Appealing to Americans' altruism is not enough to nudge them to accept novel vaccines.

BACKGROUND: The role of altruism in the acceptance of novel preventive healthcare technologies like vaccines has not been thoroughly elucidated. METHODS: We 1:1 randomized n = 2004 Amazon Mechanical Turk (MTurk) participants residing in the USA into a control or treatment arm with vaccination decisions framed altruistically, to elicit their preferences for COVID-19 vaccination using web-based discrete choice experiments. We used conditional and mixed logit models to estimate the impact of framing decisions in terms of altruism on vaccination acceptance. RESULTS: Valid responses were provided by 1674 participants (control, n = 848; treatment, n = 826). Framing vaccination decisions altruistically had no significant effect on vaccination acceptance. Further, respondents' degree of altruism had no association with vaccination acceptance. LIMITATIONS: The MTurk sample may not be representative of the American population. We were unable to ascertain concordance between stated and revealed preferences. CONCLUSIONS AND IMPLICATIONS: Framing vaccination decisions in terms of altruism does not appear to significantly influence vaccination acceptance and may not be an effective nudging mechanism to increase the uptake of novel vaccines. Instead, a favorable vaccination profile appears to be the primary driver of uptake.

Analysis of agreement between measures of subjective cognitive impairment and probable dementia in the National Health and Aging Trends Study.

BACKGROUND: Subjective cognitive impairment (SCI) measures in population-based surveys offer potential for dementia surveillance, yet their validation against established dementia measures is lacking. METHODS: We assessed agreement between SCI and a validated probable dementia algorithm in a random one-third sample (n = 1936) of participants in the 2012 National Health and Aging Trends Study (NHATS). RESULTS: SCI was more prevalent than probable dementia (12.2% vs 8.4%). Agreement between measures was 90.0% and of substantial strength. Misclassification rates were higher among older and less-educated subgroups due to higher prevalence of false-positive misclassification but did not vary by sex or race and ethnicity. DISCUSSION: SCI sensitivity (63.4%) and specificity (92.5%) against dementia were comparable with similar metrics for the NHATS probable dementia measure against the "gold-standard" Aging, Demographics, and Memory Study-based dementia criteria, implying that population-based surveys may afford cost-effective opportunities for dementia surveillance to assess risk and inform policy. HIGHLIGHTS: The prevalence of subjective cognitive impairment (SCI) is generally higher than that of a validated measure of probable dementia, particularly within the youngest age group, females, Whites, and persons with a college or higher degree. Percent agreement between SCI and a validated measure of probable dementia was 90.0% and of substantial strength (prevalence- and bias-adjusted kappa, 0.80). Agreement rates were higher in older and less-educated subgroups, driven by the higher prevalence of false-positive disagreement, but did not vary significantly by sex or race and ethnicity. SCI's overall sensitivity and specificity were 63.4% and 92.5%, respectively, against a validated measure of probable dementia, suggesting utility as a low-cost option for dementia surveillance. Heterogeneity in agreement quality across subpopulations warrants caution in its use for subgroup analyses.

An effectiveness-implementation trial protocol to evaluate PrEP initiation among U.S. cisgender women using eHealth tools vs. standard care.

Background: The United States' (U.S.) initiative to End the HIV Epidemic aims to reduce new HIV infections in areas of high HIV prevalence. Despite national efforts to reduce HIV incidence, cisgender women continue to represent approximately one out of every five new HIV diagnoses in the U.S. Taking pre-exposure prophylaxis (PrEP) is an effective HIV prevention strategy; however, PrEP initiation among cisgender women is suboptimal, with only 10% of eligible women receiving PrEP prescriptions in 2019. Methods: We designed a trial to test the effectiveness of interventions to increase PrEP initiation, while evaluating the implementation strategy (hybrid type II trial) in seven obstetrics and gynecology (OB/GYN) clinics (two federally qualified health centers, three community-based, and two academic) in Baltimore, Maryland. A total of 42 OB/GYN providers will be enrolled and randomized (1:1:1) into one of three clinical trial arms (standard of care, patient-level intervention, or multi-level intervention). Eligible patients of enrolled providers will receive a sexual health questionnaire before their appointment through the electronic health record's (EHR) patient portal. The questionnaire will be scored in three tiers (low, moderate, and high) to assess HIV risk. Patients at low risk will be offered an HIV test only, while those who score medium or high risk will be included in the clinical trial and assigned to the clinical trial arm associated with their provider. Differences in PrEP initiation, our primary outcome, across the three arms will be analyzed using generalized linear mixed-effect models with logistic regression. We will adjust results for demographic differences observed between arms and examine PrEP initiation stratified by patient's and provider's race and ethnicity.Additionally, a comprehensive economic analysis for each intervention will be conducted. Discussion: We hypothesize that gathering information on sensitive sexual behaviors electronically, communicating HIV risk in an understandable and relatable format to patients and OB/GYN providers, and deploying EHR alerts will increase PrEP initiation and HIV testing. Trial Registration: The trial is registered with ClinicalTrials.gov (NCT05412433) on 09 June 2022. https://clinicaltrials.gov/ct2/show/NCT05412433?term=NCT05412433&draw=2&rank=1.

