BACKGROUND: The public health landscape in North-East India is marked by the foundational principle of equitable health care provision, a critical endeavor considering the region\'s intricate geography and proximity to international borders. Health care workers grapple with challenges, such as treacherous routes, limited infrastructure, and diverse cultural nuances, when delivering essential medical services. Despite improvements since the National Rural Health Mission in 2005, challenges persist, prompting a study to identify health care workers\' challenges and alternative strategies in Manipur and Nagaland.
OBJECTIVE: This study aims to document the challenges experienced by health care workers during service delivery in the geographically challenging terrains of North-East India.
METHODS: This study is part of the i-DRONE (Indian Council of Medical Research\'s Drone Response and Outreach for North East) project, which aims to assess the feasibility of drone-mediated vaccine and medical delivery. This study addresses the secondary objective of the i-DRONE project. In-depth interviews of 29 health care workers were conducted using semistructured questionnaires in 5 districts (Mokokchung and Tuensang in Nagaland, and Imphal West, Bishnupur, and Churachandpur in Manipur). Nineteen health facilities, including primary health care centers, community health centers, and district hospitals, were selected. The study considered all levels of health care professionals who were in active employment for the past 6 months without a significant vacation and those who were engaged in ground-level implementation, policy, and maintenance activities. Data were recorded, transcribed, and translated, and subsequently, codes, themes, and subthemes were developed using NVivo 14 (QSR International) for thematic analysis.
RESULTS: Five themes were generated from the data: (1) general challenges (challenges due to being an international borderline district, human resource constraints, logistical challenges for medical supply, infrastructural issues, and transportation challenges); (2) challenges during the COVID-19 pandemic (increased workload, lack of diagnostic centers, mental health challenges and family issues, routine health care facilities affected, stigma and fear of infection, and vaccine hesitancy and misinformation); (3) perception and awareness regarding COVID-19 vaccination; (4) alternative actions or strategies adopted by health care workers to address the challenges; and (5) suggestions provided by health care workers. Health care workers demonstrated adaptability by overcoming these challenges and provided suggestions for addressing these challenges in the future.
CONCLUSIONS: Health care workers in Manipur and Nagaland have shown remarkable resilience in the face of numerous challenges exacerbated by the pandemic. Despite infrastructural limitations, communication barriers, and inadequate medical supply distribution in remote areas, they have demonstrated adaptability through innovative solutions like efficient data management, vaccination awareness campaigns, and leveraging technology for improved care delivery. The findings are pertinent for not only health care practitioners and policymakers but also the broader scientific and public health communities. However, the findings may have limited generalizability beyond Manipur and Nagaland.

BACKGROUND: The healthcare system in India is tiered and has primary, secondary and tertiary levels of facilities depending on the complexity and severity of health challenges at these facilities. Evidence suggests that emergency services in the country is fragmented. This study aims to identify the barriers and facilitators of emergency care delivery for patients with time-sensitive conditions, and develop and implement a contextually relevant model, and measure its impact using implementation research outcomes.
METHODS: We will study 85 healthcare facilities across five zones of the country and focus on emergency care delivery for 11 time-sensitive conditions. This implementation research will include seven phases: the preparatory phase, formative assessment, co-design of Model \"Zero\", co-implementation, model optimization, end-line evaluation and consolidation phase. The \"preparatory phase\" will involve stakeholder meetings, approval from health authorities and the establishment of a research ecosystem. The \"formative assessment\" will include quantitative and qualitative evaluations of the existing healthcare facilities and personnel to identify gaps, barriers and facilitators of emergency care services for time-sensitive conditions. On the basis of the results of the formative assessment, context-specific implementation strategies will be developed through meetings with stakeholders, providers and experts. The \"co-design of Model \'Zero\'\" phase will help develop the initial Model \"Zero\", which will be pilot tested on a small scale (co-implementation). In the \"model optimization\" phase, iterative feedback loops of meetings and testing various strategies will help develop and implement the final context-specific model. End-line evaluation will assess implementation research outcomes such as acceptability, adoption, fidelity and penetration. The consolidation phase will include planning for the sustenance of the interventions.
CONCLUSIONS: In a country such as India, where resources are scarce, this study will identify the barriers and facilitators to delivering emergency care services for time-sensitive conditions across five varied zones of the country. Stakeholder and provider participation in developing consensus-based implementation strategies, along with iterative cycles of meetings and testing, will help adapt these strategies to local needs. This approach will ensure that the developed models are practical, feasible and tailored to the specific challenges and requirements of each region.

