Trends in Health Insurance and Type Among Military Veterans: United States, 2000-2016

Insomnia in the Veteran Population: A Sleep Health and Wellness Intervention

The purpose of this evidence-based project (EBP) was to determine if an evidence-based sleep health and wellness intervention improved sleep in veterans self-reporting a history of insomnia. Insomnia can negatively affect an individual's physical and psychological well-being, as well as increase health-care costs and decrease the overall quality of life. The intervention utilized a combination of insomnia treatments, delivered to two American Legion veteran participant groups: an Alabama American Legion Retreat and individuals at an American Legion Post site. The holistic-focused modalities used in this intervention included Cognitive Behavioral Therapy for Insomnia (CBT-I) techniques, sleep hygiene principles, and Complementary and Alternative Medicine (CAM) methods. The measurement tool, the Insomnia Severity Index (ISI), indicated statistically significant changes in the severity of participants' self-reported insomnia. Based upon the research evidence and results of the pre- and post-test ISI, a more permanent, ongoing sleep health and wellness intervention is feasible and would have numerous beneficial effects for the veteran's management of insomnia symptoms. Future efforts include implementing sleep hygiene, CAM interventions, and holistic nursing-supported education interventions at other sites and venues within the Alabama American Legion, as well as maintaining long-term community partnerships with veteran groups such as the Alabama American Legion.

The role of gender and veteran status in healthcare access among a national sample of U.S. adults with unhealthy alcohol use

Background: Routine healthcare access is critical to reduce drinking and its effects, yet little is known about Veteran and gender differences in routine healthcare access among unhealthy drinkers. The current study examined differences in routine healthcare access, stratified by Veteran status and gender, among a national sample of adults endorsing unhealthy drinking. Method: Using data from the Centers for Disease Control and Prevention's 2019 Behavioral Risk Factor Surveillance System National Survey, we identified adults who endorsed unhealthy drinking over the past month (N = 58,816; 41.4% female; 2.7% female Veterans). Bivariate and multivariable analyses modeled associations between gender, Veteran status, and their interaction in predicting routine healthcare access. All multivariable models adjusted for sociodemographic characteristics. Results: Veterans with unhealthy alcohol use reported high rates of routine healthcare access (e.g., >86% sought care in the past 2 years) and were less likely to experience a cost barrier to care (aOR = 0.75, 95% CI = 0.62-0.92). Females were more likely than males to report better access to care but also to experience a cost barrier (aOR = 1.2, 95% CI = 1.10-1.37). The interaction between Veteran status and gender was non-significant. Conclusions: Overall, healthcare access was better for Veterans and females with unhealthy alcohol use compared to civilians and males with unhealthy alcohol use. However, given that females were more likely to report a cost barrier, future implementation research aiming to improve equity in care may want to explore reasons for cost barriers and develop strategies to help reduce these barriers in order to eliminate gender disparities in primary care-based alcohol-related care.

Invasive Procedures and Associated Complications After Initial Lung Cancer Screening in a National Cohort of Veterans

BACKGROUND

Little is known about rates of invasive procedures and associated complications after lung cancer screening (LCS) in nontrial settings.

RESEARCH QUESTION

What are the frequency of invasive procedures, complication rates, and factors associated with complications in a national sample of veterans screened for lung cancer?

STUDY DESIGN AND METHODS

We conducted a retrospective cohort analysis of veterans who underwent LCS in any Veterans Health Administration (VA) facility between 2013 and 2019 and identified veterans who underwent invasive procedures within 10 months of initial LCS. The primary outcome was presence of a complication within 10 days after an invasive procedure. We conducted hierarchical mixed-effects logistic regression analyses to determine patient- and facility-level factors associated with complications resulting from an invasive procedure.

RESULTS

Our cohort of 82,641 veterans who underwent LCS was older, more racially diverse, and had more comorbidities than National Lung Screening Trial (NLST) participants. Overall, 1,741 veterans (2.1%) underwent an invasive procedure after initial screening, including 856 (42.3%) bronchoscopies, 490 (24.2%) transthoracic needle biopsies, and 423 (20.9%) thoracic surgeries. Among veterans who underwent procedures, 151 (8.7%) experienced a major complication (eg, respiratory failure, prolonged hospitalization) and an additional 203 (11.7%) experienced an intermediate complication (eg, pneumothorax, pleural effusion). Veterans who underwent thoracic surgery (OR, 7.70; 95% CI, 5.48-10.81), underwent multiple nonsurgical procedures (OR, 1.49; 95% CI, 1.15-1.92), or carried a dementia diagnosis (OR, 3.91; 95% CI, 1.79-8.52) were more likely to experience complications. Invasive procedures were performed less often than in the NLST (2.1% vs 4.2%), but veterans were more likely to experience complications after each type of procedure.

