Health Care Science最新文献

{"title":"Science, technology, and innovation in health for the next twenty years: A survey analysis in Colombia","authors":"Oscar Espinosa,&nbsp;Gabriela Puentes,&nbsp;Jhonathan Rodríguez,&nbsp;Adriana Robayo,&nbsp;Juan-Manual Anaya","doi":"10.1002/hcs2.87","DOIUrl":"10.1002/hcs2.87","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Colombia is a Latin American country with a very complex social and political context that has not allowed the allocation of sufficient resources to the fields of science, technology, and innovation (STI). This is particularly worrying for the area of health since not enough resources are allocated for public health, research, or education.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The so-called “Great Survey in Health 2019” was administered online through the SurveyMonkey platform to 5298 people in different regions of the country, representing the public, private, and academic sectors. The questionnaire consisted of 46 open and closed questions, including demographic inquiries. Data analysis involved textual analytics and sentiment analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Overall, 56% of those surveyed were women within the adult life cycle. Most respondents had a postgraduate education. Greater participation was observed in the Oriental, Bogotá, and Antioquia regions, which also concentrate the largest number of resources for STI. Among the main recommendations derived from the results, priorities include investing in research, personalised medicine, promoting the social appropriation of knowledge, addressing mental health, regulating research through a statute, promoting undergraduate research, and establishing recertification exams to pursue excellence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The results of this original study serve as a fundamental input to promote and strengthen the STI processes in life sciences and health. They serve as a guide to generate public policies and actions that guarantee better health and well-being for the Colombian population, strategically proposing a clear roadmap for the next 20 years.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"3 2","pages":"78-87"},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.87","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140232463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning in neurological disorders: A multivariate LSTM and AdaBoost approach to Alzheimer's disease time series analysis","authors":"Muhammad Irfan,&nbsp;Seyed Shahrestani,&nbsp;Mahmoud Elkhodr","doi":"10.1002/hcs2.84","DOIUrl":"https://doi.org/10.1002/hcs2.84","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Alzheimer's disease (AD) is a progressive brain disorder that impairs cognitive functions, behavior, and memory. Early detection is crucial as it can slow down the progression of AD. However, early diagnosis and monitoring of AD's advancement pose significant challenges due to the necessity for complex cognitive assessments and medical tests.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study introduces a data acquisition technique and a preprocessing pipeline, combined with multivariate long short-term memory (M-LSTM) and AdaBoost models. These models utilize biomarkers from cognitive assessments and neuroimaging scans to detect the progression of AD in patients, using The AD Prediction of Longitudinal Evolution challenge cohort from the Alzheimer's Disease Neuroimaging Initiative database.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The methodology proposed in this study significantly improved performance metrics. The testing accuracy reached 80% with the AdaBoost model, while the M-LSTM model achieved an accuracy of 82%. This represents a 20% increase in accuracy compared to a recent similar study.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>The findings indicate that the multivariate model, specifically the M-LSTM, is more effective in identifying the progression of AD compared to the AdaBoost model and methodologies used in recent research.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"3 1","pages":"41-52"},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.84","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139976562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empowering health care innovations: A look forward into 2024","authors":"Zongjiu Zhang,&nbsp;Tien Yin Wong,&nbsp;Haibo Wang,&nbsp;Jiefu Huang","doi":"10.1002/hcs2.85","DOIUrl":"https://doi.org/10.1002/hcs2.85","url":null,"abstract":"<p>As we unveil the first issue of <i>Health Care Science</i> in 2024, it's a moment of reflection and anticipation. Under the astute guidance of our leadership and the collective wisdom of our distinguished Editorial Board Members, we've journeyed through an extraordinary year, marking significant milestones and embracing challenges with resilience and innovation. We believe our progress reflects not just a testament to our commitment but also an indication of our role in driving healthcare innovation and excellence.