The wellbeing of healthcare workers is increasingly recognized as foundational to high-quality care and sustainable health systems. While various leadership frameworks promote wellbeing, there remains a gap in system-wide strategies that integrate equity, psychological safety and health promotion into leadership practice. This paper aims to address that gap by adapting the Okanagan Charter, originally developed for health-promoting universities, into a novel framework for health-promoting leadership in healthcare. This conceptual paper reinterprets the principles of the Okanagan Charter through the lens of inclusive, distributed and compassionate leadership. The authors adapt an established six-domain model to the health leadership context: embed health in all policies, adapt spaces to promote wellbeing, create thriving communities and cultures, support meaningful personal and professional development, promote engagement with health services and collaborate in continuous improvement and evaluation. For each domain, they provide theoretical rationale, leadership strategies and practice-based illustrations. This paper critically examines the applicability of the Okanagan Charter within healthcare leadership, highlights practical implementation challenges and presents a revised leadership case study grounded in real-world complexity. The findings demonstrate the utility of the six-domain model in guiding leaders to embed wellbeing into everyday practice. This paper advances existing scholarship by explicitly extending Okanagan Charter-aligned work into the domain of healthcare leadership. It offers a clear, theory-informed roadmap for leaders to integrate wellbeing, equity and health promotion into the fabric of organizational life, positioning health-promoting leadership as a strategic imperative for resilient, inclusive and high-performing health systems.

Global Health Equity is increasingly threatened by interconnected global crises that expose systemic inequities in health systems, global health governance and evidence infrastructures. Global Collaborative Evidence Networks have emerged as mechanisms for mobilising knowledge, fostering interdisciplinary collaboration, and supporting decision-making across diverse contexts to address Global Health Equity. However, their potential is constrained by persistent challenges related to governance, inclusion, and power asymmetries. This review critically examines the conceptual, structural, and governance dimensions of Global Collaborative Evidence Networks to assess their potential and limitations in advancing Global Health Equity. A narrative literature review was conducted in July 2024, searching PubMed, Scopus, Web of Science, Embase, CINAHL, and grey literature sources. A thematic analysis of 162 included studies was conducted using Braun and Clarke's reflexive approach to identify themes and sub-themes. The review found that while Global Health Equity has emerged as a key normative framework shaped by historical, political, and socio-economic structures, its operationalisation remains fragmented, particularly in global governance and research systems. Global Collaborative Evidence Networks, positioned as vehicles to advance Global Health Equity, demonstrate considerable potential yet often reproduce entrenched power asymmetries. Substantial gaps remain in how equity, diversity, and inclusion are conceptualised and operationalised within these networks. Although many promote shared purpose and trust-based collaboration, participation and influence often concentrated in high-income institutions, reinforcing systemic and resource asymmetries. Key tensions, such as between efficiency and inclusiveness, unity and diversity, and centralisation and decentralisation, shape governance dynamics and impact who benefits from network participation. Despite the proliferation of equity-focused frameworks in global health partnerships, none have been adapted for networks, and accountability mechanisms remain weak. Theoretical perspectives from network typologies and governance modes offer valuable perspectives but require integration with intersectional and decolonial approaches to address persistent power imbalances. Global Collaborative Evidence Networks are a powerful mechanism for supporting and strengthening evidence-based decision-making to address global health inequities. However, they risk replicating existing inequities without deliberate, equity-centred governance. This review calls for the development of empirically grounded, context-sensitive frameworks to guide the equitable, diverse and inclusive design, evaluation, and governance of Global Collaborative Evidence Networks.

