptoms, and cognitive impairment; annual prescription regimen review; coordinated transitions in care; and preventive care including vaccinations. Conclusions and Relevance: The expert panelists identified a parsimonious set of high-priority, evidence-based, cross-cutting quality measure concepts for improving care of patients at high risk for adverse health outcomes in the VHA. These quality measures may inform both future research for patients at high risk and health care system quality improvement.
Subject(s)
COVID-19 , Quality Indicators, Health Care , COVID-19 Vaccines , Humans , Quality of Health Care , Veterans HealthABSTRACT
OBJECTIVE: The authors examined the use of Veterans Affairs Video Connect (VVC) for mental health care by rural and urban veterans and the impact of the COVID-19 pandemic on patterns of VVC use. METHODS: Data from 557,668 rural and 1,384,093 urban veterans (collected July 2019-October 2020) from the Veterans Health Administration Corporate Data Warehouse were examined with interrupted time-series models to determine rural versus urban VVC use before and during the initial 7 months of the pandemic. RESULTS: Before COVID-19, rates of VVC use as percentages of all mental health care were higher among rural veterans. After implementation of pandemic restrictions, rural veteran VVC use continued to increase, but this increase was surpassed by that of urban veterans. CONCLUSIONS: These findings highlight the need to monitor emerging disparities in telehealth use and to encourage and support use of VVC and access to mental health care for all veterans, particularly those experiencing barriers to care.
Subject(s)
COVID-19 , Veterans , Humans , United States/epidemiology , Veterans/psychology , COVID-19/epidemiology , Mental Health , Pandemics/prevention & control , Rural Population , Veterans Health , United States Department of Veterans AffairsABSTRACT
BACKGROUND: The COVID-19 epidemic in the United States is widespread, with more than 200,000 deaths reported as of September 23, 2020. While ecological studies show higher burdens of COVID-19 mortality in areas with higher rates of poverty, little is known about social determinants of COVID-19 mortality at the individual level. METHODS AND FINDINGS: We estimated the proportions of COVID-19 deaths by age, sex, race/ethnicity, and comorbid conditions using their reported univariate proportions among COVID-19 deaths and correlations among these variables in the general population from the 2017-2018 National Health and Nutrition Examination Survey (NHANES). We used these proportions to randomly sample individuals from NHANES. We analyzed the distributions of COVID-19 deaths by race/ethnicity, income, education level, and veteran status. We analyzed the association of these characteristics with mortality by logistic regression. Summary demographics of deaths include mean age 71.6 years, 45.9% female, and 45.1% non-Hispanic white. We found that disproportionate deaths occurred among individuals with nonwhite race/ethnicity (54.8% of deaths, 95% CI 49.0%-59.6%, p < 0.001), individuals with income below the median (67.5%, 95% CI 63.4%-71.5%, p < 0.001), individuals with less than a high school level of education (25.6%, 95% CI 23.4% -27.9%, p < 0.001), and veterans (19.5%, 95% CI 15.8%-23.4%, p < 0.001). Except for veteran status, these characteristics are significantly associated with COVID-19 mortality in multiple logistic regression. Limitations include the lack of institutionalized people in the sample (e.g., nursing home residents and incarcerated persons), the need to use comorbidity data collected from outside the US, and the assumption of the same correlations among variables for the noninstitutionalized population and COVID-19 decedents. CONCLUSIONS: Substantial inequalities in COVID-19 mortality are likely, with disproportionate burdens falling on those who are of racial/ethnic minorities, are poor, have less education, and are veterans. Healthcare systems must ensure adequate access to these groups. Public health measures should specifically reach these groups, and data on social determinants should be systematically collected from people with COVID-19.
Subject(s)
COVID-19/mortality , Healthcare Disparities/standards , Public Health , Social Determinants of Health/statistics & numerical data , Socioeconomic Factors , Aged , Comorbidity , Ethnicity/statistics & numerical data , Female , Health Services Needs and Demand , Humans , Male , Mortality , Public Health/methods , Public Health/standards , Quality Improvement/organization & administration , SARS-CoV-2/isolation & purification , United States , Veterans Health/statistics & numerical dataSubject(s)
Buprenorphine , COVID-19 , Opioid-Related Disorders , Humans , Opioid-Related Disorders/drug therapy , SARS-CoV-2 , Veterans HealthABSTRACT
BACKGROUND: Available COVID-19 mortality indices are limited to acute inpatient data. Using nationwide medical administrative data available prior to SARS-CoV-2 infection from the US Veterans Health Administration (VA), we developed the VA COVID-19 (VACO) 30-day mortality index and validated the index in two independent, prospective samples. METHODS AND FINDINGS: We reviewed SARS-CoV-2 testing results within the VA between February 8 and August 18, 2020. The sample was split into a development cohort (test positive between March 2 and April 15, 2020), an early validation cohort (test positive between April 16 and May 18, 2020), and a late validation cohort (test positive between May 19 and July 19, 2020). Our logistic regression model in the development cohort considered demographics (age, sex, race/ethnicity), and pre-existing medical conditions and the Charlson Comorbidity Index (CCI) derived from ICD-10 diagnosis codes. Weights were fixed to create the VACO Index that was then validated by comparing area under receiver operating characteristic curves (AUC) in the early and late validation cohorts and among important validation cohort subgroups defined by sex, race/ethnicity, and geographic region. We also evaluated calibration curves and the range of predictions generated within age categories. 13,323 individuals tested positive for SARS-CoV-2 (median age: 63 years; 91% male; 42% non-Hispanic Black). We observed 480/3,681 (13%) deaths in development, 253/2,151 (12%) deaths in the early validation cohort, and 403/7,491 (5%) deaths in the late validation cohort. Age, multimorbidity described with CCI, and a history of myocardial infarction or peripheral vascular disease were independently associated with mortality-no other individual comorbid diagnosis provided additional information. The VACO Index discriminated mortality in development (AUC = 0.79, 95% CI: 0.77-0.81), and in early (AUC = 0.81 95% CI: 0.78-0.83) and late (AUC = 0.84, 95% CI: 0.78-0.86) validation. The VACO Index allows personalized estimates of 30-day mortality after COVID-19 infection. For example, among those aged 60-64 years, overall mortality was estimated at 9% (95% CI: 6-11%). The Index further discriminated risk in this age stratum from 4% (95% CI: 3-7%) to 21% (95% CI: 12-31%), depending on sex and comorbid disease. CONCLUSION: Prior to infection, demographics and comorbid conditions can discriminate COVID-19 mortality risk overall and within age strata. The VACO Index reproducibly identified individuals at substantial risk of COVID-19 mortality who might consider continuing social distancing, despite relaxed state and local guidelines.