Objective: We sought to characterize patterns of utilization of telemental health among commercially insured individuals over the decade preceding COVID-19. Methods: We developed telemental health service groups from the US PharMetrics Plus database, using diagnostic codes to identify those diagnosed with mental health conditions and procedure codes to capture mental health visits delivered via telehealth sessions. We analyzed 2 indicators of utilization between January 1, 2010, and December 31, 2019: (1) the percentage of patients with mental health needs who used telemental health services and (2) the percentage of all mental health services provided via telehealth. We stratified our analyses by year, patient gender, patient age, and geographic region. Results: The proportion of mental health visits delivered via telemental health increased from 0.002% to 0.162% between 2010 and 2019. A larger proportion of males received telemental health services as compared to females; however, the proportion of mental health visits delivered via telehealth was higher for females than for males. Patients aged 18 to 34 years and those in the western US had the highest utilization compared to other age groups and geographic regions. Conclusions: Telemental health utilization comprised a small fraction of overall mental health services and beneficiaries in the IQVIA PharMetrics Plus claims data, but increased over time, with differences documented in utilization based on patient gender, patient age, geographic region, and type of telemental health claim. Evidence from this study may serve as a pre-pandemic baseline for comparison against future evaluations of telehealth expansion policies.

CONTEXT: Public health policy can play an important role in improving public health outcomes. Accordingly, there has been an increasing emphasis by policy makers on identifying and implementing evidence-informed public health policy interventions. PROGRAM OR POLICY: Growth and refinement of the field of research assessing the impact of legal interventions on health outcomes, known as legal epidemiology, prompted this review of studies on the relationship between laws and health or economic outcomes. IMPLEMENTATION: Authors systematically searched 8 major literature databases for all English language journal articles that assessed the effect of a law on health and economic outcomes published between January 1, 2009, and September 18, 2019. This search generated 12 570 unique articles 177 of which met inclusion criteria. The team conducting the systematic review was a multidisciplinary team that included health economists and public health policy researchers, as well as public health lawyers with expertise in legal epidemiological research methods. The authors identified and assessed the types of methods used to measure the laws' health impact. EVALUATION: In this review, the authors examine how legal epidemiological research methods have been described in the literature as well as trends among the studies. Overall, 3 major themes emerged from this study: (1) limited variability in the sources of the health data across the studies, (2) limited differences in the methodological approaches used to connect law to health outcomes, and (3) lack of transparency surrounding the source and quality of the legal data relied upon. DISCUSSION: Through highlighting public health law research methodologies, this systematic review may inform researchers, practitioners, and lawmakers on how to better examine and understand the impacts of legal interventions on health and economic outcomes. Findings may serve as a source of suggested practices in conducting legal epidemiological outcomes research and identifying conceptual and method-related gaps in the literature.

INTRODUCTION: To assess timing of Medicaid enrollment with late-stage colorectal cancer (CRC) diagnosis and estimate treatment costs by stage at diagnosis. METHODS: We analyzed 2000-2009 California and Texas Medicaid data linked with cancer registry data. We assessed the association of Medicaid enrollment timing with late-stage colorectal cancer and estimated total and incremental 6-month treatment costs to Medicaid by stage using a noncancer comparison group matched on age group and sex. RESULTS: Compared with Medicaid enrollment before diagnosis, enrolling after diagnosis was associated with late-stage diagnosis. Incremental per-person treatment costs were $31,063, $39,834, and $47,161 for localized, regional, and distant stage in California, respectively; and $28,701, $38,212, and $49,634 in Texas, respectively. DISCUSSION: In California and Texas, Medicaid enrollment after CRC diagnosis was associated with later-stage disease and higher treatment costs. Facilitating timely and continuous Medicaid enrollment may lead to earlier stage at diagnosis, reduced costs, and improved outcomes.