INTERPRETATION

These findings may reflect a higher threshold to perform procedures in veteran populations with multiple comorbidities and higher risks of complications. Future work should focus on optimizing the identification of patients whose chance of benefit likely outweighs the complication risks.

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.

Health Insurance Patterns of Older Veterans: Evidence from the Health and Retirement Study

With the increased availability of community care to veterans from the VA MISSION Act, policymakers and providers need to understand how older veterans are insured, particularly before Medicare eligibility at age 65. Using data from 1996 to 2018, this study examines the insurance patterns of veterans prior to the expansion of access to community care through the VA and compares those patterns to nonveterans. This study finds that veterans are more likely to have insurance than nonveterans and that they are less likely to rely on Medicaid and Medicare before age 65. Regression estimates also suggest that veterans with at least some college education are less likely to have private insurance and are more likely to be uninsured than nonveterans with the same educational attainment.

Health Care Access Expansions and Use of Veterans Affairs and Other Hospitals by Veterans

This cohort study examines changes in the use of Veterans Affairs (VA) and non-VA hospitals by VA enrollees and mortality associated with these policies.

Do functional status and Medicare claims data improve the predictive accuracy of an electronic health record mortality index? Findings from a national Veterans Affairs cohort

Background

Electronic health record (EHR) prediction models may be easier to use in busy clinical settings since EHR data can be auto-populated into models. This study assessed whether adding functional status and/or Medicare claims data (which are often not available in EHRs) improves the accuracy of a previously developed Veterans Affairs (VA) EHR-based mortality index.

Methods

This was a retrospective cohort study of veterans aged 75 years and older enrolled in VA primary care clinics followed from January 2014 to April 2020 (n = 62,014). We randomly split participants into development (n = 49,612) and validation (n = 12,402) cohorts. The primary outcome was all-cause mortality. We performed logistic regression with backward stepwise selection to develop a 100-predictor base model using 854 EHR candidate variables, including demographics, laboratory values, medications, healthcare utilization, diagnosis codes, and vitals. We incorporated functional measures in a base + function model by adding activities of daily living (range 0-5) and instrumental activities of daily living (range 0-7) scores. Medicare data, including healthcare utilization (e.g., emergency department visits, hospitalizations) and diagnosis codes, were incorporated in a base + Medicare model. A base + function + Medicare model included all data elements. We assessed model performance with the c-statistic, reclassification metrics, fraction of new information provided, and calibration plots.

Results

In the overall cohort, mean age was 82.6 years and 98.6% were male. At the end of follow-up, 30,263 participants (48.8%) had died. The base model c-statistic was 0.809 (95% CI 0.805-0.812) in the development cohort and 0.804 (95% CI 0.796-0.812) in the validation cohort. Validation cohort c-statistics for the base + function, base + Medicare, and base + function + Medicare models were 0.809 (95% CI 0.801-0.816), 0.811 (95% CI 0.803-0.818), and 0.814 (95% CI 0.807-0.822), respectively. Adding functional status and Medicare data resulted in similarly small improvements among other model performance measures. All models showed excellent calibration.

Conclusions

Incorporation of functional status and Medicare data into a VA EHR-based mortality index led to small but likely clinically insignificant improvements in model performance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03126-z.

Health Insurance Coverage Among Veterans Receiving Care From VA Health Care Facilities

Reasons for acquiring insurance outside Department of Veterans Affairs (VA) health care coverage among VA enrollees are incompletely understood. To assess Veterans' decision-making and acquisition of non-VA health care insurance in the Affordable Care Act era, we used mailed questionnaires and semistructured interviews in a stratified random sample of VA enrollees <65 years in the Midwest. Of the 3,666 survey participants, 32.1% reported non-VA insurance. Frequently reported reasons included wanting coverage for emergency situations or family members. Those without non-VA insurance cited unaffordability as the main obstacle. Analysis of the semistructured interview data revealed similar findings. In multivariable logistic regression analyses, characteristics associated with non-VA insurance included higher income (>$50,000 vs. <$10,000, odds ratio [OR] = 5.95, 95% confidence interval [CI]: 3.45-10.3, p < .001). As financial barriers exist for acquisition of non-VA insurance and hence community care, it is critically important that VA enrollees' health care needs are met through VA or community providers financed through VA.

