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: 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.
METHODS: The DEA was performed using countries as decision-making units, schizophrenia disease investment (cost of disease as a percentage of total health care expenditure) as the input, and disability-adjusted life years (DALYs) per patient due to schizophrenia as the output. Data were obtained from the Global Burden of Disease 2017 study, the World Bank Group, and a literature search of the PubMed database.
RESULTS: Data were obtained for 44 countries; of these, 34 had complete data and were included in the DEA. Disease investment (percentage of total health care expenditure) ranged from 1.11 in Switzerland to 6.73 in Thailand. DALYs per patient ranged from 0.621 in Lithuania to 0.651 in Malaysia. According to the DEA, countries with the most efficient schizophrenia health care were Lithuania, Norway, Switzerland and the US (all with efficiency score 1.000). The least efficient countries were Malaysia (0.955), China (0.959) and Thailand (0.965).
LIMITATIONS: DEA findings depend on the countries and variables that are included in the dataset.
CONCLUSIONS: In this international DEA, despite the difference in schizophrenia disease investment across countries, there was little difference in output as measured by DALYs per patient. Potentially, Lithuania, Norway, Switzerland and the US should be considered 'benchmark' countries by policy makers, thereby providing useful information to countries with less efficient systems.