Long-term Mammography Screening Trends and Predictors of Return to Screening after the COVID-19 Pandemic: Results from a Statewide Registry.

Purpose To evaluate long-term trends in mammography screening rates and identify sociodemographic and breast cancer risk characteristics associated with return to screening after the COVID-19 pandemic. Materials and Methods In this retrospective study, statewide screening mammography data of 222 384 female individuals aged 40 years or older (mean age, 58.8 years ± 11.7 [SD]) from the Vermont Breast Cancer Surveillance System were evaluated to generate descriptive statistics and Joinpoint models to characterize screening patterns during 2000-2022. Log-binomial regression models estimated associations of sociodemographic and risk characteristics with post-COVID-19 pandemic return to screening. Results The proportion of female individuals in Vermont aged 50-74 years with a screening mammogram obtained in the previous 2 years declined from a prepandemic level of 61.3% (95% CI: 61.1%, 61.6%) in 2019 to 56.0% (95% CI: 55.7%, 56.3%) in 2021 before rebounding to 60.7% (95% CI: 60.4%, 61.0%) in 2022. Screening adherence in 2022 remained substantially lower than that observed during the 2007-2010 apex of screening adherence (66.1%-67.0%). Joinpoint models estimated an annual percent change of -1.1% (95% CI: -1.5%, -0.8%) during 2010-2022. Among the cohort of 95 644 individuals screened during January 2018-March 2020, the probability of returning to screening during 2020-2022 varied by age (eg, risk ratio [RR] = 0.94 [95% CI: 0.93, 0.95] for age 40-44 vs age 60-64 years), race and ethnicity (RR = 0.84 [95% CI: 0.78, 0.90] for Black vs White individuals), education (RR = 0.84 [95% CI: 0.81, 0.86] for less than high school degree vs college degree), and by 5-year breast cancer risk (RR = 1.06 [95% CI: 1.04, 1.08] for very high vs average risk). Conclusion Despite a rebound to near prepandemic levels, Vermont mammography screening rates have steadily declined since 2010, with certain sociodemographic groups less likely to return to screening after the pandemic. Keywords: Mammography, Breast, Health Policy and Practice, Neoplasms-Primary, Epidemiology, Screening Supplemental material is available for this article. © RSNA, 2024.

Home and wild food procurement were associated with improved food security during the COVID-19 pandemic in two rural US states.

Both food insecurity and home and wild food procurement (HWFP), including gardening, increased in many countries during the COVID-19 pandemic; yet little evidence has demonstrated what impact HWFP had on food security. Using data from a representative sample of nearly 1000 residents in the two most rural US states (Vermont and Maine) conducted via an online survey in Spring/Summer 2021, as well as matching techniques, we compare food security outcomes among households who did and did not participate in HWFP in the first year of the pandemic. Nearly 60% of respondents engaged in HWFP in some way during the first year of the pandemic, with food insecure households more likely to do HWFP. Furthermore, HWFP early in the COVID-19 pandemic is associated with improved food security in the 9-12 months later, though these improvements were primarily associated with newly, not chronically, food insecure households. Newly and chronically food insecure households were more likely to want to continue these activities in the future, but also exhibited greater barriers to land access and costs associated with these activities. These results suggest that HWFP may provide food security improvements for certain households that utilize them, especially during crisis situations. Future research about HWFP should continue to explore multiple HWFP strategies, their barriers, and their potentially myriad relationships to food security, diet, and health outcomes, especially with longitudinal data.

Statewide Trends in Buprenorphine Prescribing in Rural and Nonrural Vermont: Analysis of Population-based Patient Pharmacy Claims.

