Community Health Alliance

There has been a rise in state policies targeting the rights of lesbian, gay, bisexual, transgender, queer, intersex, asexual, and other sexual and gender minority (LGBTQIA+) people in the United States. Although large-scale studies have quantified associations between these policies and LGBTQIA+ people's mental health, less research has centered the first-hand accounts of LGBTQIA+ people. To examine LGBTQIA+ people's accounts of how they perceive these policies to be impacting their mental health. From July to October 2024, 1-hour, semistructured, virtual interviews were conducted with LGBTQIA+ adults living in states that had recently proposed or enacted state LGBTQIA+-targeted policies. The state policies included: (1) gender-affirming care restrictions; (2) sports bans for transgender and nonbinary (TNB) people; (3) public bathroom bans for TNB people; (4) school restrictions of sexual orientation and/or gender identity discussions; and (5) religious exemptions, which permit individuals and service organizations to withhold services from LGBTQIA+ people for religious reasons. Transcripts were analyzed using thematic analysis, focusing on participants' perceptions of the mental health impacts of these policies. Interviews with the 61 adult participants in the sample (median [IQR] age, 35 [30-48] years; 13 cisgender men [21.3%], 19 cisgender women [31.1%], 16 nonbinary people [26.2%], 8 transgender men [13.1%], 2 transgender women [3.3%], and 3 people with another gender identity [4.9%]) revealed that LGBTQIA+ people perceive these policies to negatively impact their mental health. These perceived impacts were organized into 3 themes: (1) chronic worry and hypervigilance, (2) social isolation, and (3) hopelessness and powerlessness. A fourth cross-cutting theme was also identified: participants perceived these policies' mental health impacts to be unequal and more pronounced for those most frequently targeted by these policies (eg, youths, TNB people), racially and ethnically minoritized people, those without social and financial resources, and those living in rural areas. In this qualitative study, LGBTQIA+ adults in the United States perceived LGBTQIA+-targeted policies to have profound and unequal impacts on their mental health. As LGBTQIA+-targeted policies increase in number, multilevel resources and supports are necessary to support LGBTQIA+ people's well-being.

Background Pharmacist role expansion, including pharmacist prescribing, is increasing globally. Assessing the impact of such role expansion is vital. Purpose To identify key outcomes to evaluate pharmacist prescribing within Ireland's planned Common Conditions Service (CCS) and independent pharmacist prescribing contexts, and determine their measurability using existing health data sources. Methods In a three-round Delphi study, an expert panel (including pharmacists, pharmacy technicians, prescribers, public/patient contributors, policymakers, academics) rated the importance of outcomes, pre-identified via a rapid overview of reviews, using Likert scales. The research team involved public/patient team members throughout the study. Outcomes reaching consensus for inclusion (rated by ≥75% as critically important) or exclusion (<25%) after the second round were not re-rated. In the third round, remaining outcomes were re-rated and experts also rated the feasibility of measuring each outcome using existing health data sources. Results Thirty experts completed all rounds. For CCS, seven outcomes reached consensus as critically important: Patient experience and satisfaction, Access to care, Guideline concordance, Symptom improvement, or clinical cure, Re-consultation with other health care providers, Cost of care to the healthcare system, and Referral to other healthcare providers. For other independent prescribing contexts, ten outcomes were critically important, including Mortality, Clinical effectiveness, Adverse events, and Cost of care to patients. Important CCS outcomes varied in their measurability using existing data, with Prescribing rate (76% agreement) and Cost to patients (64% agreement) were most feasible. Conclusions This study identified priority outcomes for evaluating the impact of pharmacist prescribing, encompassing clinical, safety, economic, and patient perspectives.