Using simulated patients to mimic 9 established noncommunicable and infectious diseases, we assessed ChatGPT\'s performance in treatment recommendations for common diseases in low- and middle-income countries. ChatGPT had a high level of accuracy in both correct diagnoses (20/27, 74%) and medication prescriptions (22/27, 82%) but a concerning level of unnecessary or harmful medications (23/27, 85%) even with correct diagnoses. ChatGPT performed better in managing noncommunicable diseases than infectious ones. These results highlight the need for cautious AI integration in health care systems to ensure quality and safety.

BACKGROUND: The Lao People\'s Democratic Republic (Lao PDR), a lower-middle income country, has a higher malnutrition rate than other Southeast Asian countries. The decentralization of healthcare is a determinant of the effectiveness of programs to reduce malnutrition, but no study has focused on this factor in this country. This organizational study explores the state of decentralization of the healthcare system in Lao PDR that underlies the nutrition programs in the country.
METHODS: A qualitative study, which is based on a neo-institutional theory conceptual framework, explored factors related to dominant structure (laws, regulations, resources) and interpretative schemes (dominant ideas and beliefs) that characterize the nutrition services provided in the Lao healthcare system. Twenty-four semistructured interviews were performed with representatives of healthcare institutions involved in nutrition programs at different government levels, external donors and civil society organizations. The interviews were completed with relevant documents. The analysis focused on the convergence of interpretative schemes of the organizations concerned and the coherence between the structure underpinning the nutrition programs and the interpretative schemes.
RESULTS: Services deployed to reduce malnutrition in the Lao PDR remain largely centralized, despite factors specific to the country that led it to promote decentralization of its services. The convergence of interpretive schemes and the coherence between the observed structure and the interpretative schemes of actors at all governance levels ensure the stability of this state of decentralization, which has persisted for almost 50 years.
CONCLUSIONS: Nutrition programs in the Laos PDR are largely under the responsibility of the central government. The transformations in the healthcare system, notably with the use of new information technologies and the fact that the provinces are populated by a growing number of professionals trained in nutrition in addition to factors that push the system to be decentralized, such as ethnic diversity, the increasing availability of human resources in provinces, and the use of communication technologies, are not strong enough to change the balance of power between governance levels. The deconcentration that characterizes decentralization is therefore likely to continue for the foreseeable future.

OBJECTIVE: To determine Croatian healthcare (HC) professionals\' perspectives on HC management and leadership challenges.
METHODS: This cross-sectional study, conducted between May and June 2021, enrolled 1179 respondents from both the public and private sector, including medical doctors, nurses, pharmacists, economists, and other HC professionals. Their perspective on various facets of HC management, namely governance, ownership, accountability, financing, and potential for improvement, were investigated using an anonymous online survey.
RESULTS: Most respondents agreed that the system may be allocating resources ineffectively and that political mandates unduly influenced management decisions, impeding accountability. Competencies in organizational and financial experience, along with communication and leadership skills, were deemed fundamental for health care managers. Participants overwhelmingly supported data-driven decision-making, improved education, and the development of leadership skills as key avenues for system enhancement.
CONCLUSIONS: The study underscores the need for better financial management and overall governance, in the Croatian HC, offering insights that can inform evidence-based policy decisions and reforms toward a more efficient and accountable HC system.

BACKGROUND: This study aimed to explore how nurses experience relational work in the emergency department.
METHODS: A qualitative design with 34 focus group interviews using an abductive thematic analysis were completed for this study. Participants were recruited from an annual mandatory continuous learning program in 2020-2022 at 2 university hospitals in the Capital Region of Denmark. We applied semistructured interviews in an instructor-supported reflection session on the topic \"relational nursing care.\" Group discussion was supported by an interview guide addressing key elements of the nurse-patient relationship as described in the fundamentals of care framework.
RESULTS: Acute care nurses\' attention was primarily directed toward the initial patient assessment, rather than toward the later stages of the patient trajectory. Forming a relationship with the patient was highly individual and done at the discretion of each nurse. The key elements of relational nursing were not mutually exclusive, but the findings could be separated into biomedical and relational care, where biomedical tasks took precedence.
CONCLUSIONS: Relational care in the emergency department is optional and individually performed. Moreover, emergency nurses lack a vocabulary to express this type of work. Consequently, there is a risk that patients\' psychosocial needs are not sufficiently met. According to the emergency nurses participating in this study, nurses fall short when performing and describing relational care. Nurses need more knowledge to address the psychosocial patient needs during short-term hospital admissions. Relational care and patient centeredness also need to be acknowledged by nursing leaders and further developed.

