Bulletin of the World Health Organization最新文献

{"title":"Randomized controlled trials of digital health interventions for rheumatic disease management: a systematic review.","authors":"Anindita Santosa, James Weiquan Li, Tze Chin Tan","doi":"10.2471/BLT.24.292168","DOIUrl":"10.2471/BLT.24.292168","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the adoption, effectiveness and cost-effectiveness of digital health interventions for rheumatic disease management.</p><p><strong>Methods: </strong>Between 25 May 2024 and 2 June 2024, we systematically searched PubMed®, Scopus, ClinicalTrials.gov, the Global Observatory for eHealth and the World Bank Open Knowledge Repository for randomized controlled trials (RCTs) evaluating digital health interventions for rheumatic disease management. We included studies published between 2000 and 2024 that reported on adoption rates and efficacy. Two reviewers independently screened the studies, extracted data and categorized the digital interventions according to the World Health Organization's classification of digital health interventions.</p><p><strong>Findings: </strong>Of the 455 unique records identified, 21 RCTs met the inclusion criteria. Most digital health interventions (15 studies) focused on individual-centric interventions, such as targeted communication, personal health tracking, educational tools and wearable devices. Studies in high-income countries implemented advanced, integrated digital interventions combining individual-focused approaches with health worker interventions and data services using telemedicine platforms and decision support systems. In contrast, studies in low- and middle-income countries adapted accessible technologies such as mobile messaging and telephone-based education. Many telehealth, wearable technologies and educational interventions significantly improved disease control, patient adherence, knowledge and self-efficacy. Of the five studies assessing cost-effectiveness, all found digital interventions to be cost-effective.</p><p><strong>Conclusion: </strong>Digital health interventions show promise for managing rheumatic diseases. Tailoring these interventions to local infrastructure and emphasizing patient engagement are crucial for successful adoption. Future research should focus on standardizing evaluation methods, addressing digital divides and enhancing provider support and data services.</p>","PeriodicalId":9465,"journal":{"name":"Bulletin of the World Health Organization","volume":"103 2","pages":"136-147"},"PeriodicalIF":8.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774214/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards an inclusive digital health ecosystem.","authors":"Yao Xie, Kayode Philip Fadahunsi, Carol Kelleher, Derjung M Tarn, Audrey Grace, John O' Donoghue","doi":"10.2471/BLT.24.292020","DOIUrl":"10.2471/BLT.24.292020","url":null,"abstract":"","PeriodicalId":9465,"journal":{"name":"Bulletin of the World Health Organization","volume":"103 2","pages":"170-173"},"PeriodicalIF":8.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing digital health to achieve equitable and efficient health systems.","authors":"Viroj Tangcharoensathien, Alain Labrique, Divya Lakhotia, Rapeepong Suphanchaimat, Walaiporn Patcharanarumol","doi":"10.2471/BLT.24.293051","DOIUrl":"10.2471/BLT.24.293051","url":null,"abstract":"","PeriodicalId":9465,"journal":{"name":"Bulletin of the World Health Organization","volume":"103 2","pages":"82-82A"},"PeriodicalIF":8.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774223/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143078705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In this month's Bulletin.","authors":"","doi":"10.2471/BLT.25.000225","DOIUrl":"https://doi.org/10.2471/BLT.25.000225","url":null,"abstract":"","PeriodicalId":9465,"journal":{"name":"Bulletin of the World Health Organization","volume":"103 2","pages":"81"},"PeriodicalIF":8.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774218/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143078706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence, recessionary pressures and population health.","authors":"Jo-An Occhipinti, Ante Prodan, William Hynes, John Buchanan, Roy Green, Sharan Burrow, Harris A Eyre, Adam Skinner, Ian B Hickie, Mark Heffernan, Yun Ju Christine Song, Goran Ujdur, Marcel Tanner","doi":"10.2471/BLT.24.291950","DOIUrl":"10.2471/BLT.24.291950","url":null,"abstract":"<p><p>Economic and labour policies have a considerable influence on health and well-being through direct financial impacts, and by shaping social and physical environments. Strong economies are important for public health investment and employment, yet the rapid rise of generative artificial intelligence (AI) has the potential to reshape economies, presenting challenges beyond mere temporary market disruption. Generative AI can perform non-routine cognitive tasks, previously