Integrating HIV clinical records with population-based surveillance data allows the study of health care seeking behaviours, access to care, and predictors of patient outcomes. We implemented a graph-based record linkage algorithm to deduplicate and link HIV clinical and population-based surveillance records in an HIV-endemic setting in rural South Africa. We linked four data sources to create the Africa Health Research Institute (AHRI) Unified Data Platform: AHRI's Health and Demographic Surveillance System (HDSS), AHRI Clinic and Hospital Information System (AHRILink), National Health Laboratory Service (NHLS), and Three Integrated Electronic Registers (TIER.Net) HIV care and treatment records. HDSS data were collected between January 1, 2000, and July 31, 2024, through repeated household surveys of over 140,000 individuals. Clinical and laboratory data were obtained for one hospital and 17 clinics in Hlabisa, KwaZulu-Natal, covering the HDSS surveillance area. We implemented a probabilistic record linkage algorithm trained and validated on a subset of records with national identity numbers. We assessed linkage accuracy, computed descriptive statistics for the linked database, and estimated the HIV care cascade for this population. A total of 986,832 records were successfully linked across the four databases, achieving a sensitivity of 92.7% and a positive predictive value of 96.5% (F-score=0.95). The average number of records (standard deviation (SD)) in TIER.Net, HDSS, AHRILink and NHLS were 1.18 (0.44),1.05 (0.23),1.13 (0.40), and 5.21 (4.24), respectively. The linked data indicated that 12,293 HDSS resident adults (≥15 years) were living with HIV at some point during the 2022 and 2024 surveillance rounds. Of these, 10,622 (86.4%) had ever sought HIV care in the public sector, of whom 10,492 (98.8%) had ever started ART and 7,065 (66.5%) were currently on ART, of whom 6,301 (89.2%) were virally suppressed(viral load<200 copies/mL). HIV care and population surveillance records from four data sources were deduplicated and linked with high accuracy, revealing persistent gaps in retention in care and viral suppression in an HIV-endemic region in rural South Africa. The AHRI Unified Data Platform offers the potential to deepen our understanding of HIV epidemiology in a well-described population and to improve services for HIV. Not applicable.

Inflammatory bowel diseases (IBD), mainly represented by Crohn's disease and ulcerative colitis, have a multifactorial etiology and a growing incidence in developing countries. In Brazil, studies on their occurrence and relationship with social conditions remain scarce, which reinforces the importance of updated epidemiological analyses. Ecological study using secondary data on hospital admissions extracted from the Hospital Information System of the Brazilian Unified Health System (SIH/SUS). Population data were obtained from the Brazilian Institute of Geography and Statistics (IBGE), and socioeconomic indicators (HDI-M, SVI, and Gini Index) from the Institute for Applied Economic Research (IPEA). Incidence rates were age-standardized according to the WHO world standard population. For time trend analysis, Prais-Winsten linear regression was applied, and to assess relationships with socioeconomic variables, linear regression analysis was used. The statistical software employed was Stata version 18.0. Between 2010 and 2023, there were 64,303 hospital admissions for IBD in Brazil. The highest frequency was observed among women, adults aged 20 to 59 years, and in the Southeast region, while the lowest occurred in the North region. Regarding incidence, there was a significant increase among men, individuals under 19 years old, adults aged 20 to 59 years, and in the Northeast and Southeast regions. Nationally, an annual growth of 2% in incidence was observed. No significant associations were found with socioeconomic indicators, but regional analyses revealed important relationships with HDI-M and SVI. The results demonstrate an increase in hospital admissions for IBD in Brazil, particularly among younger groups and in specific regions, indicating changes in the epidemiological profile. These findings highlight the need for public policies focused on early diagnosis, equitable access to specialized services, and the strengthening of epidemiological surveillance. Future research should explore environmental, nutritional, and social factors that may influence the occurrence and progression of IBD.

