Background

Medicaid expansion substantially increased health insurance coverage, but its effect on the delivery of preventative health care is unclear.

Objective

The objective of this study was to assess the impact of Medicaid expansion on the receipt of 15 different measures of preventive care including cancer screening, cardiovascular risk reduction, diabetes care, and other primary care measures.

Research design

We performed serial cross-sectional analysis of Behavioral Risk Factor Surveillance System (BRFSS) survey data from 2012 to 2017. We used a quasi-experimental design with difference-in-differences (DiD) analyses to examine changes in preventative health care delivery over 3 time periods in Medicaid expansion compared with nonexpansion states.

Subjects

We included low-income (<138% federal poverty level) nonelderly (age younger than 65 y) adults residing in 46 US states.

Measures

Our predictor was residing in a Medicaid expansion state (24 states) versus nonexpansion state (19 states). Our primary outcomes were preventative health care services, which we categorized as cancer screening (breast cancer, cervical cancer, and colorectal cancer); cardiovascular risk reduction (serum cholesterol screening in low-risk groups, serum cholesterol monitoring in high-risk groups, and aspirin use); diabetes care (serum cholesterol monitoring, hemoglobin A1c monitoring, foot examination, eye examination, and influenza vaccination, and pneumonia vaccination); and other primary care measures [influenza vaccination, alcohol use screening, and human immunodeficiency virus (HIV) screening].

Results

Survey responses from 500,495 low-income nonelderly adults from 2012 to 2017 were included in the analysis, representing 68.2 million US adults per year. Of the 15 outcomes evaluated, we did not detect statistically significant differences in cancer screening (3 outcomes), cholesterol screening or monitoring (2 outcomes), diabetes care (6 outcomes), or alcohol use screening (1 outcome) in expansion compared with nonexpansion states. Aspirin use (DiD 8.8%, P<0.001), influenza vaccination (DiD 1.4%, P=0.016), and HIV screening (DiD 1.9%, P=0.004) increased in expansion states compared with nonexpansion states.

Conclusions

Medicaid expansion was associated with an increase in aspirin use, influenza vaccination, and HIV screening in expansion states. Despite improvements in access to care, including health insurance, having a primary care doctor, and routine visits, Medicaid expansion was not associated with improvements in cancer screening, cholesterol monitoring, diabetes care, or alcohol use screening. Our findings highlight implementation challenges in delivering high-quality primary care to low-income populations.

Background

We examined the association between cannabis use and cardiovascular outcomes among the general population, among never-tobacco smokers, and among younger individuals.

Methods and results

This is a population-based, cross-sectional study of 2016 to 2020 data from the Behavioral Risk Factor Surveillance Survey from 27 American states and 2 territories. We assessed the association of cannabis use (number of days of cannabis use in the past 30 days) with self-reported cardiovascular outcomes (coronary heart disease, myocardial infarction, stroke, and a composite measure of all 3) in multivariable regression models, adjusting for tobacco use and other characteristics in adults 18 to 74 years old. We repeated this analysis among nontobacco smokers, and among men <55 years old and women <65 years old who are at risk of premature cardiovascular disease. Among the 434 104 respondents, the prevalence of daily and nondaily cannabis use was 4% and 7.1%, respectively. The adjusted odds ratio (aOR) for the association of daily cannabis use and coronary heart disease, myocardial infarction, stroke, and the composite outcome (coronary heart disease, myocardial infarction, and stroke) was 1.16 (95% CI, 0.98-1.38), 1.25 (95% CI, 1.07-1.46), 1.42 (95% CI, 1.20-1.68), and 1.28 (95% CI, 1.13-1.44), respectively, with proportionally lower log odds for days of use between 0 and 30 days per month. Among never-tobacco smokers, daily cannabis use was also associated with myocardial infarction (aOR, 1.49 [95% CI, 1.03-2.15]), stroke (aOR, 2.16 [95% CI, 1.43-3.25]), and the composite of coronary heart disease, myocardial infarction, and stroke (aOR, 1.77 [95% CI, 1.31-2.40]). Relationships between cannabis use and cardiovascular outcomes were similar for men <55 years old and women <65 years old.

Conclusions

Cannabis use is associated with adverse cardiovascular outcomes, with heavier use (more days per month) associated with higher odds of adverse outcomes.

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.

Substance use is associated with greater barriers and reduced access to care. Little research, however, has examined the relationship between cannabis use and receipt of preventive health services. Using data from the 2017 Behavioral Risk Factor Surveillance System, we examined the association between current cannabis use and receipt of 12 preventive health services, adjusting for sociodemographic characteristics and access to care. In analyses that adjusted for sociodemographic factors and access to care, participants with current cannabis use had lower odds of being vaccinated for influenza (AOR = 0.67, 95% CI = 0.54-0.83) and higher odds of ever receiving HPV vaccination (AOR = 1.77, 95% CI = 1.06-2.96) and HIV screening (AOR = 2.34, 95% CI = 1.88-2.92) compared with those without cannabis use. Among the 12 preventive services examined, we found three differences in receipt of preventive services by cannabis use status. Cannabis use does not appear to be associated with significant underuse of preventive services.