unattainable though traditional automation, creating new efficiencies. While this technology offers opportunities for innovation and productivity, its labour-displacing potential raises serious concerns about economic stability and social equity, both of which are critical to health. Job displacement driven by generative AI could worsen income inequality, shrink middle-class opportunities and reduce consumer demand, triggering recessionary pressures. In this article, we propose the existence of an AI-capital-to-labour ratio threshold beyond which a self-reinforcing cycle of recessionary pressures may emerge, and which market forces alone cannot correct. Traditional responses to such pressures, like fiscal stimulus or monetary easing, may be ineffective in addressing structural disruptions to labour markets caused by generative AI. We call for a proactive global response to harness the benefits of generative AI while mitigating risks. This response should focus on reorienting economic systems towards collective well-being, as emphasized in the World Health Assembly resolution <i>Economics of health for all</i> and the United Nations' Global Digital Compact. Integrated strategies that combine fiscal policy, regulation and social policies are critical to ensuring generative AI advances societal health and equity while avoiding harm from excessive job displacement.</p>","PeriodicalId":9465,"journal":{"name":"Bulletin of the World Health Organization","volume":"103 2","pages":"155-163"},"PeriodicalIF":8.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774225/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health workers' adoption of digital health technology in low- and middle-income countries: a systematic review and meta-analysis.","authors":"Minmin Wang, Kepei Huang, Xiangning Li, Xuetong Zhao, Laura Downey, Sondus Hassounah, Xiaoyun Liu, Yinzi Jin, Minghui Ren","doi":"10.2471/BLT.24.292157","DOIUrl":"10.2471/BLT.24.292157","url":null,"abstract":"<p><strong>Objective: </strong>To conduct a systematic review and meta-analysis of the facilitators of and barriers to the acceptance and use of digital health technology by health workers in low- and middle-income countries.</p><p><strong>Methods: </strong>We searched several databases for relevant articles published until 25 April 2024. We extracted data on four unified theories of acceptance and use of technology factors (performance expectancy, effort expectancy, social influence and facilitating conditions) and six additional factors (attitude, habit, incentive, risk, trust and self-efficacy); how these affected the outcomes of behavioural intention and actual use; and the strength of association if reported. We conducted a meta-analysis of the quantitative studies.</p><p><strong>Findings: </strong>We reviewed 36 publications, 20 of which were included in our meta-analysis. We observed that performance expectancy was the most frequently reported facilitator (in 21 studies; 58.3%) and that lack of facilitating conditions was the most cited barrier (10; 27.8%). From our meta-analysis, trust (<i>r</i> = 0.53; 95% confidence interval, CI: 0.18 to 0.76) and facilitating conditions (<i>r</i> = 0.42; 95% CI: 0.27 to 0.55) were the leading facilitators of behavioural intention and actual use, respectively. We identified concerns with performance expectancy (<i>r</i> = -0.14, 95% CI: -0.29 to 0.01) as the primary barrier to both outcomes.</p><p><strong>Conclusion: </strong>Our approach of clustering the facilitators of and barriers to the acceptance and use of digital health technology from the perspective of health workers highlighted the importance of creating an enabling ecosystem. Supportive infrastructure, tailored training programmes and incentive policies should be incorporated in the implementation of digital health programmes in low- and middle-income countries.</p>","PeriodicalId":9465,"journal":{"name":"Bulletin of the World Health Organization","volume":"103 2","pages":"126-135F"},"PeriodicalIF":8.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of digital HIV services in Guangzhou's primary health-care system, China.","authors":"Jun Wang, Yu-Zhou Gu, Yong-Heng Lu, Ju-Shuang Li, Ye-Fei Luo, Yan-Shan Cai, Zhi-Gang Han, Chun Hao","doi":"10.2471/BLT.24.291921","DOIUrl":"10.2471/BLT.24.291921","url":null,"abstract":"<p><strong>Objective: </strong>To describe changes in access to voluntary human immunodeficiency virus (HIV) counselling and testing services following the implementation of a mini-application (app) at primary health-care facilities across Guangzhou, China.