Hospital pharmacists play a pivotal role in ensuring the safe and effective use of medications, thereby supporting the quality of care and the resilience of health systems. Identifying the factors influencing turnover intention among hospital pharmacists and implementing strategies to maintain an appropriate talent pool can contribute to strengthening public health and improving patient outcomes. This study aimed to identify the factors influencing turnover intention among hospital pharmacists in South Korea and provide implications for strategies to support pharmacist retention. A cross-sectional survey was conducted in July 2024 with 592 full-time pharmacists employed in tertiary and general hospitals using proportional stratified sampling by hospital type and region, representing 16.0% of the pharmacists working in these hospitals. The questionnaire incorporated items from Mitchell's Job Embeddedness theory, the Korean Occupational Stress Scale, and Singh's turnover intention scale, and underwent expert content validation and exploratory factor analysis. Multivariable linear and logistic regression analyses were performed to determine the factors associated with turnover intention after adjusting for key demographic and institutional characteristics. Among the 592 respondents, 255 (43.1%) had high turnover intention, with shorter employment durations associated with higher turnover intention scores. Within job embeddedness, factors significantly reducing turnover intention included fit to organization_task, organization-related sacrifice_direct, link to organization_task, and link to community_transverse. Within job stress, the factors that significantly increased turnover intention were lack of rewards, job demand_density, and organizational system_fairness. The identified associations were consistent across both linear and logistic regression models, supporting the robustness of the findings. To retain skilled professionals, hospitals should improve their reward structures, foster a culture of fairness, and provide targeted support to junior pharmacists. Improving role fit in task assignments may help reduce turnover risk and enhance workforce stability.

Nearly two thirds of Australian adults are estimated to use complementary therapies, including 36% who consult with such providers. Despite this relatively high use, traditional and complementary medicine (T&CM) providers and mainstream practitioners rarely collaborate. The World Health Organization (WHO) advocates for the integration of T&CM, as appropriate, towards strengthening universal health coverage and people-centred health care. This study explored the perspectives of primary care providers on greater integration of T&CM with Australia's healthcare system. Guided by a health policy and systems research approach, this qualitative study used purposive and convenience sampling to recruit general practitioners, registrars, and practice nurses. Semi-structured, in-depth interviews were thematically analysed using a hybrid inductive/deductive approach. The four main themes arising from the 13 interviewees were: (i) exposure to T&CM; (ii) perception of safety; (iii) priorities of the healthcare system; and (iv) acceptability. Participants had varying levels of knowledge about T&CM, which influenced attitudes towards T&CM integration. Participants were generally supportive of greater integration of T&CM providers with the health system, but patient safety, practitioner regulation, a robust evidence-base, and adequacy of T&CM provider training were factors shaping their views. Further research with a larger sample and a broader mix of stakeholders is needed to better understand Australians' appetite for, and the appropriateness of, more formal utilisation and/or integration of T&CM. Making robust evidence for specific T&CM therapies and providers more accessible to established or in-training healthcare professionals may be a pathway for greater understanding of the scope of T&CM practice in Australia.

Enrollment in public benefits is associated with improved health outcomes, yet many eligible individuals do not claim them. Public benefit programs are important policy tools to address health-related social needs. Health systems have developed new partnerships with community organizations to assist patients with enrollment in benefits. To determine whether text messages were more effective than paper referrals in prompting patients to contact benefits navigators following discharge from the emergency department. This 2-arm, nonblinded, randomized clinical trial was conducted from November 2023 to April 2024 at 2 academic hospital emergency departments in Philadelphia, Pennsylvania, and included adult individuals in stable condition with Medicaid or Medicare insurance who were discharged from the emergency department and eligible for at least 1 of 10 public benefit programs. Individuals were excluded if they were unable to read English or did not have access to a mobile phone. Data were analyzed from May 2024 to November 2024. Eligible participants were randomized in a 1:1 ratio. Participants allocated to the intervention received a series of 4 automated text messages over 14 days that prompted them to contact a benefits navigator telephone line operated by a community partner; those allocated to the control group received a paper flyer. The primary outcome was whether study participants called benefits navigators within 14 days. Secondary outcomes included whether study participants submitted any benefits application within 14 days. Of 1778 patients screened, there were 160 participants enrolled. Participants' mean (SD) age was 44 (17) years; 94 (59%) were women, 145 (91%) were non-Hispanic Black, and 11 (7%) were non-Hispanic White. In the intervention group, 20 participants (25%) contacted benefits navigators vs 0 in the control group (difference, 25 percentage points; 95% CI, 16%-35%). In the intervention group, 11 participants (14%) submitted at least 1 application for public benefits compared with 0 in the control group (difference, 14 percentage points; 95% CI, 6-22). The trial results suggest that text messages were more effective than paper referrals to help eligible emergency department patients seek assistance with public benefits applications. Text messages may offer a tool to allow health systems, in collaboration with community partners, to address health-related social needs. ClinicalTrials.gov Identifier: NCT05654220.