PURPOSE: The purpose of this paper is to examine the impact of rural hospital closures on age-adjusted hospitalization rates for ambulatory care sensitive condition (ACSC) and emergency care sensitive condition (ECSC) and associated outcomes, such as length of stay and in-hospital mortality in hospital service areas (HSAs) that utilized the closed hospital. METHODS: We used the State Inpatient Data from the Healthcare Cost and Utilization Project for 9 states from 2010 to 2017 and classified admissions as ACSC or ECSC. We compared age-adjusted admission rates and length of stay (LOS) for ACSC and ECSC rates and age adjusted in-hospital mortality rate for ECSC among rural ZIP codes in HSAs with a closure to rural ZIP codes in HSAs without closures. We used propensity score-weighted regression analysis and event study design. FINDINGS: Findings suggest that ACSC admission rates started to increase right before the closure. However, this increase levels off 2 years after closure. LOS for ACSC significantly decreased almost a year after closure. ECSC admissions showed a significant decrease for a few quarters 1 year before the closure. CONCLUSIONS: Rural hospital closures were associated with increase in ACSC admissions right before closure and for nearly 2 years post closure as well as decrease in ECSC admissions before closure. As rural hospitals continue to close, efforts to ensure communities affected by these closures maintain access to primary health care may help eliminate increases in costly preventable hospital admissions for ACSC while ensuring access for emergency care services.

PURPOSE: This study estimates the rural-urban differences in outpatient service utilization and expenditures for depression, anxiety disorder, and substance use disorder, and the evolving mental health provider mix for privately insured US adults aged 18-64 during 2005-2018. METHODS: We used the IBM MarketScan Commercial Claims and Encounters Database for individuals covered by employer-sponsored health insurance, from 2005 to 2018, with a yearly total number of beneficiaries ranging from 17.5 to 53.1 million. Claims for nonelderly adults with mental health and substance abuse coverage are included. Outcomes include rates of outpatient service utilization for depression, anxiety disorder, and substance use disorder; counts of outpatient visits; expenditure and share of the out-of-pocket cost; and the mental health services provider mix. FINDINGS: Rural enrollees were less likely than urban enrollees to use outpatient mental health services for depression by 1.2% (percentage points) in 2005 and 0.6% in 2018. Among those who used outpatient mental health services, rural enrollees had fewer outpatient visits than their urban counterparts (difference: 1.8-2.4 visits for depression, 1.2-1.7 visits for anxiety disorder, and 0.7-2.1 visits for substance use disorder). Rural patients paid less per year for mental health outpatient visits of the 3 conditions but incurred a higher share of out-of-pocket expenses. Rural and urban patients differ in the mix of mental health providers, with rural enrollees relying more on primary care providers than urban enrollees. CONCLUSIONS: Rural-urban disparities in access to mental health services persist during 2005-2018 among a population with private insurance.

INTRODUCTION: Improving access to naloxone is an important public health strategy in the U.S. This study examines the state-level trends in naloxone dispensing from 2012 to 2019 for all 50 states and the District of Columbia. METHODS: Data from IQVIA Xponent were used to examine the trends and geographic inequality in annual naloxone dispensing rates and the number of naloxone prescriptions dispensed per high-dose opioid prescription from 2012 to 2019 and from 2016 to 2019 to correspond with the Centers for Disease Control and Prevention Guideline for Prescribing Opioids for Chronic Pain release. Annual percentage change was estimated using linear regression. Analyses were conducted in 2020. RESULTS: Naloxone dispensing rates and the number of naloxone prescriptions per 100 high-dose opioid prescriptions increased from 2012 to 2019 across all states and the District of Columbia. Average state-level naloxone dispensing rates increased from 0.55 per 100,000 population in 2012 to 45.60 in 2016 and 292.31 in 2019. Similarly, the average number of naloxone prescriptions per 100 high-dose opioid prescriptions increased from 0.002 in 2012 to 0.24 in 2016 and 3.04 in 2019. Across both measures of naloxone dispensing, the geographic inequality gap increased during the study period. In 2019, the number of naloxone prescriptions dispensed per 100 high-dose opioid prescriptions ranged from 1.04 to 16.64 across states. CONCLUSIONS: Despite increases in naloxone dispensing across all states, dispensing rates remain low, with substantial variation and increasing disparities over time at the state level. This information may be helpful in efforts to improve naloxone access and in designing state-specific intervention programs.