</p><p><b>International diversity:</b> 2023, our journal emerged as a vibrant international academic platform, attracting manuscripts from 29 countries and regions. Focusing on technological innovation in healthcare services, we published six issues of 39 articles in 2023, reaching over 41,000 downloads from 166 countries and regions. This diversity is a clear indicator of our expanding global footprint and the trust the academic community places in us. The growth in our publications, alongside a dramatic increase in international manuscript submissions, highlights our journal's rising stature on the global healthcare community.</p><p><b>Impactful publications:</b> 2023 saw us publishing groundbreaking work in the fields of healthcare management, healthcare policy, medical technology, and public health. We also delved into hot topics like xenotransplantation, gene editing, and the application of large language models in healthcare. Moreover, we published influential guides and research on technological responses to pandemics. These contributions include some of our most downloaded and cited articles since the launch of <i>Health Care Science</i>.</p><p><b>Milestone recognitions:</b> The landmark achievements in 2023 were our inclusion in prestigious databases such as Scopus and the Directory of Open Access Journals (DOAJ), a recognition that came just a year after our launch. These inclusions are not just an honor but a responsibility to uphold the standards of scientific excellence and accessibility.</p><p><b>Key metrics of publication process:</b> We are pleased to share some key metrics regarding our manuscript process. Our median time to first decision was 24 days and the median time to final decision stood at 37 days, demonstrating our commitment to providing timely feedback to authors while also reflecting our thorough review process. Overall, our acceptance rate in 2023 was 54%. For those articles accepted, the median time from acceptance to online publication was 46 days. We are actively optimizing our publication cycle to enhance efficiency, while firmly safeguarding the rigor of the peer review process. Our emerging Associate Editor (eAE) team, composed of 21 dynamic young talents in academia, has been instrumental in manuscript sourcing, reviewing, curated readings, and promotions, significantly contributing to our journal's success.</p><p><b>Goals for 2024:</b> Looking ahead, we aim to streamline our editorial process whi","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"3 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.85","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139976501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of growth monitoring among children younger than 5 years at early childhood development centres in Nelson Mandela Bay, South Africa","authors":"S. McLaren, Liana Steenkamp, Jessica Ronaasen","doi":"10.1002/hcs2.83","DOIUrl":"https://doi.org/10.1002/hcs2.83","url":null,"abstract":"Early childhood development (ECD) centres are important community hubs in South Africa and act as sites for community detection of childhood nutrition problems. This study aimed to assess the ability of trained ECD practitioners with optimal support to correctly classify the nutritional status of infants and young children at ECD centres in the Nelson Mandela Bay.A descriptive, cross‐sectional study was used to collect data from 1645 infants and children at 88 ECD centres. Anthropometric measurements were taken by trained fieldworkers and growth monitoring and promotion infrastructure was audited at ECD centres.Of the sample, 4.4% (n = 72) were underweight by weight for age Z‐score (WAZ < −2) and 0.8% (n = 13) were severely underweight (WAZ < −3). Results showed that 13.1% (n = 214) were stunted by height for age Z‐score (HAZ < −2) and 4.5% (n = 74) were severely stunted (HAZ < −3). The prevalence of moderate acute malnutrition was 1.2% and severe acute malnutrition was 0.5%, while the prevalence of overweight was 9.2% and the prevalence of obesity was 4%. A significant level of agreement between the correct interpretation and the ECD practitioners' interpretation was observed across all the anthropometric indicators investigated. The true positive wasting cases had a mean mid‐upper arm circumference (MUAC) of 14.6 cm, which may explain the high false negative rate found in terms of children identified with wasting, where ECD practitioners fail to use the weight for height Z‐score (WHZ) interpretation for screening.By using ECD centres as hub to screen for malnutrition, it may contribute to the early identification of failure to thrive among young children. Although it was concerning that trained ECD practitioners are missing some children with an unacceptably high false negative rate, it may have been due to the fact that wasting in older children cannot be identified with MUAC alone and that accurate WFH plotting is needed. Onsite mentorship by governmental health workers may provide ECD practitioners with more confidence to screen children for growth failure based on regular WFH measurements. Moreover, ECD practitioners will be more confident to monitor the Road to Health booklets for missed vaccinations, vitamin A and deworming opportunities.","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"45 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139864095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of growth monitoring among children younger than 5 years at early childhood development centres in Nelson Mandela Bay, South Africa","authors":"Shawn W. McLaren,&nbsp;Liana Steenkamp,&nbsp;Jessica Ronaasen","doi":"10.1002/hcs2.83","DOIUrl":"10.1002/hcs2.83","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Early childhood development (ECD) centres are important community hubs in South Africa and act as sites for community detection of childhood nutrition problems. This study aimed to assess the ability of trained ECD practitioners with optimal support to correctly classify the nutritional status of infants and young children at ECD centres in the Nelson Mandela Bay.