Abstract Large language models (LLMs) have demonstrated strong performance in medical contexts; however, existing benchmarks often fail to reflect the real-world complexity of low-resource health systems accurately. Here we develop a dataset of 5,609 clinical questions contributed by 101 community health workers across 4 Rwandan districts and compared responses generated by 5 LLMs (Gemini-2, GPT-4o, o3-mini, Deepseek R1 and Meditron-70B) with those from local clinicians. A subset of 524 question–answer pairs was evaluated using a rubric of 11 expert-rated metrics, scored on a 5-point Likert scale. Gemini-2 and GPT-4o were the best performers (achieving mean scores of 4.49 and 4.48 out of 5, respectively, across all 11 metrics). All LLMs significantly outperformed local clinicians ( P &lt; 0.001) across all metrics, with Gemini-2, for example, surpassing local general practitioners by an average of 0.83 points on every metric (range 0.38–1.10). Although performance degraded slightly when LLMs communicated in Kinyarwanda, the LLMs remained superior to clinicians and were over 500 times cheaper per response. These findings support the potential of LLMs to strengthen frontline care quality in low-resource, multilingual health systems.

Despite the relatively high turnover rates and increasing demand for homecare, little is known about the costs of turnover for homecare employers. To create effective policies to reduce turnover and associated costs, employers require an understanding of what factors contribute to the costs of turnover. Building upon existing models from labour economic and human resources theories, we worked with subject matter experts from a large homecare employer organization to co-design the first known homecare cost of turnover model. The resulting model accounts for sector-specific cost differences and can be used to estimate the costs of homecare worker turnover. As homecare continues to face high workforce instability, clear estimates of the cost of turnover can guide organizations and decision-makers in the evidence-based design of retention policies and programs to the benefit of homecare workers, funders, those seeking homecare, and the broader health and social care system.

The scarcity of subspecialist medical expertise poses a considerable challenge for healthcare delivery. This issue is particularly acute in cardiology, where timely, accurate management determines outcomes. We explored the potential of Articulate Medical Intelligence Explorer (AMIE), a large language model-based experimental medical artificial intelligence system, to augment clinical decision-making in this challenging context. We conducted a randomized controlled trial comparing large language model-assisted care with the usual care of complex patients suspected of having a genetic cardiomyopathy, and we curated a real-world dataset of complex cases from a subspecialist cardiology practice. Nine participating general cardiologists were provided with access to both clinical text reports and raw diagnostic data-including electrocardiograms, echocardiograms, cardiac magnetic resonance imaging scans and cardiopulmonary exercise testing-and were randomized to manage these cases, either with or without assistance from AMIE. We developed a ten-domain evaluation rubric used by three blinded subspecialists to evaluate the quality of triage, diagnosis and management. In our randomized controlled trial with retrospective patient data, subspecialists favored large language model-assisted responses overall, and for the management plan and diagnostic testing domains, with the remaining domains considered a tie. Overall, subspecialists preferred AMIE-assisted cardiology assessments 46.7% of the time, compared with 32.7% for cardiologists alone (P = 0.02), with 20.6% rated as a tie. Subspecialists also quantified errors, extra and missing content, reasoning and potential bias. Cardiologists alone had more clinically significant errors (24.3% versus 13.1%, P = 0.033) and more missing content (37.4% versus 17.8%, P = 0.0021) than cardiologists assisted by AMIE. Lastly, cardiologists who used AMIE reported that AMIE helped their assessment more than half the time (57.0%) and saved time in 50.5% of cases.

After performing an abortion in 1973, Dr. Kenneth Edelin was indicted and convicted of manslaughter. Dr. Edelin's conviction was reversed 50 years ago. However, the conflict between the medical and legal systems, the use of abortion prosecution to control patients and providers, and the framing of a fetus as a person feel just as relevant to today's abortion landscape.

