METHODS: Data were collected on travellers evaluated at GeoSentinel Network sites who reported healthcare during travel. Both unplanned and planned healthcare were analysed, including the reason and nature of healthcare sought, characteristics of the treatment provided and outcomes. Travellers that presented for rabies post-exposure prophylaxis were described elsewhere and were excluded from detailed analysis.
RESULTS: From May 2017 through June 2020, after excluding travellers obtaining rabies post-exposure prophylaxis (n= 415), 1093 travellers reported care for a medical or dental issue that was an unanticipated part of the travellers' planned itinerary (unplanned healthcare). Travellers who sought unplanned healthcare abroad had frequent diagnoses of acute diarrhoea, dengue, falciparum malaria and unspecified viral syndrome, and obtained care in 131 countries. Thirty-four (3%) reported subsequent deterioration and 230 (21%) reported no change in condition; a third (n = 405; 37%) had a pre-travel health encounter. Forty-one travellers had sufficient data on planned healthcare abroad for analysis. The most common destinations were the US, France, Dominican Republic, Belgium and Mexico. The top reasons for their planned healthcare abroad were unavailability of procedure at home (n = 9; 19%), expertise abroad (n = 9; 19%), lower cost (n = 8; 17%) and convenience (n = 7; 15%); a third (n = 13; 32%) reported cosmetic or surgical procedures. Early and late complications occurred in 14 (33%) and 4 (10%) travellers, respectively. Four travellers (10%) had a pre-travel health encounter.
CONCLUSIONS: International travellers encounter health problems during travel that often could be prevented by pre-travel consultation. Travellers obtaining planned healthcare abroad can experience negative health consequences associated with treatments abroad, for which pre-travel consultations could provide advice and potentially help to prevent complications.
MATERIALS AND METHODS: This qualitative study involved five public healthcare clinics in the Kuching district with indepth interviews (IDI) conducted on 14 primary care doctors (PCDs). Semi-structured interviews and in-depth discussions were conducted via videoconferencing. One representative was selected from each clinic at initiation, followed by snowball method for subsequent subject selection until saturation of themes. Interviews were transcribed verbatim, and analysis based on framework analysis principles via NVivo software. Themes were analysed deductively according to study objectives and evidence from literature.
RESULTS: Three main themes emerged from the IDI: (1) The perception of depression in elderly patients, (2) The perceived barriers to screening, and (3) The screening processes. Majority of the PCDs perceived depression as part of ageing process. Time constraints, lack of privacy in consultation rooms, dominant caregivers and failure to recognise recurrent somatic symptoms as part of depression influenced PCDs decision to screen. Screening was technically challenging for PCDs to use the DASS-21, which was not socio-culturally validated for local native population. Only 21.4% of respondents (3/14) reported screening at least three out 10 elderly patients seen over 1- month period. During the covid pandemic, due to the same human resource support and practices, most participants thought their screening for depression in elderlies had not changed.
CONCLUSION: Awareness of depression among PCDs needs to be re-enforced via continuous medical education programs to use appropriate screening tools, address infrastructure related barriers to optimise screening practices. The use of appropriate locally validated and socio-culturally adapted tool is vital to correctly interpret the screening test for patients.
METHODS: The Multiple Sclerosis International Federation third edition of the Atlas of MS was a survey that assessed the current global state of diagnosis including adoption of MS diagnostic criteria; barriers to diagnosis with respect to the patient, health care provider, and health system; and existence of national guidelines or national standards for speed of MS diagnosis.
RESULTS: Coordinators from 107 countries (representing approximately 82% of the world population), participated. Eighty-three percent reported at least 1 "major barrier" to early MS diagnosis. The most frequently reported barriers included the following: "lack of awareness of MS symptoms among general public" (68%), "lack of awareness of MS symptoms among health care professionals" (59%), and "lack of availability of health care professionals with knowledge to diagnose MS" (44%). One-third reported lack of "specialist medical equipment or diagnostic tests." Thirty-four percent reported the use of only 2017 McDonald criteria (McD-C) for diagnosis, and 79% reported 2017 McD-C as the "most commonly used criteria." Sixty-six percent reported at least 1 barrier to the adoption of 2017 McD-C, including "neurologists lack awareness or training" by 45%. There was no significant association between national guidelines pertaining to MS diagnosis or practice standards addressing the speed of diagnosis and presence of barriers to early MS diagnosis and implementation of 2017 McD-C.
DISCUSSION: This study finds pervasive consistent global barriers to early diagnosis of MS. While these barriers reflected a lack of resources in many countries, data also suggest that interventions designed to develop and implement accessible education and training can provide cost-effective opportunities to improve access to early MS diagnosis.
METHODS: This bibliometric work investigated the academic publication trends in medical image segmentation technology. These data were collected from the Web of Science (WoS) Core Collection and the Scopus. In the quantitative analysis stage, important visual maps were produced to show publication trends from five different perspectives including annual publications, countries, top authors, publication sources, and keywords. In the qualitative analysis stage, the frequently used methods and research trends in the medical image segmentation field were analyzed from 49 publications with the top annual citation rates.