Background

Current health care reform efforts are focused on reorganizing health care systems to reduce waste in the US health care system.

Objective

To compare rates of overuse in different health care systems and examine whether certain systems of care or insurers have lower rates of overuse of health care services.

Data sources

Articles published in MEDLINE between 1978, the year of publication of the first framework to measure quality, and June 21, 2012.

Study selection

Included studies compared rates of overuse of procedures, diagnostic tests, or medications in at least 2 systems of care.

Data extraction

Four reviewers screened titles; 2 reviewers screened abstracts and full articles and extracted data.

Results

We identified 7 studies which compared rates of overuse of 5 services across multiple different health care settings. National rates of inappropriate coronary angiography were similar in Medicare HMOs and Medicare FFS (13% vs. 13%, P=0.33) and in a state-based study comparing 15 hospitals in New York and 4 hospitals in a Massachusetts-managed care plan (4% vs. 6%, P>0.1). Rates of carotid endarterectomy in New York State were similar in Medicare HMOs and Medicare FFS plans (8.4% vs. 8.6%, P=0.55) but nonrecommended use of antibiotics for the treatment of upper respiratory infection was higher in a managed care organization than a FFS private plan (31% vs. 21%, P=0.02). Rates of inappropriate myocardial perfusion imaging were similar in VA and private settings (22% vs. 16.6%, P=0.24), but rates of inappropriate surveillance endoscopy in the management of gastric ulcers were higher in the VA compared with private settings (37.4% vs. 20.4%-23.3%, P<0.0001).

Conclusions

The available evidence is limited but there is no consistent evidence that any 1 system of care has been more effective at minimizing the overuse of health care services. More research is necessary to inform current health care reform efforts directed at reducing overuse.

Background

Marijuana use is increasing in the United States, and its effect on cardiovascular health is unknown.

Purpose

To review harms and benefits of marijuana use in relation to cardiovascular risk factors and clinical outcomes.

Data sources

PubMed, MEDLINE, EMBASE, PsycINFO, and the Cochrane Library between 1 January 1975 and 30 September 2017.

Study selection

Observational studies that were published in English, enrolled adults using any form of marijuana, and reported on vascular risk factors (hyperglycemia, diabetes, dyslipidemia, and obesity) or on outcomes (stroke, myocardial infarction, cardiovascular mortality, and all-cause mortality in cardiovascular cohorts).

Data extraction

Study characteristics and quality were assessed by 4 reviewers independently; strength of evidence for each outcome was graded by consensus.

Data synthesis

13 and 11 studies examined associations between marijuana use and cardiovascular risk factors and clinical outcomes, respectively. Although 6 studies suggested a metabolic benefit from marijuana use, they were based on cross-sectional designs and were not supported by prospective studies. Evidence examining the effect of marijuana on diabetes, dyslipidemia, acute myocardial infarction, stroke, or cardiovascular and all-cause mortality was insufficient. Although the current literature includes several long-term prospective studies, they are limited by recall bias, inadequate exposure assessment, minimal marijuana exposure, and a predominance of low-risk cohorts.

Limitation

Poor- or moderate-quality data, inadequate assessment of marijuana exposure and minimal exposure in the populations studied, and variation in study design.

Conclusion

Evidence examining the effect of marijuana on cardiovascular risk factors and outcomes, including stroke and myocardial infarction, is insufficient.

Primary funding source

National Heart, Lung, and Blood Institute. (PROSPERO: CRD42016051297).

BACKGROUND: Understanding experiences with private important to improving the quality of health care coverage. OBJECTIVE: To examine the association of health with cost-related access barriers, medical debt, and dissatisfaction with care among privately insured Americans. DESIGN: We classified Americans with private insurance by self-reported health status into five groups (excellent, very good, good, fair, and poor health). We examined self-reported difficulty seeing a doctor due to costs, not taking medications due to costs, medical debt, and dissatisfaction with care among individuals with differing health status. We used logistic regression to examine the association of health status with individuals experiences after accounting for baseline characteristics. The analysis was repeated among individuals with different forms of private insurance. Odds ratios were converted to risk ratios to improve ease of interpretation of the results. SETTING: Behavioral Risk Factor Surveillance System of Americans in 17 states RESULTS: The sample included 82,494 US adults with private insurance. Following adjustment, compared to individuals with excellent health those in very good health, good health, fair health, and poor health reported increasingly higher risks of difficulty seeing a doctor due to costs with risk ratios of 1.02 (95% CI 1.01, 1.03), 1.07 (95% CI 1.06, 1.08), 1.18 (95% CI 1.17, 1.20), and 1.29 (95% CI 1.27, 1.31), respectively. Compared to individuals with excellent health, those in very good health, good health, fair health, and poor health reported increasingly higher risks of not taking medication due to costs, outstanding medical debt, and dissatisfaction with care. Similar relationships were seen across individually purchased and employer-sponsored insurance. CONCLUSION: Cost-related access barriers, medical debt, and dissatisfaction with care were common among individuals with private insurance and most pronounced among those with fair and poor health who likely need and use their health insurance the most.