INTRODUCTION: Heart disease, cancer, unintentional injury, chronic lower respiratory disease, and stroke are the 5 leading causes of death in the U.S. The objective of this review is to examine the economic value of prevention interventions addressing these 5 conditions. METHODS: Tufts Medical Center Cost-Effectiveness Analysis Registry data were queried from 2010 to 2018 for interventions that addressed any of the 5 conditions in the U.S. Results were stratified by condition, prevention stage, type of intervention, study sponsorship, and study perspective. The analyses were conducted in 2020, and all costs were reported in 2019 dollars. RESULTS: In total, 549 cost-effectiveness analysis studies examined interventions addressing these 5 conditions in the U.S. Tertiary prevention interventions were assessed in 61.4%, whereas primary prevention was assessed in 8.6% of the studies. Primary prevention studies were predominantly funded by government, whereas industry sources funded more tertiary prevention studies, especially those dealing with pharmaceutical interventions. The median incremental cost-effectiveness ratio for the 5 conditions combined was $68,500 per quality-adjusted life year. Median incremental cost-effectiveness ratios were lowest for primary prevention and highest for tertiary prevention. DISCUSSION: Primary prevention may be more cost effective than secondary and tertiary prevention interventions; however, research investments in primary prevention interventions, especially by industry, lag in comparison. These findings help to highlight the gaps in the cost-effectiveness analysis literature related to the 5 leading causes of death and identify understudied interventions and prevention stages for each condition.

PURPOSE: Suboptimal diet is a preventable cause of cancer. We aimed to estimate the economic burden of diet-associated cancer among US adults. METHODS: We used a Comparative Risk Assessment model to quantify the number of new cancer cases attributable to seven dietary factors among US adults ages 20 + years. A Markov cohort model estimated the 5-year medical costs for 15 diet-associated cancers diagnosed in 2015. We obtained dietary intake from 2013 to 2016 National Health and Nutrition Examination Survey, cancer incidence, and survival from 2008 to 2014 Surveillance, Epidemiology, and End Results (SEER) program, and medical costs from 2007 to 2013 linked SEER-Medicare data. RESULTS: The estimated 5-year medical costs of new diet-associated cancer cases diagnosed in 2015 were $7.44 (2018 US$). Colorectal cancer had the largest diet-related 5-year medical costs of $5.32B. Suboptimal consumption of whole grains ($2.76B), dairy ($1.82B), and high consumption of processed meats ($1.5B) accounted for the highest medical costs. Per-person medical costs attributable to suboptimal diet vary by gender, race, and age group. CONCLUSIONS: Suboptimal diet contributes substantially to the economic burden of diet-associated cancers among US adults. This study highlights the need to implement population-based strategies to improve diet and reduce cancer burden in the US.

BACKGROUND: Obesity is associated with a substantial health and economic burden in the general population in the United States. This study estimates the excess health care utilization and medical spending associated with overweight and obesity among long-term cancer survivors. METHODS: Long-term cancer survivors (≥2 years after their diagnosis) aged ≥18 years (N = 12,547) were identified from the nationally representative 2008-2016 Medical Expenditure Panel Survey. A 2-part modeling approach was used to calculate the average annual care utilization and spending by service type. Excess care utilization and spending associated with overweight (25 kg/m(2) ≤ body mass index [BMI] < 30 kg/m(2) ), obesity (BMI ≥ 30 kg/m(2) ), and severe obesity (BMI ≥ 40 kg/m(2) ), in comparison with normal weight (18.5 kg/m(2) ≤ BMI < 25 kg/m(2) ), were estimated. RESULTS: Compared with normal-weight cancer survivors, overweight survivors had comparable care utilization and medical spending; survivors with obesity had an additional $3216 (95% CI, $1940-$4492) of medical spending, including $1243 (95% CI, $417-$2070) on hospital inpatient services and $1130 (95% CI, $756-$1504) on prescriptions per person per year. The excess annual medical spending associated with obesity among long-term cancer survivors translated to $19.7 billion in 2016 in the United States. The excess medical spending was magnified in cancer survivors with severe obesity ($5317 [95% CI, $2849-$7785], which translated to $6.7 billion in 2016). Excess care utilization and medical spending were mostly explained by comorbid conditions related to obesity. CONCLUSIONS: For long-term cancer survivors, obesity was associated with increased health care utilization and substantial excess medical spending. This suggests that policies and practices promoting a healthy lifestyle and achieving and maintaining a healthy body weight for cancer survivors may reduce their health care utilization and economic burden.