IMPORTANCE: Opioid-related mortality rates have risen dramatically over the past decade, and office-based opioid treatment using buprenorphine offers hope for combatting this trend. Vermont's policymakers, health care systems, and treatment providers have worked to expand access to treatment throughout the rural state. OBJECTIVE: The objective of the current study was to characterize the trends in the number of buprenorphine prescribers and the number of patients per prescriber in Vermont over the past decade (2010-2020). METHODS: We used Vermont's all-payer claims database to identify patients with buprenorphine claims between 2010 and 2020 and their prescribers. We conducted analyses of trends in the number of prescribers treating different numbers of patients, the number of patients treated by prescribers in those categories, and the number of rural (vs nonrural) patients filling buprenorphine prescriptions. We used Z tests to determine if there were statistical differences between trends. RESULTS: The number of buprenorphine prescribers treating 10+ patients grew more rapidly than other prescriber groups ( P < 0.001). Nearly half of Vermont patients in 2020 were treated by 33 high-volume prescribers who treated 100 or more patients with buprenorphine. The number of patients filling buprenorphine prescriptions in Vermont increased by 98% between 2010 and 2020, with greater increases seen among rural than nonrural residents (107% vs 72%; P = 0.008). CONCLUSIONS AND RELEVANCE: Since 2010, Vermont has increased utilization of its office-based opioid treatment capacity, particularly in rural counties.

Optimal non-pharmaceutical pandemic response strategies depend critically on time horizons and costs.

The COVID-19 pandemic has called for swift action from local governments, which have instated non-pharmaceutical interventions (NPIs) to curb the spread of the disease. The swift implementation of social distancing policies has raised questions about the costs and benefits of strategies that either aim to keep cases as low as possible (suppression) or aim to reach herd immunity quickly (mitigation) to tackle the COVID-19 pandemic. While curbing COVID-19 required blunt instruments, it is unclear whether a less-transmissible and less-deadly emerging pathogen would justify the same response. This paper illuminates this question using a parsimonious transmission model by formulating the social distancing lives vs. livelihoods dilemma as a boundary value problem using calculus of variations. In this setup, society balances the costs and benefits of social distancing contingent on the costs of reducing transmission relative to the burden imposed by the disease. We consider both single-objective and multi-objective formulations of the problem. To the best of our knowledge, our approach is distinct in the sense that strategies emerge from the problem structure rather than being imposed a priori. We find that the relative time-horizon of the pandemic (i.e., the time it takes to develop effective vaccines and treatments) and the relative cost of social distancing influence the choice of the optimal policy. Unsurprisingly, we find that the appropriate policy response depends on these two factors. We discuss the conditions under which each policy archetype (suppression vs. mitigation) appears to be the most appropriate.

Spillover After Mammography Guideline Change: Evidence From State-Level Trends.

INTRODUCTION: Changes to which age groups are recommended for mammography may have affected screening rates for all women. This spillover effect has not previously been shown empirically in a national sample. METHODS: Using data from the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System from 2002 to 2018, authors tested whether screening trends at a national level changed after the 2009 U.S. Preventive Services Task Force guideline change. The authors also tested whether state-level screening trends for women aged 40-49 years and 75+ years were associated with screening trends for women aged 50-74 years. Analyses were conducted in March-December 2022. RESULTS: In a model predicting state-level trends in screening for women aged 50-74 years, authors find positive, statistically significant associations with screening trends for women aged 40-49 years (p=0.033) and for women aged 75+ years (p<0.001). CONCLUSIONS: Deimplementation is difficult and important for controlling healthcare spending and delivering high value care. However, states most successful at reducing mammography screening rates among those aged 40-49 years and 75+ years also had greater reductions in recommended screening among women aged 50-74 years. More work is needed to understand and mitigate the unintended consequences of deimplementation.

Belief correlations with parental vaccine hesitancy: Results from a national survey.

We conducted a nationally representative survey of parents' beliefs and self-reported behaviors regarding childhood vaccinations. Using Bayesian selection among multivariate models, we found that beliefs, even those without any vaccine or health content, predicted vaccine-hesitant behaviors better than demographics, social network effects, or scientific reasoning. The multivariate structure of beliefs combined many types of ideation that included concerns about both conspiracies and side effects. Although they are not strongly related to vaccine-hesitant behavior, demographics were key predictors of beliefs. Our results support some of the previously proposed pro-vaccination messaging strategies and suggest some new strategies not previously considered.