Adherence to Follow-up Testing Recommendations in US Veterans Screened for Lung Cancer, 2015-2019

IMPORTANCE

Lung cancer screening (LCS) can reduce lung cancer mortality with close follow-up and adherence to management recommendations. Little is known about factors associated with adherence to LCS in real-world practice, with data limited to case series from selected LCS programs.

OBJECTIVE

To analyze adherence to follow-up based on standardized follow-up recommendations in a national cohort and to identify factors associated with delayed or absent follow-up.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study was conducted in Veterans Health Administration (VHA) facilities across the US. Veterans were screened for lung cancer between 2015 to 2019 with sufficient follow-up time to receive recommended evaluation. Patient- and facility-level logistic regression analyses were performed. Data were analyzed from November 26, 2019, to December 16, 2020.

MAIN OUTCOMES AND MEASURES

Receipt of the recommended next step after initial LCS according to Lung CT Screening Reporting & Data System (Lung-RADS) category, as captured in VHA or Medicare claims.

RESULTS

Of 28 294 veterans (26 835 [94.8%] men; 21 969 individuals [77.6%] were White; mean [SD] age, 65.2 [5.5] years) who had an initial LCS examination, 17 863 veterans (63.1%) underwent recommended follow-up within the expected timeframe, whereas 3696 veterans (13.1%) underwent late evaluation, and 4439 veterans (15.7%) had no apparent evaluation. Facility-level differences were associated with 9.2% of the observed variation in rates of late or absent evaluation. In multivariable-adjusted models, Black veterans (odds ratio [OR], 1.19 [95% CI, 1.10-1.29]), veterans with posttraumatic stress disorder (OR, 1.13 [95% CI, 1.03-1.23]), veterans with substance use disorders (OR, 1.11 [95% CI, 1.01-1.22]), veterans with lower income (OR, 0.88 [95% CI, 0.79-0.98]), and those living at a greater distance from a VHA facility (OR, 1.06 [95% CI, 1.02-1.10]) were more likely to experience delayed or no follow-up; veterans with higher risk findings (Lung-RADS category 4 vs Lung-RADS category 1: OR, 0.35 [95% CI, 0.28-0.43]) and those screened in high LCS volume facilities (OR, 0.38 [95% CI, 0.21-0.67]) or academic facilities (OR, 0.86 [95% CI, 0.80-0.92]) were less likely to experience delayed or no follow-up. In sensitivity analyses, varying how stringently adherence was defined, expected evaluation ranged from 14 486 veterans (49.7%) under stringent definitions to 20 578 veterans (78.8%) under liberal definitions.

CONCLUSIONS AND RELEVANCE

In this cohort study that captured follow-up care from the integrated VHA health care system and Medicare, less than two-thirds of patients received timely recommended follow-up after initial LCS, with higher risk of delayed or absent follow-up among marginalized populations, such as Black individuals, individuals with mental health disorders, and individuals with low income, that have long experienced disparities in lung cancer outcomes. Future work should focus on identifying facilities that promote high adherence and disseminating successful strategies to promote equity in LCS among marginalized populations.

Preventive Care Delivery After the Veterans Choice Program

INTRODUCTION

The Veterans Choice Program expanded Veteran access to community care. The Veterans Choice Program may negatively impact the receipt of preventive care services owing to care fragmentation. This study assesses 10 measures of preventive care in Veterans with the Department of Veterans Affairs coverage before and after the Veterans Choice Program.

METHODS

The study population included Veterans who responded to the National Health Interview Survey during the 2 time periods before and after Veterans Choice Program implementation: January 2011-October 2014 and November 2015-December 2018. Outcomes were preventive care services categorized as cardiovascular risk reduction (cholesterol monitoring, blood pressure monitoring, aspirin use), infectious disease prevention (influenza vaccination and HIV testing), and diabetes care (fasting blood glucose monitoring, podiatry visits, ophthalmology visits, influenza vaccination, and pneumonia vaccination). Two different analyses were conducted: (1) unadjusted and multivariable-adjusted pre-post analysis and (2) difference-in-differences analyses. Analyses were conducted in 2019.