Abstract The variability in responses generated by Large Language Models (LLMs) like OpenAI’s GPT-4 poses challenges in ensuring consistent accuracy on medical knowledge assessments, such as the United States Medical Licensing Exam (USMLE). This study introduces a novel multi-agent framework—referred to as a "Council of AIs"—to enhance LLM performance through collaborative decision-making. The Council consists of multiple GPT-4 instances that iteratively discuss and reach consensus on answers facilitated by a designated "Facilitator AI." This methodology was applied to 325 USMLE questions across Step 1, Step 2 Clinical Knowledge (CK), and Step 3 exams. The Council achieved consensus responses that were correct 97%, 93%, and 94% of the time for Step 1, Step 2CK, and Step 3, respectively, outperforming single-instance GPT-4 models. In cases where there wasn’t an initial unanimous response, the Council of AI deliberations achieved a consensus that was the correct answer 83% of the time. For questions that required deliberation, the Council corrected over half (53%) of responses that majority vote had gotten incorrect. At the end of deliberation, the Council often corrected majority responses that were initially incorrect: the odds of a majority voting response changing from incorrect to correct were 5 (95% CI: 1.1, 22.8) times higher than the odds of changing from correct to incorrect after discussion. We additionally characterized the semantic entropy of the response space for each question and found that deliberations impact entropy of the response space and steadily decrease it, consistently reaching an entropy of zero in all instances. This study showed that in a Council model response variability—often viewed as a limitation—could be leveraged as a strength, enabling adaptive reasoning and collaborative refinement of answers. These findings suggest new paradigms for AI implementation and reveal diversity of responses as a strength in collective decision-making even in medical question scenarios where there is a single correct response.Author SummaryIn our study, we explored how collaboration among multiple artificial intelligence (AI) systems could improve accuracy on medical licensing exams. While individual AI models like GPT-4 often produce varying answers to the same question—a challenge known as "response variability"—we designed a "Council of AIs" to turn this variability into a strength. The Council consists of several AI models working together, discussing their answers through an iterative process until they reach consensus.When tested on 325 medical exam questions, the Council achieved 97%, 93%, and 94% accuracy on the Step 1, Step 2CK, and Step 3, respectively. This improvement was most notable when answers required debate: in cases where initial responses disagreed, the collaborative process corrected errors 83% of the time. Our findings suggest that collective decision-making— even among AIs—can enhance accuracy and AI collaboration can potentially lead to more trustworthy tools for healthcare, where accuracy is critical. By demonstrating that diverse AI perspectives can refine answers, we challenge the notion that consistency alone defines a "good" AI. Instead, embracing variability through teamwork might unlock new possibilities for AI in medicine and beyond. This approach could inspire future systems where AIs and humans collaborate (e.g. on Councils with both humans and AIs), combining strengths to solve complex problems. While technical challenges remain, our work highlights a promising path toward more robust, adaptable AI solutions.

Introduction/Objectives:Since 2015, the rise in e-cigarette use among youth has concerned public health authorities. After peaking in 2019, usage rates have declined but remain high. In 2023, 10% of high school and 4.6% of middle school students reported current use. This report describes the implementation and evaluation of a school-based e-cigarette prevention program, CATCH My Breath (CMB), in 8 central Appalachian counties. These counties have some of the highest rates of tobacco use, poor health, and premature death in the United States.Methods:A total of 6217 students across 25 middle and high schools in West Virginia and Kentucky received the CMB program from 2019 to 2023. Lists of participating counties, schools, and teachers were maintained on a rolling basis over the 4 years of the project. Program reach and impact on e-cigarette knowledge and use are reported. Thirteen-item pre- and post-tests were completed electronically by students before and after each course delivery. Questions assessed knowledge about e-cigarettes, current (past 30-day) e-cigarette use, and interest in future use.Results:From 2019 to 2023, there were 9399 deliveries of the 4-session CMB course, primarily to middle school students. Approximately 84% reported being less likely to use e-cigarettes following the program. Significant improvements in e-cigarette knowledge and beliefs on 5 of 8 items were observed, including a significant increase in knowledge composite score (4.15-4.75, P < .001). From pre- to post-test, declines in current e-cigarette use (5.1% to 4.4%; P = .005) and peer influence (4.9% to 4.0%; P = .025) were also observed.Conclusions:CMB was feasible, effective, and well-received in a convenience sample of central Appalachian counties and schools. This curriculum, combined with other policy initiatives, offers hope for curbing the growing epidemic of youth e-cigarette use and nicotine dependence. The success of this project contributed to a decision by the West Virginia Bureau for Public Health and the West Virginia Department of Education to launch a joint effort to bring CMB to middle schools in all 55 counties during the next 3 school years of 2023-2026.

There is increasing recognition of the crucial need for robust community engagement in health research and clinical trials. Despite this awareness, challenges persist in bridging the gap between researchers and communities. Much of the current discourse focuses on addressing issues such as cultural humility and equitable partnerships. To expand this conversation, we conducted community engagement studios, following the model by Joosten et al. We wanted to gather perspectives on research involvement across New Mexico. This process and resultant findings offer valuable insights into effective community engagement practices and advance clinical and translational science by amplifying community voices and needs.