Realizamos una encuesta nacionalmente representativa sobre las creencias y comportamientos autodeclarados por los padres con relación a la vacunación infantil. Usando selección bayesiana entre modelos multivariados, encontramos que las creencias, aun aquellas sin ningún contenido sobre vacunas o salud, predijeron comportamientos indecisos sobre la vacuna mejor que las características demográficas, los efectos de las redes sociales o el razonamiento científico. La estructura multivariada de las creencias combinó muchos tipos de ideación que incluyó preocupaciones tanto sobre conspiraciones como efectos secundarios. Aunque no están relacionados fuertemente con los comportamientos de indecisión, las características demográficas fueron predictores centrales de las creencias. Nuestros resultados apoyan algunas de las estrategias de mensajes pro­vacunación propuestas previamente y sugieren algunas nuevas estrategias no consideradas anteriormente. [vacunación, encuesta, cultura acumulativa, bayesiana].

Reciprocal relationships among influenza experiences, perceptions, and behavior: Results from a national, longitudinal survey of United States adults.

OBJECTIVE: Our objective was to model the reciprocal relationships of perceived risk of contracting influenza with and without influenza vaccination, vaccination behavior, and reported influenza illness. METHODS: We fit structural equation models to data from a longitudinal survey of adults in the United States collected through the RAND American Life Panel. Data come from fall and spring surveys fielded before and after each of 3 influenza seasons, 2016/2017, 2017/2018, and 2018/2019, for a total of 6 waves. RESULTS: As expected, reported influenza experience was associated with increased perceived influenza risk in subsequent survey waves. Furthermore, perceived risk was associated with subsequent vaccination behavior, such that vaccination was more common for those with higher perceived unvaccinated influenza risk and lower perceived vaccinated influenza risk. Perhaps surprisingly, both elements of perceived risk were also associated with a greater likelihood of subsequent reported influenza illness. This malleability in illness reports may reflect uncertainty, as more respondents reported being sick but being unsure about whether they had influenza than reported certainty that they had influenza. CONCLUSIONS: Interventions that influence perceptions about past experience with influenza, including increased testing and informational campaigns about influenza symptoms, could have unanticipated impacts on perceptions of influenza vaccination and vaccination behavior.

Association among trust in health care providers, friends, and family, and vaccine hesitancy.

A health care provider's vaccination recommendation is one of the most important factors influencing parents' decisions about whether to vaccinate their children. Unfortunately, vaccine hesitancy is associated with mistrust of health care providers and the medical system. We conducted a survey of 2440 adults through the RAND American Life Panel in 2019. Respondents were asked to rate their trust in pediatricians, OB/GYNs, doulas, midwives, lactation consultants, friends and family for information about childhood vaccines. Respondents were also asked about willingness to vaccinate a hypothetical child as a measure of vaccine hesitancy. We used principal component analysis to characterize variance in responses on trust items and logistic regression to model the relationship between trust and vaccine hesitancy. Vaccine hesitancy was associated with: (1) lower overall trust; (2) reduced trust in OB/GYNs and pediatricians and greater trust in doulas, midwives, and lactation consultants; and (3) greater trust in friends and family.

Using an Agent-based Model to Examine Deimplementation of Breast Cancer Screening.

OBJECTIVE: The objective of this study was to examine the potential impact of provider social networks and experiences with patients on deimplementation of breast cancer screening. RESEARCH DESIGN: We constructed the Breast Cancer-Social network Agent-based Model (BC-SAM), which depicts breast cancer screening decisions, incidence, and progression among 10,000 women ages 40 and over and the screening recommendations of their providers over a 30-year period. The model has patient and provider modules that each incorporate social network influences. Patients and providers were connected in a network, which represented patient-patient peer connections, provider-provider peer connections, connections between providers and patients they treat, and friend/family relationships between patients and providers. We calibrated provider decisions in the model using data from the CanSNET national survey of primary care physicians in the United States, which we fielded in 2016. RESULTS: First, assuming that providers' screening recommendations for women ages 50-74 remain unchanged but their recommendations for screening among younger (below 50 y old) and older (75+ y old) women decrease, we observed a decline in predicted screening rates for women ages 50-74 due to spillover effects. Second, screening rates for younger and older women were slow to respond to changes in provider recommendations; a 78% decline in provider recommendations to older women over 30 years resulted in an estimated 23% decline in patient screening in that group. Third, providers' experiences with unscreened patients, friends, and family members modestly increased screening recommendations over time (7 percentage points). Finally, we found that provider peer effects can have a substantial impact on population screening rates and can entrench existing practices. CONCLUSION: Modeling cancer screening as a complex social system demonstrates a range of potential effects and may help target future interventions designed to reduce overscreening.