Emergency management of severe polytrauma with traumatic diaphragmatic hernia via EMSS: case report and literature review

Coronary revascularization decision-making for patients with coronary artery disease (CAD) can be complex and challenging. Artificial intelligence (AI) has the potential to improve this decision-making by bringing data-driven insights to the point of care. We aimed to elicit, collect, and analyze various stakeholders' perceived potential and challenges related to developing, implementing, and adopting AI-based CAD treatment decision support systems. A facilitated small-group discussion method, known as a World Café, was conducted with general cardiologists, interventional cardiologists, cardiac surgeons, patients, caregivers, health system administrators, and industry representatives. One-on-one interviews were conducted for participants who could not attend the World Café. Perceived potential and challenges of AI-based CAD treatment decision support systems were solicited by asking participants three broad questions: (1) What is most challenging about revascularization decision-making? (2) How could an AI tool be integrated into the existing clinical workflow? (3) What are the critical components that need to be considered when developing the AI tool? Thematic analysis was performed to identify themes from the data. Nine participants completed the World Café, and 3 participants completed the one-on-one interviews. Five main themes emerged: (1) evidence-based care, (2) workload and resources, (3) data requirements (subthemes: patient-centered approach, evidence-based AI, and data integration), (4) tool characteristics (subthemes: end user built; generation and presentation of decision support information; user-friendliness and accessibility; and system logic, reasoning, and data privacy), and (5) incorporation into clinical workflow (subthemes: AI as an opportunity to improve care and knowledge translation). While health care providers aim to provide evidence-based care, CAD treatment decision-making can often be subjective due to the limited applicability of clinical practice guidelines and randomized controlled trial evidence to individual patients. AI-based clinical decision support systems may be an effective solution if the development and implementation focus on the issues identified by end users in this study (patient preference, data privacy, integration with clinical information systems, transparency, and usability).

Artificial Intelligence (AI) is transforming mental health service delivery within public health systems, offering innovative tools for assessment, intervention, and policy-level decision-making. Children with special needs—including those with developmental, learning, and neurodiverse conditions—often face challenges in accessing timely mental health support, leading to delayed identification of emotional and behavioral difficulties and widening disparities in care. AI-driven mental health support provides opportunities to bridge these gaps by enabling early detection, personalized interventions, and continuous monitoring of psychological well-being. Aligned with the World Health Organization (WHO) framework, which emphasizes mental health promotion, prevention, early intervention, and community-based care, AI applications such as predictive analytics, digital screening tools, and adaptive therapeutic platforms can enhance the accuracy and efficiency of mental health assessments. These technologies also allow mental health professionals and educators to monitor progress, adjust interventions in real time, and provide scalable support in school and community settings. Similarly, the National Education Policy (NEP) 2020 highlights inclusive education, early identification of learning difficulties, and the integration of technology to provide personalized learning experiences. AI can support these goals by facilitating individualized educational and psychological plans, improving access to assistive technologies, and enhancing engagement for learners with special needs. While the potential benefits of AI are significant, ethical, legal, and policy challenges must be addressed. Issues such as data privacy, algorithmic bias, informed consent, equitable access, and over-reliance on technology require careful consideration. Human oversight, interdisciplinary collaboration, and evidence-based regulation are critical to ensuring that AI tools complement, rather than replace, traditional mental health services. This research work aims to explore AI-driven mental health support from a public health perspective, emphasizing the integration of technological innovation with ethical practice, inclusive education, and policy frameworks. By examining the intersection of AI, mental health, and special education, the discussion seeks to advance strategies for responsible, equitable, and effective mental health support for children with special needs, ensuring their holistic development and psychological well-being at a population level.