Awareness of the link between breast cancer and risk factors such as family history of breast cancer and alcohol consumption may help modify health behaviors. To reduce risk factors for breast cancer among young women, it is important to understand overall levels of risk awareness and socioeconomic differences in awareness. Data from the National Survey of Family Growth 2011-2015 were used to examine awareness of two risk factors for breast cancer, positive family history and alcohol consumption, among women aged 15-44 years (n = 10,940) in the United States by presence of risk factors and by socioeconomic characteristics. Prevalence of positive family history, non-binge, and binge drinking was 30%, 29%, and 31%, respectively among women aged 15-44. Awareness of positive family history of breast cancer as a risk factor for breast cancer was 88%, whereas for alcohol consumption it was 25%. Awareness of family history as a risk factor was higher among women with positive family history of breast cancer compared to those without. Current drinkers were more likely to believe that alcohol was not a risk factor for breast cancer compared to those who did not drink. Racial/ethnic minority women and those with lower education and income had lower awareness of family history as a risk factor. Awareness of alcohol consumption as a risk factor for breast cancer was low across all socioeconomic groups. Evidence-based interventions to increase risk awareness and decrease excessive alcohol use among young women are needed to reduce the risk of developing breast cancer.

Background: In recent years, most insurance plans eliminated cost-sharing for breast cancer screening and recommended screening intervals changed, and newer modalities-digital mammography and breast tomosynthesis-became more widely available. The objectives of this study are to examine how these changes affected utilization, frequency, and costs of breast cancer screening among commercially insured women, and to understand factors associated with utilization and frequency of screening. Materials and Methods: This study used commercial insurance claims data for women 50 to 64 years of age, continuously enrolled in commercial insurance plans during 2012-2016. Results: Of the 685,737 eligible women, 20% were not screened, 40% received annual screening, 24% received biennial screening, and 16% were screened less frequently than recommended during the time period examined. Sociodemographic factors such as age <60 years, rurality, and fee-for-service insurance were associated with low screening utilization. Patients who received annual screening incurred approximately 1.78 times higher costs compared to those who received biennial screening during the study period. Digital mammography was the most costly and commonly used modality along with computer-aided detection. Conclusions: Evidence-based interventions to promote screening among women who are screened less frequently are needed along with interventions to move toward biennial screening rather than annual screening. Increasing provider awareness regarding breast cancer screening rates and frequency among various sociodemographic groups is essential to guide provider recommendations and shared decision making. The results of this study can guide targeted public health interventions to reduce barriers to screening, and can also serve as inputs for economic analyses of screening interventions and programs.

PURPOSE: The purpose of this paper is to provide a brief overview of economic analysis methods used in estimating the costs and benefits of public health programs and systematically review the application of these methods to the National Breast and Cervical Cancer Early Detection Program (NBCCEDP). METHODS: Published literature on economic analyses of the NBCCEDP was systematically reviewed. The Consensus on Health Economic Criteria checklist was used to assess methodological quality of the included studies. RESULTS: Methods available for economic analysis of public health programs include program cost, cost-effectiveness, cost-utility, cost-benefit analysis, and budget impact analysis. Of these, program cost analysis, cost-effectiveness analysis, and cost-utility analysis have been applied to the NBCCEDP in previously published literature. CONCLUSION: While there have been multiple program cost analyses, there are relatively fewer cost-effectiveness and cost-utility studies and no cost-benefit and budget impact analysis studies to evaluate the NBCCEDP. Addressing these gaps will inform implementation of effective public health programs with equitable resource allocation to all population subgroups.