RESULTS

Measures of cardiovascular risk reduction and influenza vaccination were not statistically different before and after Veterans Choice Program implementation using the 2 different analytic approaches. In unadjusted pre-post analysis, after Veterans Choice Program implementation, Veterans with Veterans Affairs coverage had increased HIV testing (66.1%‒75.4%, p=0.008), podiatry visits (22.4%‒38.3%, p=0.01), and ophthalmology visits (62.2%‒77.2%, p=0.02). Using multivariable adjustment for participant sociodemographic factors, Veterans Choice Program implementation was associated with higher odds of podiatry visits (AOR=2.28, 95% CI=1.24, 4.20, p=0.009) and ophthalmology visits (AOR=2.11, 95% CI=1.13, 3.94, p=0.02) among Veterans with diabetes. In difference-in-differences analyses, Veterans Choice Program implementation was associated with increased podiatry visits (AOR=2.95, 95% CI=1.49, 5.83, p=0.002) among Veterans with diabetes and Veterans Affairs coverage compared with that among those with other coverage types, but no statistically significant effect was observed for ophthalmology visits.

CONCLUSIONS

Veterans with Veterans Affairs coverage and diabetes had an increase in podiatry visits after Veterans Choice Program implementation. There was no evidence that Veterans Choice Program implementation had a negative impact on the receipt of preventive care services among Veterans with Veterans Affairs coverage.

Physician skin cancer screening among U.S. military veterans: Results from the National Health Interview Survey

Introduction

Although military veterans are at increased risk for skin cancer, little is known about the extent to which they have been screened for skin cancer. The study objective was to examine the prevalence and correlates of physician skin cancer screening among U.S. military veterans.

Methods

Data were drawn from the National Health Interview Survey. The study sample consisted of 2,826 individuals who reported being military veterans. Receipt of a physician skin examination was measured using a single question that asked participants whether they had ever had all of their skin from head to toe checked for cancer by a dermatologist or some other kind of doctor.

Results

Less than a third (30.88%) of participants reported ever having a physician skin examination. Factors positively associated with receipt of a physician skin examination in a multivariable logistic regression analysis included: older age, greater educational level, non-Hispanic white race/ethnicity, having TRICARE (military) health insurance, greater skin sensitivity to the sun, and engagement in more sun protection behaviors.

Conclusions

The majority of military veterans have never been screened for skin cancer by a physician. Screening rates were higher among individuals with one or more skin cancer risk factors. Future research is warranted to test targeted skin cancer screening interventions for this at risk and understudied population.

Veterans Affairs Pharmacogenomic Testing for Veterans (PHASER) clinical program

In 2019, the Veterans Affairs (VA), the largest integrated US healthcare system, started the Pharmacogenomic Testing for Veterans (PHASER) clinical program that provides multi-gene pharmacogenomic (PGx) testing for up to 250,000 veterans at approximately 50 sites. PHASER is staggering program initiation at sites over a 5-year period from 2019 to 2023, as opposed to simultaneous initiation at all sites, to facilitate iterative program quality improvements through Plan-Do-Study-Act cycles. Current resources in the PGx field have not focused on multisite, remote implementation of panel-based PGx testing. In addition to bringing large scale PGx testing to veterans, the PHASER program is developing a roadmap to maximize uptake and optimize the use of PGx to improve drug response outcomes.

Did the Affordable Care Act Decrease Veteran Enrollment in the Veterans Health Administration?

BACKGROUND

Provisions of the Affordable Care Act (ACA) provided nonelderly individuals, including Veterans, with additional health care coverage options. This may impact enrollment for health care through the Veterans Health Administration (VHA). National enrollment data was used to: (1) compare characteristics of enrollees at 3 time points in relation to the implementation of ACA insurance provisions (2012); and (2) examine enrollment trends.

METHODS

The study population included a 10% sample of Veterans under age 65 who were VHA enrollees between January 2012 and September 2015. Demographic and baseline characteristics were compared between 3 enrollment groups: pre-2012, pre-ACA (2012-2013), and post-ACA (2014-2015). Using an interrupted time series approach, we employed pooled logistic regression to assess trends in new VHA enrollment, overall, and by select enrollee characteristics.

RESULTS

A total of 429,833 enrollees were identified. Compared with pre-ACA enrollees, post-ACA enrollees were more likely to be older, have a service-connected disability, live further away from a VHA medical center, but less likely to use primary care within 6 months. The post-ACA quarterly trend in the odds of being a new enrollee was 3% lower (95% confidence interval: 0.96, 0.98) as compared with the pre-ACA trend. This decline was consistent across sex, geography, (all but 1) priority group, and state Medicaid-expansion subgroups.