Despite well-established recommendations for the treatment and secondary prevention of fragility fractures, implementation remains challenging. Understanding local practice realities and barriers is therefore essential for adapting global guidelines to national health systems. This study assessed the management of fragility hip fractures in elderly patients in Thailand, focusing on the perspectives of orthopaedic surgeons. We conducted a questionnaire-based survey of orthopaedic surgeons in Thailand who are actively involved in the care of patients with fragility fractures, focusing on acute management, secondary prevention, and overall perceptions of care. The survey was adapted and translated from the "Survey of Awareness and Attitudes to the Management of Fragility Fractures" developed by the Asia Pacific Orthopaedic Association. It was piloted with 10 volunteer orthopaedic surgeons and refined for clarity, comprehensiveness, and validity. The final questionnaire was distributed online in collaboration with the Royal College of Orthopaedic Surgeons of Thailand using registered membership contacts. Of 223 responses, 199 were eligible. Most participants practiced in tertiary public hospitals (36.2%), had < 5 years of experience, and managed 0-5 cases weekly. According to respondents, hip fracture fast-track protocols were available in 79.4% of hospitals, and 58.8% had fracture liaison services. Only 22.6% of respondents reported achieving surgery within 48h in > 90% of their patients, and 46.7% prescribed osteoporosis treatment to ≥ 75% of patients. University-affiliated hospitals were more likely to prescribe osteoporosis medication (OR 4.68, 95% CI 1.87-11.67), while cost concerns reduced prescribing (OR 0.40, 95% CI 0.20-0.81). Private hospitals had the highest odds of surgery within 48h (OR 104.43, 95% CI 7.21-1513.05). Implant unavailability was the main barrier to expedited surgery (OR 0.20, 95% CI 0.04-0.91). Although hip fracture fast-track protocols and fracture liaison services are increasingly available, timely surgery and osteoporosis treatment remain suboptimal. Addressing cost barriers, improving implant logistics, and expanding diagnostic access are essential to strengthen fragility fracture care in Thailand.

Fewer than 2% of eligible patients are screened for primary aldosteronism, despite evidence that early detection and targeted therapy are associated with lower cardiovascular and kidney morbidity. Recent updates to major hypertension and endocrine guidelines reflect growing recognition that primary aldosteronism is far more prevalent than previously understood and that broader, more practical screening approaches are needed. These recommendations increasingly extend screening beyond resistant hypertension to adults with stage 2 hypertension and even to all individuals with hypertension. They also aim to lower barriers to testing through more flexible guidance on antihypertensive medication management, reaffirm the aldosterone-to-renin ratio as the preferred initial test, and provide more standardized criteria for interpretation. Supporting evidence includes epidemiological data demonstrating a continuum of renin-independent aldosterone production across blood pressure categories, strong associations between untreated primary aldosteronism and adverse cardiovascular and kidney outcomes independent of blood pressure, and favorable cost-effectiveness of screening even in lower-risk groups. Implementation remains the principal challenge, with obstacles spanning patient, clinician, and health system levels. Emerging electronic health record strategies, including electronic phenotyping and integrated clinical decision support, have shown early promise in increasing screening uptake and streamlining diagnostic pathways. Collectively, contemporary guideline updates and implementation innovations represent a shift toward earlier and broader detection of primary aldosteronism, with the potential to reduce preventable cardiorenal disease across the hypertensive population.

Climate change poses significant threats to the livelihoods, health, and overall well-being of smallholder women farmers globally. In Mhondoro Ngezi, where agricultural production is predominantly rain-fed, high temperatures, recurrent droughts, and erratic rainfall patterns have intensified women's vulnerability to climate-induced health risks. This study examined the gendered health impacts of climate change on women farmers and explored how these challenges intersect with broader socio-economic inequalities. The research employed the Q methodology to identify and analyse women farmers' subjective viewpoints and lived experiences regarding climate-related health challenges. Findings reveal that prolonged exposure to extreme heat contributes to dehydration, heat stress, and pregnancy-related complications. Declining water availability increases susceptibility to waterborne diseases such as cholera and diarrhoea. Food shortages caused by recurrent crop failures have also led to malnutrition, reduced dietary diversity, and weakened immunity among women and their households. These health burdens are compounded by limited access to adequate healthcare services, including shortages of essential medicines, limited diagnostic capacity, and insufficiently trained rural health workers. Women also face difficulties accessing timely medical care during extreme weather events. Structural gender inequalities, such as limited financial resources and restricted decision-making power, further constrain their ability to adapt. The study underscores the urgent need to address the gendered health impacts of climate change, particularly for women farmers in vulnerable, climate-affected communities. Strengthening rural health systems, investing in gender-responsive climate adaptation strategies, and improving access to climate-health information are essential. The insights generated through Q methodology highlight the importance of incorporating women's voices into climate and health policy planning to enhance their resilience and well-being.