Caregiving-Related Work Productivity Loss Among Employed Family and Other Unpaid Caregivers of Older Adults.

OBJECTIVES: Although nearly half of all family and unpaid caregivers to older adults work, little is known about short-term work impacts of caregiving using measures encompassing both missed work time and reduced productivity while physically at work. We quantify the prevalence, costs, and correlates of caregiving-related work productivity loss. METHODS: We used the 2015 National Study of Caregiving and National Health and Aging Trends Study to estimate caregiving-related work absences (absenteeism) and reduced productivity while at work (presenteeism). We calculated costs of lost productivity using hours lost, compensation, and a wage multiplier, accounting for the additional cost of replacing employee time. We examined correlates of caregiving-related absenteeism and presenteeism separately, using multivariable logistic regression models, adjusting for caregiver sociodemographic characteristics, occupation and hours worked, role overload, older adult health, use of respite care, support groups, flexible workplace schedules, help from family or friends, and caregiver training. RESULTS: Nearly 1 in 4 (23.3%) of the estimated 8.8 million employed family caregivers reported either absenteeism or presenteeism over a 1-month period owing to caregiving. Among those affected, caregiving reduced work productivity by one-third on average-or an estimated $5600 per employee when annualized across all employed caregivers-primarily because of reduced performance while present at work. Productivity loss was higher among caregivers of older adults with significant care needs and varied according to sociodemographic characteristics and caregiver supports. CONCLUSIONS: Findings emphasize the potential economic value of targeted policy intervention to support working caregivers.

Using Microsimulation Modeling to Inform EHE Implementation Strategies in Los Angeles County.

BACKGROUND: Pre-exposure prophylaxis (PrEP) is essential to ending HIV. Yet, uptake remains uneven across racial and ethnic groups. We aimed to estimate the impacts of alternative PrEP implementation strategies in Los Angeles County. SETTING: Men who have sex with men, residing in Los Angeles County. METHODS: We developed a microsimulation model of HIV transmission, with inputs from key local stakeholders. With this model, we estimated the 15-year (2021-2035) health and racial and ethnic equity impacts of 3 PrEP implementation strategies involving coverage with 9000 additional PrEP units annually, above the Status-quo coverage level. Strategies included PrEP allocation equally (strategy 1), proportionally to HIV prevalence (strategy 2), and proportionally to HIV diagnosis rates (strategy 3), across racial and ethnic groups. We measured the degree of relative equalities in the distribution of the health impacts using the Gini index (G) which ranges from 0 (perfect equality, with all individuals across all groups receiving equal health benefits) to 1 (total inequality). RESULTS: HIV prevalence was 21.3% in 2021 [Black (BMSM), 31.1%; Latino (LMSM), 18.3%, and White (WMSM), 20.7%] with relatively equal to reasonable distribution across groups (G, 0.28; 95% confidence interval [CI], 0.26 to 0.34). During 2021-2035, cumulative incident infections were highest under Status-quo (n = 24,584) and lowest under strategy 3 (n = 22,080). Status-quo infection risk declined over time among all groups but remained higher in 2035 for BMSM (incidence rate ratio, 4.76; 95% CI: 4.58 to 4.95), and LMSM (incidence rate ratio, 1.74; 95% CI: 1.69 to 1.80), with the health benefits equally to reasonably distributed across groups (G, 0.32; 95% CI: 0.28 to 0.35). Relative to Status-quo, all other strategies reduced BMSM-WMSM and BMSM-LMSM disparities, but none reduced LMSM-WMSM disparities by 2035. Compared to Status-quo, strategy 3 reduced the most both incident infections (% infections averted: overall, 10.2%; BMSM, 32.4%; LMSM, 3.8%; WMSM, 3.5%) and HIV racial inequalities (G reduction, 0.08; 95% CI: 0.02 to 0.14). CONCLUSIONS: Microsimulation models developed with early, continuous stakeholder engagement and inputs yield powerful tools to guide policy implementation.

