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Financial exploitation (FE) is one of the most common reports to Adult Protective Services (APS) and the cases are often complex. Consequently, APS caseworkers report FE investigations to be among the most difficult while simultaneously reporting low confidence in productive outcomes for these investigations. This necessitates finding ways to support APS FE investigations. This paper describes the structure, process, and formative findings of a collaboration between forensic accounting examiners and APS workers to investigate complex cases of FE. Among the 77 FE cases completed, forensic examiners reviewed multiple years of financial records which included over 101,000 transactions, totaling over $213,000,000.00 in finances, and identified over $8,000,000 in questionable activity. Scores on the 8-item Client Satisfaction Questionnaire were high indicating high program satisfaction by APS workers, subject matter experts, and forensic examiners. These findings support the feasibility and acceptability of forensic accounting and APS collaborations to investigate complex cases of FE. [ABSTRACT FROM AUTHOR]

Objectives. To demonstrate the spatially uneven effects of abortion restriction laws in Texas. Methods. We used network analysis to determine the change in distance to the nearest surgical abortion provider for 5253 Texas neighborhoods after the passing of Texas Senate Bill 8 (SB8; 2021) and the US Supreme Court's Dobbs v Jackson Women's Health Organization (2022) decision. We identified associations between key measures of neighborhood socioeconomic context and change in distance to providers using multivariable linear regression models. Results. After the Dobbs decision, Texas residents experienced an average change in distance to the nearest provider of 457 miles (SD = 179). Neighborhoods of concentrated disadvantage experienced the greatest increase in distance to abortion providers after SB8's passing, and neighborhoods with high levels of income inequality experienced the greatest increase in distance after the Dobbs decision. Conclusions. We document the rapidly changing abortion landscape in a highly restrictive state and show that women living in more disadvantaged and unequal areas are most affected by the increasing distance to providers. Public Health Implications. Our methods and findings will continue to be relevant in understanding the burden placed on women in areas where medical abortion has been restricted because of the Dobbs decision. (Am J Public Health. 2024;114(10):1024–1033. https://doi.org/10.2105/AJPH.2024.307652) [ABSTRACT FROM AUTHOR]

Purpose: The Joint Committee on Infant Hearing recommends hearing screening before 1 month of age, audiologic diagnosis before 3 months of age, and enrollment in early intervention before 6 months of age (1-3-6 benchmarks of Early Hearing Detection and Intervention [EHDI] programs). Nearly 98% of newborns have their hearing screened, but many, who do not pass or do not complete their newborn hearing screening, fail to complete the EHDI process. Historically, lower socioeconomic level, more complex infant health status, and farther geographical location reduce rates of EHDI follow-up, but levels vary widely across states. This study examined barriers to the EHDI process by comparing census-based variables at the state and regional levels to national and Texas EHDI outcomes, respectively. Method: We used correlational analysis to assess relationships between U.S. Census data (state- and region-specific population and geographic characteristics, sociodemographic and geographic factors, and health and health insurance) and EHDI data (newborn screening, audiologic diagnosis, and early intervention) at the national level and in Texas. Results: Nationally, higher labor force participation, lower unemployment rates, and presence of health insurance significantly correlated with higher rates of completing EHDI benchmarks. Larger population size and density and higher socioeconomic factors coincided with higher rates of completing the EHDI process and lower rates of loss to follow-up (LTF) or loss to documentation in Texas. Conclusions: Population, socioeconomic, and demographic factors significantly correlate with following through with the EHDI process, with weak correlations at the national level and strong correlations at the state level. These findings underscore the need to increase our attention to underserved, economically challenged, and/or geographically distanced families who have children with a higher risk of becoming LTF in the EHDI process. [ABSTRACT FROM AUTHOR]