CONCLUSIONS

The ACA appears to have contributed to a decline in new VHA enrollment. In addition, the profile of newer enrollees differs from that of pre-ACA enrollees. The VHA must continue to monitor trends in demand in order to continue delivering high-quality, efficient care.

Sociodemographic Risk Factors for Serious Psychological Distress among U.S. Veterans: Findings from the 2016 National Health Interview Survey

Serious Psychological Distress (SPD) is a measure of mental health associated with poor functioning. This study identified sociodemographic risk factors for SPD, among veterans using Veterans Health Administration (VHA), TRICARE or the Civilian Health and Medical Programs for Uniformed Services (CHAMP) (all referred herein as VA coverage) and compared risk factors for SPD to non-veterans. VA coverage offers preventative care and treatment for illnesses and injuries to veterans with the aim of improving their quality of life. Veterans with and with no SPD, using VA coverage aged 18 to 64 years were sampled from the 2016 National Health Interview Survey (NHIS) (n = 525 total, n = 48 veterans with serious psychological distress) were compared to each other and to non-veterans sampled from the NHIS (n = 24,121 total and n = 1055 with serious psychological distress), by sex, age group, race/ethnicity, education level, living arrangements, education level, number of chronic health conditions, and region of residence. The greatest proportion of veterans with SPD were female, middle aged (45-64 years), white, had less than a high school education, and lived alone or with other adults (compared to those living with a spouse/partner). The greatest proportion of veterans with SPD lived in the Southern and Western U.S. regions, and the smallest proportion lived in the Northeastern U.S. region. Hispanic and white veterans were at increased risk for SPD relative to black veterans, and relative to their same race/ethnic counterparts in the non-veteran civilian population. Additional analyses suggest that veterans with SPD experience greater barriers to care compared to veterans without SPD. Further research is warranted to examine access to mental and physical health care providers in U.S. regions with the greatest proportions of veterans with SPD. Particular attention is needed for female veterans due to their high rates of SPD relative to male veterans.

Health coverage types and their relationship to mental and physical health in U.S. veterans

OBJECTIVE

To examine sociodemographic characteristics and chronic health conditions in veterans across health coverage types including those without coverage.

DESIGN

The sample included cross-sectional data from veterans aged 18 years and over, collected in the 2016 National Health Interview Survey (n = 3487). Chronic health conditions and sociodemographic variables were examined across eleven health coverage types and combinations of health coverage types, as follows: No coverage, Medicare, Medicaid, Private, TRICARE (formerly known as the Civilian Health and Medical Program of the Uniformed Services (CHAMPUS)), TRICARE and Medicare, Veteran's Administration, Veteran's Administration and Medicare, Veteran's Administration and Private, Veteran's Administration and Private and Medicare.

RESULTS

Approximately 3.9% of veterans did not have coverage. The greatest proportion had private coverage (28.2%), then private coverage plus Medicare (19.6%). Only 5.9% had Veterans Administration coverage solely. Among the veterans not covered, the majority were young, lived alone, had less than a high school education and resided in the South. The most common chronic health conditions among non-covered veterans were obesity and migraine. Regional differences were observed in the types of chronic health conditions. Veterans in the Northeast were less likely to report serious psychological distress. In a logistic regression, younger age (18-44 years), living alone and having less than a high school education were predictive of no coverage, but number of chronic health conditions was not.

CONCLUSION

A population of veterans without health coverage may be undeserved and at risk for poor mental and physical health due to non-health related factors.

Medicaid Expansion as an Employment Incentive Program for People With Disabilities

Before the Patient Protection and Affordable Care Act (ACA), many Americans with disabilities were locked into poverty to maintain eligibility for Medicaid coverage. US Medicaid expansion under the ACA allows individuals to qualify for coverage without first going through a disability determination process and declaring an inability to work to obtain Supplemental Security Income. Medicaid expansion coverage also allows for greater income and imposes no asset tests. In this article, we share updates to our previous work documenting greater employment among people with disabilities living in Medicaid expansion states. Over time (2013-2017), the trends in employment among individuals with disabilities living in Medicaid expansion states have become significant, indicating a slow but steady progression toward employment for this group post-ACA. In effect, Medicaid expansion coverage is acting as an employment incentive program for people with disabilities. These findings have broad policy implications in light of recent changes regarding imposition of work requirements for Medicaid programs.