Comparing covariation among vaccine hesitancy and broader beliefs within Twitter and survey data.

Over the past decade, the percentage of adults in the United States who use some form of social media has roughly doubled, increasing from 36 percent in early 2009 to 72 percent in 2019. There has been a corresponding increase in research aimed at understanding opinions and beliefs that are expressed online. However, the generalizability of findings from social media research is a subject of ongoing debate. Social media platforms are conduits of both information and misinformation about vaccines and vaccine hesitancy. Our research objective was to examine whether we can draw similar conclusions from Twitter and national survey data about the relationship between vaccine hesitancy and a broader set of beliefs. In 2018 we conducted a nationally representative survey of parents in the United States informed by a literature review to ask their views on a range of topics, including vaccine side effects, conspiracy theories, and understanding of science. We developed a set of keyword-based queries corresponding to each of the belief items from the survey and pulled matching tweets from 2017. We performed the data pull of the most recent full year of data in 2018. Our primary measures of belief covariation were the loadings and scores of the first principal components obtained using principal component analysis (PCA) from the two sources. We found that, after using manually coded weblinks in tweets to infer stance, there was good qualitative agreement between the first principal component loadings and scores using survey and Twitter data. This held true after we took the additional processing step of resampling the Twitter data based on the number of topics that an individual tweeted about, as a means of correcting for differential representation for elicited (survey) vs. volunteered (Twitter) beliefs. Overall, the results show that analyses using Twitter data may be generalizable in certain contexts, such as assessing belief covariation.

The Stability of Influenza Vaccination Behavior Over Time: A Longitudinal Analysis of Individuals Across 8 Years.

BACKGROUND: Seasonal influenza vaccination is an important behavior with significant individual and public health consequences, yet fewer than half of individuals in the USA are vaccinated annually. To promote vaccination adherence, it is important to understand the factors that affect vaccination behavior. PURPOSE: In this research, we focused on one such factor, an individual's vaccination history. We gathered longitudinal data to track and understand the relationship between an individual's vaccination history and their current behaviors. METHODS: U.S. adults completed multiple surveys over an 8 year period, which asked about whether they had received the influenza vaccination during the previous flu season. We analyzed the data to determine the strength of the relationship between vaccination decisions across single-year and multiyear intervals. Additionally, we fitted two mathematical models to the data to determine whether individuals were better characterized as having a stable propensity to vaccinate or a stable propensity to repeat their previous decisions. RESULTS: Individuals exhibited highly consistent behavior across adjacent years, yet, across the complete extent of the longitudinal study, they were far more likely to repeat the earlier decision to vaccinate. Surprisingly, the results of the mathematical model suggest that individuals are better characterized as having a stable propensity to repeat their previous decisions rather than a stable propensity to vaccinate per se. Although most individuals had an extremely strong tendency to repeat the previous decision, some had a far weaker propensity to do so. CONCLUSIONS: This suggests that interventions intended to increase vaccination uptake might be most impactful for those individuals with only a weak tendency to vaccinate or not to vaccinate.

Linking physician attitudes to their breast cancer screening practices: A survey of US primary care providers and gynecologists.

Despite changes to breast cancer screening guidelines intended to decrease screening in younger and older women, mammography rates remain high. We investigated physician attitudes towards screening younger and older women. Surveys were mailed to US primary care providers and gynecologists between May and September 2016 (871/1665, 52.3% adjusted response rate). We assessed physician (1) attitudes towards screening younger (45-49years) and older (75+ years) women and (2) recommendations for routine mammography. We used exploratory factor analysis to identify underlying themes among physician attitudes and created measures standardized to a 5-point scale. Using multivariable logistic regression models, we examined associations between physician attitudes and screening recommendations. Attitudes identified with factor analysis included: potential regret, expectations, and discordant guidelines (referred to as potential regret), patient-related hazards due to screening, physician limitations and uncertainty, and concerns about rationing care. Gynecologists had higher levels of potential regret compared to internists. In adjusted analyses, physicians with increasing potential regret (1-point increment on 5-point scale) had higher odds of recommending mammography to younger (OR 8.68; 95% CI 5.25-14.36) and older women (OR 4.62; 95% CI 3.50-6.11). Increasing concern for patient-related hazards was associated with decreased odds of recommending screening to older women (OR 0.68; 95% CI 0.56-0.83). Physicians were more motivated by potential regret in recommending screening for younger and older women than by concerns for patient-related hazards in screening. Addressing physicians' most salient concerns, such as fear of missing cancer diagnoses and malpractice, may present an important opportunity to improving delivery of guideline-concordant cancer screening.