This narrative review investigates the implications of out-of-pocket (OOP) payments for malaria treatment in developing countries by synthesizing evidence from peer-reviewed articles, reports, and policy documents. A thematic approach was employed to analyze key areas, including economic impacts on households, barriers to accessing care, and the overall effectiveness of malaria control interventions. The review also evaluated alternative financing mechanisms and their potential to mitigate the financial burden on vulnerable populations. The findings reveal that OOP payments significantly hinder timely access to malaria treatment, disproportionately affecting low-income and rural households. Delayed treatment-seeking behavior, underutilization of preventive measures such as insecticide-treated nets, and suboptimal use of diagnostics were identified as major challenges. Furthermore, the financial burden of OOP payments exacerbates health inequities, increasing morbidity and mortality among marginalized groups. Effective alternatives, such as government subsidies, community health insurance, and donor-funded programs, were highlighted as solutions to reduce these barriers. The review concludes that reducing OOP payments is critical to improving malaria control and ensuring equitable healthcare access in developing countries. It recommends scaling up subsidized care, strengthening public health systems, and engaging in public-private partnerships to enhance the availability and affordability of malaria interventions. Policymakers are urged to prioritize financial protection strategies to achieve sustainable progress in malaria eradication efforts.

Maternal evaluation during routine antenatal care visits may reduce maternal morbidity and mortality by identifying and addressing issues early on. A health recommender system could help health professionals and pregnant women monitor daily health parameters, provide tailored recommendations, and support timely antenatal care. This study aims to qualitatively analyze challenges in the preimplementation of health recommender system for maternal care in Indonesia as perceived by multiple stakeholders, including health care providers, patients, health system managers, government officers, and technology vendors. The methodology used a qualitative approach, where qualitative data were obtained from interviews of 37 respondents from multiple stakeholders, consisting of 15 health workers and 15 patients from private and government health care facilities, 4 officers from government health offices, 2 directors of health application vendors, and 1 manager from a private health clinic. These semistructured interview results were analyzed using thematic analysis. This qualitative study identifies key challenges in implementing a health recommender system for maternal care in Indonesia across the people, process, infrastructure, and policy dimensions. Intercoder reliability for the coding process demonstrated almost perfect agreement (Cohen κ=0.90), supporting the consistency of the coding process. Six major challenges were revealed, mostly regarding skill, accuracy, completeness, timeliness, cost, and standardization. These 6 major challenges were mentioned 96 times, accounting for 64.43% of all codes extracted from the interviews. These findings emphasize the value of user involvement in system design to meet health care professionals' and patients' needs, technical advancements to foster trust and support effective decision-making, as well as enhanced data accuracy, reliable and timely service delivery, cost management, and clear regulatory standards. This formative, preimplementation qualitative study highlights the importance of involving users in system design and future implementation to meet the needs of health care professionals and patients. Reducing input errors and improving system reliability are critical to building trust and supporting effective point-of-care decision-making and, in later phases, facility-level monitoring as part of public health surveillance. Adherence to regulatory standards and the establishment of standardized guidelines will be key to enabling broader implementation. Further usability, feasibility, and pilot studies are required before any evaluation of effectiveness.

As behavioral health systems across the country continue to struggle with rising demand, workforce shortages and fragmented care, a new player is stepping into the policy arena with an ambitious reform agenda. Healthsperien's newly formed Center for Behavioral Health has launched Action for Progress, an initiative designed to bring together national leaders, advocacy groups and system experts to push for structural change in how behavioral health care is financed, measured and delivered.