Healthy for Two/Healthy for You: Design and methods for a pragmatic randomized clinical trial to limit gestational weight gain and prevent obesity in the prenatal care setting.

OBJECTIVE: To compare the effect of Healthy for Two/Healthy for You (H42/H4U), a health coaching program, in prenatal care clinics that serve a racially and economically diverse population, on total gestational weight gain (GWG) (vs. usual care). We hypothesize that compared to usual prenatal care, intervention participants will have lower GWG and lower rates of gestational diabetes mellitus (GDM). METHODS: We report the rationale and design of a pragmatic, parallel arm randomized clinical trial with 380 pregnant patients ≤15 weeks gestation with overweight or obesity from one of 6 academic and community-based obstetrics practices, randomized to either H42/H4U or usual prenatal care in a 1:1 ratio. The study duration is early pregnancy to 6 months postpartum. The primary outcome is total GWG, calculated as the difference between first clinic-assessed pregnancy weight and the weight at 37 weeks gestation. Key maternal and infant secondary outcomes include GDM incidence, weight retention at 6 months postpartum, infant weight, maternal health behaviors and wellness. CONCLUSIONS: This pragmatic clinical trial embeds a pregnancy health coaching program into prenatal care to allow parallel testing compared to usual prenatal care on the outcome of total GWG. The real-world design provides an approach to enhance its sustainability beyond the trial to ultimately improve maternal/child health outcomes and reduce future obesity. TRIAL REGISTRATION: The study was first registered at clinicaltrials.gov on 1/26/21 (NCT04724330).

Where Do We Go From Here? A Framework for Using Susceptible-Infectious-Recovered Models for Policy Making in Emerging Infectious Diseases.

OBJECTIVES: Throughout the coronavirus disease 2019 pandemic, susceptible-infectious-recovered (SIR) modeling has been the preeminent modeling method to inform policy making worldwide. Nevertheless, the usefulness of such models has been subject to controversy. An evolution in the epidemiological modeling field is urgently needed, beginning with an agreed-upon set of modeling standards for policy recommendations. The objective of this article is to propose a set of modeling standards to support policy decision making. METHODS: We identify and describe 5 broad standards: transparency, heterogeneity, calibration and validation, cost-benefit analysis, and model obsolescence and recalibration. We give methodological recommendations and provide examples in the literature that employ these standards well. We also develop and demonstrate a modeling practices checklist using existing coronavirus disease 2019 literature that can be employed by readers, authors, and reviewers to evaluate and compare policy modeling literature along our formulated standards. RESULTS: We graded 16 articles using our checklist. On average, the articles met 6.81 of our 19 categories (36.7%). No articles contained any cost-benefit analyses and few were adequately transparent. CONCLUSIONS: There is significant room for improvement in modeling pandemic policy. Issues often arise from a lack of transparency, poor modeling assumptions, lack of a system-wide perspective in modeling, and lack of flexibility in the academic system to rapidly iterate modeling as new information becomes available. In anticipation of future challenges, we encourage the modeling community at large to contribute toward the refinement and consensus of a shared set of standards for infectious disease policy modeling.

On All Accounts: Cost-Effectiveness Analysis of Limited Preoperative Optimization Efforts Before Colon Cancer Surgery.