Background: Disparities in birth outcomes continue to exist in the United States, particularly for low-income, publicly insured women. Doula support has been shown to be a cost-effective intervention in predominantly middle-to-upper income White populations, and across all publicly insured women at the state level. This analysis extends previous studies by providing an estimate of benefits that incorporates variations in averted outcomes by race and ethnicity in the context of one region in Texas. The objectives of this study were to determine (1) whether the financial value of benefits provided by doula support exceeds the costs of delivering it; (2) whether the cost-benefit ratio differs by race and ethnicity; and (3) how different doula reimbursement levels affect the cost-benefit results with respect to pregnant people covered by Medicaid in central Texas., Methods: We conducted a forward-looking cost-benefit analysis using secondary data carried out over a short-term time horizon taking a public payer perspective. We focused on a narrow set of health outcomes (preterm delivery and cesarean delivery) that was relatively straightforward to monetize. The current, usual care state was used as the comparison condition., Results: Providing pregnant people covered by Texas Medicaid with access to doulas during their pregnancies was cost-beneficial (benefit-to-cost ratio: 1.15) in the base model, and 65.7% of the time in probabilistic sensitivity analyses covering a feasible range of parameters. The intervention is most cost-beneficial for Black women. Reimbursing doulas at $869 per client or more yielded costs that were greater than benefits, holding other parameters constant., Conclusions: Expanding Medicaid pregnancy-related coverage to include doula services would be cost-beneficial and improve health equity in Texas., (© 2023 Wiley Periodicals LLC.)

Public health spatial data are often recorded at different spatial scales (or geographic regions/divisions) and over different correlated variables. Motivated by data from the Dartmouth Atlas Project, we consider jointly analyzing average annual percentages of diabetic Medicare enrollees who have taken the hemoglobin A1c and blood lipid tests, observed at the hospital service area (HSA) and county levels, respectively. Capitalizing on bivariate relationships between these two scales is not immediate as counties are not nested within HSAs. It is well known that one can improve predictions by leveraging correlations across both variables and scales. There are very few methods available that simultaneously model multivariate and multiscale correlations. We propose three new hierarchical Bayesian models for bivariate multiscale spatial data, extending spatial random effects, multivariate conditional autoregressive (MCAR), and ordered hierarchical models through a multiscale spatial approach. We simulated data from each of the three models and compared the corresponding predictions, and found the computationally intensive multiscale MCAR model is more robust to model misspecification. In an analysis of 2015 Texas Dartmouth Atlas Project data, we produced finer resolution predictions (partitioning of HSAs and counties) than univariate analyses, determined that the novel multiscale MCAR and OH models were preferable via out-of-sample metrics, and determined the HSA with the highest within-HSA variability of hemoglobin A1c blood testing. Additionally, we compare the univariate multiscale models to the bivariate multiscale models and see clear improvements in prediction over univariate analyses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: This study examined daily associations between alcohol use, cannabis use, and simultaneous alcohol and cannabis/marijuana (SAM) use with the likelihood of hooking up (uncommitted sexual encounter that may or may not include intercourse)., Method: We used a longitudinal measurement burst ecological momentary assessment (EMA) design with 3-week EMA bursts with daily measurements repeated quarterly across 12 months. 1,009 (57 % female, Mean age = 20.00 [SD = 3.21]) Texan adolescents and young adults ages 15-25 participated in the study. Mixed effects logistic regression models were estimated using maximum likelihood estimation to evaluate the associations between substance use and hooking up., Results: Within-person results indicated that participants were more likely to hook up on days with alcohol use and on days with cannabis use, but not on days with SAM use. Participants were also more likely to hook up on drinking days with higher-than-usual alcohol use. Between-person results indicated that participants who used alcohol more often or cannabis more often on average were more likely to hook up, and participants who tended to drink more on drinking days were more likely to hook up., Conclusions: Given the significant daily-level associations between alcohol and cannabis use and hooking up behavior, public health initiatives should focus on developing interventions to reduce alcohol and cannabis use and promote safer hooking up behavior among adolescents and young adults., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)