A General Agent-Based Model of Social Learning.

When engaging in behaviors that may entail risks or outcomes that are unknown or uncertain, individuals often look beyond their own experiences (including past behaviors and subsequent outcomes) to consider the experiences of others in their immediate social networks. This social influence at the micro-scale (i.e., the way in which individuals are influenced by their immediate social networks) can affect change in the greater social web in such a way that social networks may have profound effects on decisionmaking at the population level. Such micro-level social influence is central to many theories of individual decisionmaking and behavior. Observations of population-level dynamics at the macro-level demonstrate the end result of these processes-for example, over time, people's behavior tends to look more like that of their peers. This article describes a general agent-based model (ABM) for studying social influence, and uses that general ABM to explore the relationship between micro-influence and macro-dynamics for broad classes of problems. We also describe an approach to tailor the general ABM to model a specific behavior influenced by social learning, which we illustrate using surveys designed to inform the ABM. The framework we developed could be useful for studying any system in which social learning may occur. But while our general ABM can produce dynamics reminiscent of those that might result from many different types of behaviors, it will typically need to be tailored when used to model any particular behavior.

Linking Reminders and Physician Breast Cancer Screening Recommendations: Results From a National Survey.

PURPOSE: Physician reminders have successfully increased rates of mammography. However, considering recent changes to breast cancer screening guidelines that disagree on the optimal age to start and stop mammography screening, we sought to examine the extent to which reminders have been deployed for breast cancer screening targeting younger and older patients. METHODS: A mailed survey was sent to a national sample of 2,000 primary care physicians between May and September 2016. Physicians were asked whether they received reminders to screen women in various age groups (40 to 44, 45 to 49, and ≥ 75 years), the organizational screening guidelines they trusted most, and whether they recommended routine breast cancer screening to average-risk women in the different age groups. Using regression models, we assessed the association between reminders and physician screening recommendations, controlling for physician and practice characteristics, and evaluated whether the association varied by the guidelines they trusted. RESULTS: A total of 871 physicians responded (adjusted response rate, 52.3%). Overall, 28.9% of physicians reported receiving reminders for patient ages 40 to 44 years, 32.5% for patient ages 45 to 49 years, and 16.5% for patient ages ≥ 75 years. Receiving reminders significantly increased the likelihood of physicians recommending mammography screening. In adjusted analyses, 84% (95% CI, 77% to 90%) of physicians who received reminders recommended screening for women ages ≥ 75 versus 65% (95% CI, 62% to 69%) of those who did not receive reminders. The associations between reminders and screening recommendations remained consistent regardless of which guidelines physicians reported trusting. CONCLUSION: Reminders were significantly associated with increases in physician screening recommendations for mammography, underscoring the need for careful implementation in scenarios where guidelines are discordant.

Alternatives to the ACA's Affordability Firewall.

The Affordable Care Act (ACA) was designed to increase health insurance coverage while limiting the disruption to individuals with existing sources of insurance coverage, particularly those with employer-sponsored insurance (ESI). To limit disruption to those with coverage, the ACA implements the employer mandate, which requires firms with more than 50 employees to offer health insurance or face penalties, and the individual "affordability firewall," which limits subsidies to individuals lacking access to alternative sources of coverage that are "affordable." This article examines the policy impacts of the affordability firewall and investigates two potential modifications. Option 1, which is the "entire family" scenario, involves allowing an exception to the firewall for anyone in a family where the family ESI premium contribution exceeds 9.5 percent of the worker's household income. In Option 2, the "dependents only" scenario, only dependents (and not the worker) become eligible for Marketplace subsidies when the ESI premium contribution exceeds 9.5 percent of the worker's household income. Relative to the ACA, RAND researchers estimate that nongroup enrollment will increase by 4.1 million for Option 1 and by 1.4 million for Option 2. However, the number without insurance only declines by 1.5 million in Option 1 and 0.7 million in Option 2. The difference between the increase in nongroup enrollment and the decrease in uninsurance is primarily due to ESI crowd-out, which is more pronounced for Option 1. Researchers also estimated that about 1.3 million families who have ESI and unsubsidized nongroup coverage under current ACA policy would receive Marketplace subsidies under the alternative affordability firewall scenarios. For these families, health insurance coverage would become substantially more affordable; these families' risk of spending at least 20 percent of income on health care would drop by more than two thirds. We additionally estimated that federal spending will increase by $8.9 billion and $3.9 billion for Options 1 and 2, respectively, relative to the ACA.