Background

As health care systems shift to greater use of telemedicine and digital tools, an individual's digital health literacy has become an important skillset. The Veterans Health Administration (VA) has invested resources in providing digital health care; however, to date, no study has compared the digital health skills and preparedness of veterans receiving care in the VA to veterans receiving care outside the VA.

Objective

The goal of the research was to describe digital health skills and preparedness among veterans who receive care within and outside the VA health care system and examine whether receiving care in the VA is associated with digital preparedness (reporting more than 2 digital health skills) after accounting for demographic and social risk factors.

Methods

We used cross-sectional data from the 2016-2018 National Health Interview Survey to identify veterans (aged over 18 years) who obtain health care either within or outside the VA health care system. We used multivariable logistic regression models to examine the association of sociodemographic (age, sex, race, ethnicity), social risk factors (economic instability, disadvantaged neighborhood, low educational attainment, and social isolation), and health care delivery location (VA and non-VA) with digital preparedness.

Results

Those who received health care within the VA health care system (n=3188) were younger (age 18-49 years: 33.3% [95% CI 30.7-36.0] vs 24.2% [95% CI 21.9-26.5], P<.01), were more often female (34.7% [95% CI 32.0-37.3] vs 6.6% [95% CI 5.5-7.6], P<.01) and identified as Black (13.1% [95% CI 11.2-15.0] vs 10.2% [95% CI 8.7-11.8], P<.01), and reported greater economic instability (8.3% [95% CI 6.9-9.8] vs 5.5% [95% CI 4.6-6.5], P<.01) and social isolation (42.6% [95% CI 40.3-44.9] vs 35.4% [95% CI 33.4-37.5], P<.01) compared to veterans who received care outside the VA (n=3393). Veterans who obtained care within the VA reported more digital health skills than those who obtained care outside the VA, endorsing greater rates of looking up health information on the internet (51.8% [95% CI 49.2-54.4] vs 45.0% [95% CI 42.6-47.3], P<.01), filling a prescription using the internet (16.2% [95% CI 14.5-18.0] vs 11.3% [95% CI 9.6-13.0], P<.01), scheduling a health care appointment on the internet (14.1% [95% CI 12.4-15.8] vs 11.6% [95% CI 10.1-13.1], P=.02), and communicating with a health care provider by email (18.0% [95% CI 16.1-19.8] vs 13.3% [95% CI 11.6-14.9], P<.01). Following adjustment for sociodemographic and social risk factors, receiving health care from the VA was the only characteristic associated with higher odds (adjusted odds ratio [aOR] 1.36, 95% CI 1.12-1.65) of being digitally prepared.

Conclusions

Despite these demographic disadvantages to digital uptake, veterans who receive care in the VA reported more digital health skills and appear more digitally prepared than veterans who do not receive care within the VA, suggesting a positive, system-level influence on this cohort.

INTRODUCTION: Veterans are at high risk for lung cancer and are an important group for lung cancer screening. Previous research suggests that lung cancer screening may not be reaching healthier and/or non-White individuals, who stand to benefit most from lung cancer screening. We sought to test whether lung cancer screening is associated with poor health and/or race and ethnicity among veterans. METHODS: This cross-sectional, population-based study included veterans eligible for lung cancer screening (aged 55-79 years, ≥30 pack-year smoking history, current smokers or quit within 15 years, no previous lung cancer) in the 2017-2020 Behavioral Risk Factor Surveillance System surveys. Exposures were (1) poor health, defined as fair/poor health status and difficulty walking or climbing stairs, aligning with eligibility criteria for a pivotal lung cancer screening trial, and (2) race/ethnicity. The outcome was a receipt of lung cancer screening. All variables were self-reported. RESULTS: Of 3,376 lung cancer screening-eligible veterans representing an underlying population of 866,000 individuals, 20.3% (95% CI=17.3, 23.6) had poor health, and 13.7% (95% CI=10.6, 17.5) identified as non-White. Poor health was strongly associated with lung cancer screening (adjusted RR=1.64, 95% CI=1.06, 2.27); one third of veterans screened for lung cancer would not qualify for a pivotal lung cancer screening trial in terms of health. Marked racial disparities were observed among veterans: after adjustment, non-White veterans were 67% less likely to report lung cancer screening than White veterans (adjusted RR=0.33, 95% CI=0.11, 0.66). CONCLUSIONS: Lung cancer screening is correlated with poorer health and White race/ethnicity among veterans, which may undermine its population-level effectiveness. These results highlight the need to promote lung cancer screening, especially for healthier and/or non-White veterans, an important group of Americans for lung cancer screening.