BACKGROUND: Reports suggest that preoperative optimization of a patient's serious comorbidities is associated with a reduction in postoperative complications. OBJECTIVE: The purpose of this study was to assess the cost and benefits of preoperative optimization, accounting for total costs associated with postoperative morbidity. DESIGN: This study is a decision tree cost-effectiveness analysis with probabilistic sensitivity analysis (10,000 iterations). SETTING: This is a hypothetical scenario of stage II colon cancer surgery. PATIENT: The simulated 65-year-old patient has left-sided, stage II colon cancer. INTERVENTION: Focused preoperative optimization targets high-risk comorbidities. OUTCOMES: Total discounted (3%) economic costs (US $2018), effectiveness (quality-adjusted life-years), incremental cost-effectiveness ratio (incremental cost-effectiveness ratio, cost/quality-adjusted life-years gained), and net monetary benefit. RESULTS: We calculated the per individual expected health care sector total cost of preoperative optimization and sequelae to be $12,395 versus $15,638 in those not optimized (net monetary benefit: $1.04 million versus $1.05 million). A nonoptimized patient attained an average 0.02 quality-adjusted life-years less than one optimized. Thus, preoperative optimization was the dominant strategy (lower total costs; higher quality-adjusted life-years). Probabilistic sensitivity analysis demonstrated 100% of simulations favoring preoperative optimization. The breakeven cost of optimization to remain cost-effective was $6421 per patient. LIMITATIONS: Generalizability must account for the lack of standardization among existing preoperative optimization efforts, and decision analysis methodology provides guidance for the average patient or general population, and is not patient-specific. CONCLUSIONS: Although currently not comprehensively reimbursed, focused preoperative optimization may reduce total costs of care while also reducing complications from colon cancer surgery. See Video Abstract at http://links.lww.com/DCR/B494. EN TODO CASO ANLISIS DE RENTABILIDAD DE LOS ESFUERZOS LIMITADOS DE OPTIMIZACIN PREOPERATORIA ANTES DE LA CIRUGA DE CNCER DE COLON: ANTECEDENTES:Los informes sugieren que la optimización preoperatoria de las comorbilidades graves de un paciente se asocia con una reducción de las complicaciones postoperatorias.OBJETIVO:El propósito de este estudio fue evaluar el costo y los beneficios de la optimización preoperatoria, teniendo en cuenta los costos totales asociados con la morbilidad postoperatoria.DISEÑO:Análisis de costo-efectividad de árbol de decisión con análisis de sensibilidad probabilístico (10,000 iteraciones).AJUSTE ENTORNO CLINICO:Escenario hipotético Cirugía de cáncer de colon en estadio II.PACIENTE:Paciente simulado de 65 años con cáncer de colon en estadio II del lado izquierdo.INTERVENCIÓN:Optimización preoperatoria enfocada dirigida a comorbilidades de alto riesgo.RESULTADOS:Costos económicos totales descontados (3%) (US $ 2018), efectividad (años de vida ajustados por calidad [AVAC]), relación costo-efectividad incremental (ICER, costo / AVAC ganado) y beneficio monetario neto (NMB).RESULTADOS:Calculamos que el costo total esperado por sector de atención médica individual de la optimización preoperatoria y las secuelas es de $ 12,395 versus $ 15,638 en aquellos no optimizados (NMB: $ 1.04 millones versus $ 1.05 millones, respectivamente). Un paciente no optimizado alcanzó un promedio de 0.02 AVAC menos que uno optimizado. Por lo tanto, la optimización preoperatoria fue la estrategia dominante (menores costos totales; mayores AVAC). El análisis de sensibilidad probabilístico demostró que el 100% de las simulaciones favorecían la optimización preoperatoria. El costo de equilibrio de la optimización para seguir siendo rentable fue de $ 6,421 por paciente.LIMITACIONES:La generalización debe tener en cuenta la falta de estandarización entre los esfuerzos de optimización preoperatorios existentes y esa metodología de análisis de decisiones proporciona una guía para el paciente promedio o la población general, no específica del paciente.CONCLUSIONES:Si bien actualmente no se reembolsa de manera integral, la optimización preoperatoria enfocada puede reducir los costos totales de la atención y al mismo tiempo reducir las complicaciones de la cirugía de cáncer de colon. Consulte Video Resumen en http://links.lww.com/DCR/B494.

Patterns and Predictors of Transitions Across Residential Care Settings and Nursing Homes Among Community-Dwelling Older Adults in the United States.