</p><p><strong>Methods: </strong>In 2018, the Guangzhou Center for Disease Control and Prevention and the Lingnan Community Support Center co-developed WellTest, a mini-app within the WeChat environment, to address voluntary counselling and testing service needs. The mini-app provides on-demand information for clients, links them to health services, and allows users to provide feedback on health-care quality and share test results with partners. We retrieved data from the National HIV/AIDS Prevention and Control Information System and the app backend to assess adoption and service use after implementation of WellTest in primary health-care facilities in December 2018.</p><p><strong>Findings: </strong>Between 2018 and 2023, WellTest adoption at primary health-care facilities increased from 1.5% (2/134) to 90.1% (172/191). The annual number of visits for voluntary HIV counselling and testing services at these facilities rose from 7376 to 20 002, representing 83.6% of all 23 930 voluntary HIV counselling and testing visits in 2023, compared with 36.6% (7376/20 129) in 2018. The proportion of newly diagnosed HIV infections at primary health-care facilities increased from 21.7% (187/862) to 50.4% (239/474).</p><p><strong>Conclusion: </strong>The increased access to HIV services in Guangzhou's primary health-care facilities highlights the value of digital health interventions in addressing service delivery gaps and meeting the needs of providers and clients. Expanding such interventions has the potential to strengthen decentralized health care and disease screening in low-resource settings.</p>","PeriodicalId":9465,"journal":{"name":"Bulletin of the World Health Organization","volume":"103 2","pages":"99-109"},"PeriodicalIF":8.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging teleradiology with artificial intelligence.","authors":"","doi":"10.2471/BLT.25.020225","DOIUrl":"https://doi.org/10.2471/BLT.25.020225","url":null,"abstract":"<p><p>Can teleradiology supported by artificial intelligence (AI) boost overall radiology capacity in resource-constrained settings? Gary Humphreys reports.</p>","PeriodicalId":9465,"journal":{"name":"Bulletin of the World Health Organization","volume":"103 2","pages":"86-87"},"PeriodicalIF":8.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774222/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143078707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scan and share to register outpatients, India.","authors":"Sutapa B Neogi, Vikram Pagaria, Sharbari Dutta, Nishikant Bele, Prateeksha Yadav, Ratika Samtani","doi":"10.2471/BLT.24.292828","DOIUrl":"10.2471/BLT.24.292828","url":null,"abstract":"<p><strong>Problem: </strong>To address the long waiting times patients incur when visiting outpatient departments in India.</p><p><strong>Approach: </strong>In 2022, the National Health Authority in India developed a paperless service, called Scan and Share, leveraging mobile technology and QR (quick-response) codes to streamline outpatient department appointments. Patients can use a mobile application (app) to scan QR codes at health facilities, generating tokens linked to registration counters. The service integrates patients' demographic data from their Ayushman Bharat Health Account with the facilities' health information systems. Collaboration with government bodies, health workers and patient advocacy groups ensured compliance with data protection regulations. For developers, the National Health Authority published detailed technical specifications outlining standards for app functionality, security and interoperability on the Ayushman Bharat Digital Mission platform.</p><p><strong>Local setting: </strong>Launched in 2021, Ayushman Bharat Digital Mission in India aims to digitize health care, creating a shared digital infrastructure for affordable and accessible care.</p><p><strong>Relevant changes: </strong>As at 19 October 2024, the Scan and Share service operates in 16 939 health-care facilities across 35 states and territories. The service has reduced waiting times from 1 hour to 2-5 minutes. Out of 56 801 213 tokens generated, 714 014 (1.3%) were issued in the private sector. There are currently 2074 active developers, with 1545 from the private sector.</p><p><strong>Lessons learnt: </strong>The Scan and Share service is transforming health-care delivery by reducing outpatient department queues, waiting times and errors. High-performing states can provide valuable insights for states with low service adoption.</p>","PeriodicalId":9465,"journal":{"name":"Bulletin of the World Health Organization","volume":"103 2","pages":"164-169"},"PeriodicalIF":8.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774221/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From infrastructure to impact: why foundations matter in digital health.","authors":"Alain Labrique","doi":"10.2471/BLT.24.293085","DOIUrl":"10.2471/BLT.24.293085","url":null,"abstract":"","PeriodicalId":9465,"journal":{"name":"Bulletin of the World Health Organization","volume":"103 2","pages":"83-83A"},"PeriodicalIF":8.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774216/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143078703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}