BACKGROUND: Following marked reductions in sleep medicine care early in the COVID-19 pandemic, there is limited information about the recovery of these services. We explored long-term trends in obstructive sleep apnoea (OSA) health services and service backlogs during the pandemic compared with pre-pandemic levels in Ontario (the most populous province of Canada).
METHODS: In this retrospective population-based study using Ontario (Canada) health administrative data on adults, we compared rates of polysomnograms (PSGs), outpatient visits and positive airway pressure (PAP) therapy purchase claims during the pandemic (March 2020 to December 2022) to pre-pandemic rates (2015-2019). We calculated projected rates using monthly seasonal time series auto-regressive integrated moving-average models based on similar periods in previous years. Service backlogs were estimated from the difference between projected and observed rates.
RESULTS: Compared with historical data, all service rates decreased at first during March to May 2020 and subsequently increased. By December 2022, observed service rates per 100 000 persons remained lower than projected for PSGs (September to December 2022: 113 vs 141, 95% CI: 121 to 163) and PAP claims (September to December 2022: 50 vs 60, 95% CI: 51 to 70), and returned to projected for outpatient OSA visits. By December 2022, the service backlog was 193 078 PSGs (95% CI: 139 294 to 253 075) and 57 321 PAP claims (95% CI: 27 703 to 86 938).
CONCLUSIONS: As of December 2022, there was a sustained reduction in OSA-related health services in Ontario, Canada. The resulting service backlog has likely worsened existing problems with underdiagnosis and undertreatment of OSA and supports the adoption of flexible care delivery models for OSA that include portable technologies.

Generative AI models, such as ChatGPT, have significantly impacted healthcare through the strategic use of prompts to enhance precision, relevance, and ethical standards. This perspective explores the application of prompt engineering to tailor outputs specifically for healthcare stakeholders: patients, providers, policymakers, and researchers. A nine-stage process for prompt engineering in healthcare is proposed, encompassing identifying applications, understanding stakeholder needs, designing tailored prompts, iterative testing and refinement, ethical considerations, collaborative feedback, documentation, training, and continuous updates. A literature review focused on \"Generative AI\" or \"ChatGPT,\" prompts, and healthcare informed this study, identifying key prompts through qualitative analysis and expert input. This systematic approach ensures that AI-generated prompts align with stakeholder requirements, offering valuable insights into symptoms, treatments, and prevention, thereby supporting informed decision-making among patients.

BACKGROUND: A Dutch nationwide prospective cohort study was initiated to investigate recovery trajectories of people recovering from coronavirus disease 2019 (COVID-19) and costs of treatment by primary care allied health professionals.
OBJECTIVE: The study described recovery trajectories over a period of 12 months and associated baseline characteristics of participants recovering from COVID-19 who visited a primary care allied health professional. It also aimed to provide insight into the associated healthcare and societal costs.
METHODS: Participants completed participant-reported standardized outcomes on participation, health-related quality of life, fatigue, physical functioning, and costs at baseline (ie, start of the treatment), 3, 6, 9 and 12 months.
RESULTS: A total of 1451 participants (64 % women, 76 % mild/moderate severity) with a mean (SD) age of 49 (12) years were included. Linear mixed models showed significant and clinically relevant improvements over time in all outcome measures between baseline and 12 months. Between 6 and 12 months, we found significant but not clinically relevant improvements in most outcome measures. Having a worse baseline score was the only baseline factor that was consistently associated with greater improvement over time on that outcome. Total allied healthcare costs (mean €1921; SEM €48) made up about 3% of total societal costs (mean €64,584; SEM €3149) for the average participant in the cohort.
CONCLUSIONS: The health status of participants recovering from COVID-19 who visited an allied health professional improved significantly over a 12-month follow-up period, but nearly the improvement occurred between baseline and 6 months. Most participants still reported severe impairments in their daily lives, and generated substantial societal costs. These issues, combined with the fact that baseline characteristics explained little of the variance in recovery over time, underscore the importance of continued attention for the management of people recovering from COVID-19.
BACKGROUND: clinicaltrials.gov (NCT04735744).

UNASSIGNED: This study investigates the integration of financial technology (FinTech) and electronic health (eHealth) to explore the opportunities, challenges, and implications arising from their interlinkage in Saudi Arabia.
UNASSIGNED: Utilizing qualitative semi-structured interviews with 26 participants-including physicians, patients, technical and administrative managers, and FinTech consultants-the research adopts an inductive approach to understand diverse perspectives.
UNASSIGNED: Key findings reveal significant benefits such as improved efficiency in administrative processes, enhanced access to healthcare services, increased financial inclusion, better decision-making, improved patient experience, and the promotion of innovation and sustainability. However, barriers including regulatory challenges, data privacy and security concerns, interoperability issues, the digital divide, resistance to change, and cost implications were also identified.
UNASSIGNED: Overall, the integration of FinTech and eHealth holds substantial promise for advancing healthcare delivery in Saudi Arabia. Future implications include the expansion of telehealth services, an increase in startups, the integration of wearable health devices, blockchain-based systems, evolving regulatory frameworks, and heightened collaborations. Addressing the identified challenges is crucial for realizing the full potential of this integration.