BACKGROUND AND OBJECTIVES: Older adults prefer to age in place, but sociodemographic, health, and socioeconomic factors may influence their decision to remain in the community. Guided by Andersen's behavioral model, we characterize incident transitions out of the community into residential care settings or nursing homes and identify predictors of these transitions. RESEARCH DESIGN AND METHODS: Study participants include 2,725 (weighted n = 13,704,390) community-dwelling U.S. older adults of the National Health and Aging Trends Study from 2011 to 2018. We examined the associations between sociodemographic, socioeconomic, and health factors and the probability of transition using a multinomial logit model. RESULTS: Over the study period, 86.2% of older adults remained in the community, whereas 9.0% and 4.9% transitioned to residential care settings and nursing homes, respectively. Older age, living alone, having functional and cognitive limitations, and hospitalization were associated with increased risk of transitioning to residential care settings or nursing homes from the community. Blacks and Hispanics were less likely to transition to residential care settings or nursing homes. Adults with lower income had a greater risk of transitioning to nursing homes. Medicaid enrollment did not affect the likelihood of transition. DISCUSSION AND IMPLICATIONS: Majority of older adults remained in the community, and incident transition to residential care settings was more common than to nursing homes. Policy should target sociodemographic, health, and socioeconomic factors that enable older adults to age in place. Future work should examine whether these new residential care settings enhance the quality of life or result in subsequent transitions back into the community.

Pharmaceutical Treatment for Alzheimer's Disease and Related Dementias: Utilization and Disparities.

BACKGROUND: Four prescription drugs (donepezil, galantamine, memantine, and rivastigmine) are approved by the US FDA to treat symptoms of Alzheimer's disease (AD). Even modest effectiveness could potentially reduce the population-level burden of AD and related dementias (ADRD), especially for women and racial/ethnic minorities who have higher incidence of ADRD. OBJECTIVE: Describe the prevalence of antidementia drug use and timing of initiation relative to ADRD diagnosis among a nationally representative group of older Americans, and if there are disparities in prevalence and timing by sex and race/ethnicity. METHODS: Descriptive analyses and logistic regressions of Medicare claims (2008-2016) for beneficiaries who had an ADRD or dementia-related symptom diagnosis, or use of an FDA approved drug for AD. We investigate prevalence of use and timing of treatment initiation relative to ADRD diagnosis across time and beneficiary characteristics (age, sex, race/ethnicity, socioeconomic status, comorbidities). RESULTS: Among persons diagnosed with ADRD or related symptoms, 33.3% used an approved drug over the study period. Odds of use was higher among Whites than non-Whites. Among ADRD drug users, 40% initiated use within 6 months of the initial ADRD or related symptoms diagnosis, and 16% initiated prior to a diagnosis. We observed disparities by race/ethnicity: 28% of Asians, 24% of Hispanics, 16% of Blacks, and 15% of Whites initiated prior to diagnosis. CONCLUSIONS: The use of antidementia drugs is relatively low and varies widely by race/ethnicity. Heterogeneity in timing of initiation and use may affect health and cost outcomes, but these effects merit further study.

Incentives Versus Defaults: Cost-Effectiveness of Behavioral Approaches for HIV Screening.

Many HIV positive individuals are still undiagnosed, which has led health systems to try many approaches to expand HIV testing. In a randomized controlled trial, we found that behavioral economics interventions (opt-out testing and financial incentives) each improved HIV testing rates and these approaches are being implemented by several hospital systems. However, it is unclear if these strategies are cost-effective. We quantified the cost-effectiveness of different behavioral approaches to HIV screening-opt-out testing, financial incentives, and their combination-in terms of cost per new HIV diagnosis and infections averted. We estimated the incremental number of new HIV diagnoses and program costs using a mathematical screening model, and infections averted using and HIV transmission model. We used a 1-year time horizon and a hospital perspective. Switching from opt-into opt-out results in 39 additional diagnoses (56% increase) after 1-year at a cost of $3807 per new diagnosis. Switching from no incentive to a $1, $5, or $10 incentive adds 14, 13, and 28 new diagnoses (20, 19, and 41% increases) at a cost of $11,050, $17,984, and $15,298 per new diagnosis, respectively. Layering on financial incentives to opt-out testing enhances program effectiveness, though at a greater marginal cost per diagnosis. We found a similar pattern for infections averted. This is one of the first cost-effectiveness analyses of behavioral economics interventions in public health. Changing the choice architecture from opt-into opt-out and giving financial incentives for testing are both cost-effective in terms of detecting HIV and reducing transmission. For hospitals interested in increasing HIV screening rates, changing the choice architecture is an efficient strategy and more efficient than incentives.