The evidence base supports effectiveness of dental sealants for prevention of childhood caries in school-aged children. This study describes planning, development, usability testing and outcomes following implementation of DentaSeal, a web-based application designed to accurately track unique student data and generate reports for all Wisconsin school-based sealant placement (SP) programs. Application software development was informed by a steering committee of representative stakeholders who were interviewed to inform design and provide feedback for design of DentaSeal during development and evaluation. Software development proceeded based on wireframes developed to build architectural design. Usability testing followed and informed any required adjustments to the application. The DentaSeal prototype was beta tested and fully implemented subsequently in the public health sector. The DentaSeal application demonstrated capacity to: 1) track unique student SP data and longitudinal encounter history, 2) generate reports and 3) support administrative tracking. In 2019, DentaSeal captured SP data of 47 school-based programs in Wisconsin that sponsored > 7,000 program visits for 184,000 children from 62 counties. Delivery of > 548,000 SP services were catalogued. For public health initiatives targeting reduction in caries incidence, web-based applications such as DentaSeal represent useful longitudinal tracking tools for cataloguing SP in school-based program participants.

Polypharmacy is common among the elderly and can predispose them to increased morbidity and higher healthcare expenditures. Deprescribing is an important aspect of preventative medicine to minimize polypharmacy-related adverse effects. Mid-Michigan has historically been considered a medically underserved area. We sought to describe polypharmacy prevalence and primary care provider (PCP) perceptions of deprescribing in the elderly at community practices in the region. Medicare Part D claims data from 2018 to 2020 were queried to calculate the prevalence of polypharmacy, which is defined as Medicare beneficiaries who were concurrently prescribed at least five medications. PCPs from four community practices in adjacent counties in mid-Michigan, including two high- and two low-prescribing practices, were surveyed to assess their perceptions of deprescribing. The prevalence of polypharmacy in two adjacent mid-Michigan counties was 44.0% and 42.5%, which was similar to Michigan's overall prevalence of 40.7% (p = 0.720 and 0.844, respectively). Additionally, 27 survey responses were received from mid-Michigan PCPs (response rate, 30.7%). Most respondents expressed confidence in deprescribing in the elderly from a clinical standpoint (66.7%). Barriers to deprescribing included patient/family concerns (70.4%) and lack of time during office visits (37.0%). Facilitators to deprescribing included patient readiness (18.5%), collaboration with case managers/pharmacists (18.5%), and up-to-date medication lists (18.5%). An exploratory comparison of perceptions at high- and low-prescribing practices showed no significant differences. These findings demonstrate a high prevalence of polypharmacy in mid-Michigan and suggest that PCPs in the region are generally supportive of deprescribing. Potential targets to improve deprescribing in patients with polypharmacy include addressing visit length, patient/family concerns, increasing interdisciplinary collaboration, and medication reconciliation support.

IntroductionAs of July 2022, a little over one-third of Guatemalans were fully vaccinated. While COVID-19 vaccination rates are not officially reported nationally by racial/ethnic groups, non-governmental organisations and reporters have observed that COVID-19 vaccination rates are especially low among high-risk Indigenous populations. We conducted one of the first studies on COVID-19 vaccine acceptance in Indigenous populations in the Central Highlands of Guatemala, which aimed to better understand the barriers to COVID-19 vaccine uptake and how to improve vaccine promotional campaigns.MethodsIn November 2021, we conducted eight focus group discussions (FGDs) with 42 Indigenous men and women and 16 in-depth interviews (IDIs) with community health workers, nurses and physicians in Chimaltenango and Sololá. Using a participatory design approach, our qualitative analysis used constant comparative methods to understand the inductive and deductive themes from the FGD and IDI transcripts.ResultsWe found three major overarching barriers to vaccination within the sampled population: (1) a lack of available easily understandable, linguistically appropriate and culturally sensitive COVID-19 vaccine information; (2) vaccine access and supply issues that prevented people from being vaccinated efficiently and quickly; and (3) widespread misinformation and disinformation that prey on people’s fears of the unknown and mistrust of the medical establishment and government.ConclusionWhen developing COVID-19 vaccine messages, content should be culturally relevant, appropriate for low-literacy populations and in the languages that people prefer to speak. Promotional materials should be in multiple modalities (print, radio and social media) and also have specific Maya cultural references (dress, food and concepts of disease) to ensure messaging connects with intended targets. This study supports the need for more robust research into best practices for communicating about COVID-19 vaccines to marginalised communities globally and suggests that policy makers should invest in targeted local solutions to increase vaccine uptake.