The Centers for Disease Control and Prevention (CDC) examines mental health indicators and trends, conducts surveillance of mental health concerns, and supports programs to address the mental health needs of men, women, and children (www.cdc.gov/mentalhealth/learn/index.htm). The Healthy People 2020 objectives (www.healthypeople.gov/2020/topics-objectives/topic/mental-health-and-mental-disorders) and National Prevention Strategy (www.hhs.gov/sites/default/files/disease-prevention-wellness-report.pdf) offer examples of public health objectives that can improve mental health through prevention by ensuring access to appropriate, quality mental health services.

In the United States in 2019, an estimated 16.9 million persons are living after receiving a cancer diagnosis (1). These cancer survivors face many challenges, including functional limitations, serious psychological distress (2), and other lasting and late effects of cancer treatments. Because of the high cost of cancer therapy, many cancer survivors are more likely to face substantial out-of-pocket health care expenditures and financial hardship, compared with persons without a history of cancer (3,4). Out-of-pocket expenditures and financial hardship associated with cancer have been higher among survivors aged 18-64 years than they have been among older survivors (5). To estimate annual out-of-pocket expenditures and financial hardship among cancer survivors aged 18-64 years, compared with persons without a cancer history, CDC, the American Cancer Society, and the National Cancer Institute analyzed data from the 2011-2016 Medical Expenditure Panel Survey (MEPS).* The average annual out-of-pocket spending per person was significantly higher among cancer survivors ($1,000; 95% confidence interval [CI] = $886-$1,113) than among persons without a cancer history ($622; CI = $606-$639). Financial hardship was common; 25.3% of cancer survivors reported material hardship (e.g., problems paying medical bills), and 34.3% reported psychological hardship (e.g., worry about medical bills). These findings add to accumulating evidence documenting the financial difficulties of many cancer survivors. Mitigating the negative impact of cancer in the United States will require implementation of strategies aimed at alleviating the disproportionate financial hardship experienced by many survivors. These strategies include systematic screening for financial hardship at cancer diagnosis and throughout cancer care, integration of discussions about the potential for adverse financial consequences of treatments in shared treatment decision-making, and linkage of patients and survivors to available resources to ensure access to high-quality evidence-based care.

OBJECTIVES: To estimate awardee-specific costs of delivering breast and cervical cancer screening services in their jurisdiction and to assess potential variation in the cost of key activities across awardees. METHODS: We developed the cost assessment tool to collect resource use and cost data from the National Breast and Cervical Cancer Early Detection Program awardees for 3 years between 2006 and 2010 and generated activity-based cost estimates. We estimated awardee-specific cost per woman served for all activities, clinical screening delivery services, screening promotion interventions, and overarching program support activities. RESULTS: The total cost per woman served by the awardees varied greatly from $205 (10th percentile) to $499 (90th percentile). Differences in the average (median) cost per person served for clinical services, health promotion interventions, and overarching support activities ranged from $51 to $125. CONCLUSIONS: The cost per woman served varied across awardee and likely reflected underlying differences across awardees in terms of screening infrastructure, population served, and barriers to screening uptake. Collecting information on contextual factors at the awardee, health system, provider, and individual levels may assist in understanding this variation in cost.

INTRODUCTION: This systematic review examines healthcare costs associated with mental health conditions among cancer survivors in the United States. Areas covered: Ten published studies were identified. Studies varied substantially in terms of population, mental health conditions examined, data collection methods, and type of cost reported. Cancer survivors with mental health conditions incurred significantly higher total medical costs and costs of most service types compared to cancer survivors without a mental health condition. Additionally, the total healthcare expenditure related to mental health was higher among cancer survivors compared with people without history of cancer. Expert commentary: Mental health conditions are associated with increased healthcare costs among cancer survivors. Future examination of other components of economic burden, including patient out-of-pocket costs, non-medical costs, such as transportation, childcare, and productivity losses for patients and their caregivers, will be important. Additionally, evaluation of economic burden by cancer site, stage at diagnosis, duration of survivorship, and treatment(s) will increase understanding of the overall impact of mental health conditions on cancer survivors and on the healthcare system.