Performance of Matching Methods as Compared With Unmatched Ordinary Least Squares Regression Under Constant Effects.

Matching methods are assumed to reduce the likelihood of a biased inference compared with ordinary least squares (OLS) regression. Using simulations, we compared inferences from propensity score matching, coarsened exact matching, and unmatched covariate-adjusted OLS regression to identify which methods, in which scenarios, produced unbiased inferences at the expected type I error rate of 5%. We simulated multiple data sets and systematically varied common support, discontinuities in the exposure and/or outcome, exposure prevalence, and analytical model misspecification. Matching inferences were often biased in comparison with OLS, particularly when common support was poor; when analysis models were correctly specified and common support was poor, the type I error rate was 1.6% for propensity score matching (statistically inefficient), 18.2% for coarsened exact matching (high), and 4.8% for OLS (expected). Our results suggest that when estimates from matching and OLS are similar (i.e., confidence intervals overlap), OLS inferences are unbiased more often than matching inferences; however, when estimates from matching and OLS are dissimilar (i.e., confidence intervals do not overlap), matching inferences are unbiased more often than OLS inferences. This empirical "rule of thumb" may help applied researchers identify situations in which OLS inferences may be unbiased as compared with matching inferences.

Preventing, Identifying, and Treating Prescription Drug Misuse Among Active-Duty Service Members.

Prescription drug misuse (PDM) is of critical concern for the military because of its potential impact on military readiness, the health and well-being of military personnel, and associated health care costs. The purpose of this study is to summarize insights gleaned from a series of activities that the RAND Corporation undertook for the Deputy Assistant Secretary of Defense for Readiness to address this important health and military readiness issue. The authors completed a review of U.S. Department of Defense policies and a comprehensive literature review of clinical guidelines and the empirical literature on the prevention and treatment of PDM and conducted individual face-to-face interviews with 66 health and behavioral health care providers at nine medical treatment facilities across three regions within the contiguous United States to identify best practices in the prevention, identification, and treatment of PDM and the extent to which those practices are known and followed. The study also presents the framework of an analytic tool that, once informed by data available to the military but not available to the authors, can assist the military in predicting future trends in PDM based on current demographics of active-duty service members and rates of injury and prescribing of prescription drugs. The findings from this work led the authors to formulate a set of key insights that they believe might improve the rapid identification and treatment of service members dealing with PDM, thereby improving future force readiness.

A Cost-effectiveness Analysis of Preexposure Prophylaxis for the Prevention of HIV Among Los Angeles County Men Who Have Sex With Men.

BACKGROUND: Substantial gaps remain in understanding the trade-offs between the costs and benefits of choosing alternative human immunodeficiency virus (HIV) prevention strategies, including test-and-treat (expanded HIV testing combined with immediate treatment) and PrEP (initiation of preexposure prophylaxis by high-risk uninfected individuals) strategies. METHODS: We develop a mathematical epidemiological model to simulate HIV incidence among men residing in Los Angeles County, California, aged 15-65 years, who have sex with men. We combine these incidence data with an economic model to estimate the discounted cost, effectiveness (quality-adjusted life-years [QALYs]), and incremental cost-effectiveness ratios of various HIV prevention strategies using a societal perspective and a lifetime horizon. RESULTS: PrEP and test-and-treat yield the largest reductions in HIV incidence, and are highly cost-effective ($27 863/QALY and $19 302/QALY, respectively) relative to status quo and at a US willingness-to-pay threshold of $150 000/QALY saved. Status quo and 12 test-and-treat and PrEP strategies determine the frontier for efficient decisions. More aggressive strategies are costlier, but more effective, albeit with diminishing returns. The relative effectiveness of PrEP is sensitive to the initial HIV prevalence rate, PrEP and antiretroviral therapy (ART) adherence and initiation rates, the probabilities of HIV transmission, and the rates of sexual partner mixing. CONCLUSIONS: PrEP and test-and-treat offer cost-effective alternatives to the status quo. The success of these strategies depends on ART and PrEP adherence and initiation rates. The lack of evidence on adherence behaviors toward PrEP, therefore, warrants further studies.