The Economic Incidence of Health Care Spending in Vermont.

In 2015, Vermont legislators may consider financing plans to implement Act 48, a law that aims to provide universal health care coverage to all Vermont residents starting in 2017. In this analysis, we estimate the economic incidence of payments for health care by Vermont residents and the value of health care benefits received by Vermont residents in 2012 and 2017, without the implementation of Act 48 reforms. The goal of the analysis was to understand how health care is currently paid for in Vermont, and to provide a baseline for understanding the possible effects of Act 48. We use data from the 2012 Vermont Household Health Interview Survey, the Vermont Health Care Uniform Evaluation and Reporting System, and administrative data on taxes to estimate payments in 2012. We then project these estimates forward to 2017, using the RAND COMPARE microsimulation to account for how health care coverage in Vermont will change as a result of the Affordable Care Act (ACA). We find that most Vermont residents receive more in health benefits than they pay for directly or through taxes. While lower-income individuals, on average, pay less than higher-income individuals, there is considerable variation across individuals in the level of payment for health care. Much of the current variation stems from the fractured nature of the health system, with some individuals receiving coverage through employers, some through the Exchange (i.e., the health insurance marketplace created by the ACA), and some through other sources. As Vermont considers health care reform, legislators may wish to consider options to reduce the degree of variation in payments made by individuals with similar income levels.

Social network effects of nonlifesaving early-stage breast cancer detection on mammography rates.

OBJECTIVES: We estimated the effect of anecdotes of early-stage, screen-detected cancer for which screening was not lifesaving on the demand for mammography. METHODS: We constructed an agent-based model of mammography decisions, in which 10 000 agents that represent women aged 40 to 100 years were linked together on a social network, which was parameterized with a survey of 716 women conducted through the RAND American Life Panel. Our model represents a population in equilibrium, with demographics reflecting the current US population based on the most recent available census data. RESULTS: The aggregate effect of women learning about 1 category of cancers-those that would be detected but would not be lethal in the absence of screening-was a 13.8 percentage point increase in annual screening rates. CONCLUSIONS: Anecdotes of detection of early-stage cancers relayed through social networks may substantially increase demand for a screening test even when the detection through screening was nonlifesaving.

Effects of the Affordable Care Act on Consumer Health Care Spending and Risk of Catastrophic Health Costs.

This study examines the likely effects of the Affordable Care Act (ACA) on average annual consumer health care spending and the risk of catastrophic medical costs for the United States overall and in two large states that have decided not to expand their Medicaid programs (Texas and Florida). The ACA will have varied impacts on individuals' and families' spending on health care, depending on income level and on estimated 2016 insurance status without the ACA. The authors find that average out-of-pocket spending is expected to decrease for all groups considered in the analysis, although decreases in out-of-pocket spending will be largest for those who would otherwise be uninsured. People who would otherwise be uninsured who transition to the individual market under the ACA will have higher total health care spending on average after implementation of the ACA because they will now incur the cost of health insurance premiums. The authors also find that risk of catastrophic health care spending will decrease for individuals of all income levels for the insurance transitions considered; decreases will be greatest for those at the lowest income levels. Case studies found that in Texas and Florida, Medicaid expansion would substantially reduce out-of-pocket and total health care spending for those with incomes below 100 percent of the federal poverty level, compared with a scenario in which the ACA is implemented without Medicaid expansion. Expansion would reduce the risk of high medical spending for those covered under Medicaid who would remain uninsured without expansion.