RESULTS: The analysis results showed that the number of publications had increased rapidly by year. The top related countries include the Chinese mainland, the United States, and India. Most of these publications were conference papers, besides there are also some top journals. The research hotspot in this field was deep learning-based medical image segmentation algorithms based on keyword analysis. These publications were divided into three categories: reviews, segmentation algorithm publications, and other relevant publications. Among these three categories, segmentation algorithm publications occupied the vast majority, and deep learning neural network-based algorithm was the research hotspots and frontiers.
CONCLUSIONS: Through this bibliometric research work, the research hotspot in the medical image segmentation field is uncovered and can point to future research in the field. It can be expected that more researchers will focus their work on deep learning neural network-based medical image segmentation.
METHODS: Eligible studies were included if they used any models to assess the impact of COVID-19 disruptions on any health services. Articles published from January 2020 to December 2022 were identified from PubMed, Embase and CINAHL, using detailed searches with key concepts including COVID-19, modelling and healthcare disruptions. Two reviewers independently extracted the data in four domains. A descriptive analysis of the included studies was performed under the format of a narrative report.
RESULTS: This scoping review has identified a total of 52 modelling studies that employed several models (n=116) to assess the potential impact of disruptions to essential health services. The majority of the models were simulation models (n=86; 74.1%). Studies covered a wide range of health conditions from infectious diseases to non-communicable diseases. COVID-19 has been reported to disrupt supply of health services, demand for health services and social change affecting factors that influence health. The most common outcomes reported in the studies were clinical outcomes such as mortality and morbidity. Twenty-five studies modelled various mitigation strategies; maintaining critical services by ensuring resources and access to services are found to be a priority for reducing the overall impact.
CONCLUSION: A number of models were used to assess the potential impact of disruptions to essential health services on various outcomes. There is a need for collaboration among stakeholders to enhance the usefulness of any modelling. Future studies should consider disparity issues for more comprehensive findings that could ultimately facilitate policy decision-making to maximise benefits to all.
DESIGN: Scoping review, following the Arksey and O'Malley's framework, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.
DATA SOURCES: PubMed, Web of Science and Scopus were searched from 1 January 2020 through 31 December 2021.
ELIGIBILITY CRITERIA: Original articles, reviews, case studies and reports written in English were included. Works without full article and articles that did not answer the research questions were excluded.
DATA EXTRACTION AND SYNTHESIS: Data were extracted using a standardised data extraction form in Microsoft Excel. The findings of all included articles were synthesised narratively.
RESULTS: Eighty-five records were reviewed and 25 studies were included. For the field hospital implementation strategies, 'surge capacity', namely space, human resource, supply and system, was discussed in addition to the preparation and workflow of other services such as pharmacy, rehabilitation, food and nutrition. The management of COVID-19 field hospitals is challenging with respect to staff and resource shortages, inability to anticipate patient load and poor communication. The opportunities and recommendations for improvement of management were also highlighted.
CONCLUSIONS: The compilation of lessons learnt may help improve the future management of field hospitals, administratively and clinically.
METHODS: The review follows a systematic methodology with four core components: eligibility criteria, review selection, data extraction, and data synthesis. Studies focused on AI applications and hybrid chatbots in healthcare, particularly in chronic disease management and mental health support, were included. Publications from 2022 to 2025 were prioritized, and peer-reviewed sources in English were considered. After screening 116 studies, 29 met the criteria for inclusion. Data was extracted using a structured template, capturing study objectives, methodologies, findings, and challenges. Thematic analysis was applied to identify four themes: AI applications, technical advancements, user adoption, and challenges/ethical concerns. Statistical and content analysis methods were employed to synthesize the data comprehensively, ensuring robustness in the findings.
RESULTS: Hybrid chatbots in healthcare have shown significant benefits, such as reducing hospital readmissions by up to 25%, improving patient engagement by 30%, and cutting consultation wait times by 15%. They are widely used for chronic disease management, mental health support, and patient education, demonstrating their efficiency in both developed and developing countries.
DISCUSSION: The review concludes that overcoming these barriers through infrastructure investment, training, and enhanced transparency is crucial for maximizing the potential of AI in healthcare. Future researchers should focus on long-term outcomes, addressing ethical considerations, and expanding cross-cultural adaptability. Limitations of the review include the narrow scope of some case studies and the absence of long-term data on AI's efficacy in diverse healthcare contexts. Further studies are needed to explore these challenges and the long-term impact of AI-driven healthcare solutions.
METHODS: A mixed methods study was conducted at 20 participating EnPHC clinics in Johor and Selangor, two months after the intervention was initiated. Data collected from self-reported forms and a structured observation checklist were descriptively analysed. In-depth interviews were also conducted with 20 participants across the clinics selected to clarify any information gaps observed in each clinic, and data were thematically analysed.
RESULTS: Evaluation showed that all components of EnPHC intervention had been successfully implemented except for the primary triage counter and visit checklist. The challenges were mainly discovered in terms of human resource and physical structure. Although human resource was a common implementation challenge across all interventions, clinic-specific issues could still be identified. Among the adaptive measures taken were task sharing among staff and workflow modification to match the clinic's capacity. Despite the challenges, early benefits of implementation were highlighted especially in terms of service outcomes.
CONCLUSIONS: The evaluation study disclosed issues of human resource and physical infrastructure when a supplementary intervention is implemented. To successfully achieve a scaled-up PHC service delivery model based on comprehensive management of NCDs patient-centred care, the adaptive measures in local clinic context highlight the importance of collaboration between good organisational process and good clinical practice and process.