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A descriptive, cross-sectional study was used to collect data from 1645 infants and children at 88 ECD centres. Anthropometric measurements were taken by trained fieldworkers and growth monitoring and promotion infrastructure was audited at ECD centres.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of the sample, 4.4% (<i>n</i> = 72) were underweight by weight for age Z-score (WAZ &lt; −2) and 0.8% (<i>n</i> = 13) were severely underweight (WAZ &lt; −3). Results showed that 13.1% (<i>n</i> = 214) were stunted by height for age Z-score (HAZ &lt; −2) and 4.5% (<i>n</i> = 74) were severely stunted (HAZ &lt; −3). The prevalence of moderate acute malnutrition was 1.2% and severe acute malnutrition was 0.5%, while the prevalence of overweight was 9.2% and the prevalence of obesity was 4%. A significant level of agreement between the correct interpretation and the ECD practitioners' interpretation was observed across all the anthropometric indicators investigated. The true positive wasting cases had a mean mid-upper arm circumference (MUAC) of 14.6 cm, which may explain the high false negative rate found in terms of children identified with wasting, where ECD practitioners fail to use the weight for height Z-score (WHZ) interpretation for screening.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>By using ECD centres as hub to screen for malnutrition, it may contribute to the early identification of failure to thrive among young children. Although it was concerning that trained ECD practitioners are missing some children with an unacceptably high false negative rate, it may have been due to the fact that wasting in older children cannot be identified with MUAC alone and that accurate WFH plotting is needed. Onsite mentorship by governmental health workers may provide ECD practitioners with more confidence to screen children for growth failure based on regular WFH measurements. Moreover, ECD practitioners will be more confident to monitor the Road to Health booklets for missed vaccinations, vitamin A and deworming opportunities.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"3 1","pages":"32-40"},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.83","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139803908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying a competency improvement strategy for infection prevention and control professionals: A rapid systematic review and cluster analysis","authors":"Nuo Chen,&nbsp;Shunning Li,&nbsp;Zhengling Kuang,&nbsp;Ting Gong,&nbsp;Weilong Zhou,&nbsp;Ying Wang","doi":"10.1002/hcs2.81","DOIUrl":"10.1002/hcs2.81","url":null,"abstract":"<p>Remarkable progress has been made in infection prevention and control (IPC) in many countries, but some gaps emerged in the context of the coronavirus disease 2019 (COVID-19) pandemic. Core capabilities such as standard clinical precautions and tracing the source of infection were the focus of IPC in medical institutions during the pandemic. Therefore, the core competences of IPC professionals during the pandemic, and how these contributed to successful prevention and control of the epidemic, should be studied. To investigate, using a systematic review and cluster analysis, fundamental improvements in the competences of infection control and prevention professionals that may be emphasized in light of the COVID-19 pandemic. We searched the PubMed, Embase, Cochrane Library, Web of Science, CNKI, WanFang Data, and CBM databases for original articles exploring core competencies of IPC professionals during the COVID-19 pandemic (from January 1, 2020 to February 7, 2023). Weiciyun software was used for data extraction and the Donohue formula was followed to distinguish high-frequency technical terms. Cluster analysis was performed using the within-group linkage method and squared Euclidean distance as the metric to determine the priority competencies for development. We identified 46 studies with 29 high-frequency technical terms. The most common term was “infection prevention and control training” (184 times, 17.3%), followed by “hand hygiene” (172 times, 16.2%). “Infection prevention and control in clinical practice” was the most-reported core competency (367 times, 34.5%), followed by “microbiology and surveillance” (292 times, 27.5%). Cluster analysis showed two key areas of competence: Category 1 (program management and leadership, patient safety and occupational health, education and microbiology and surveillance) and Category 2 (IPC in clinical practice). During the COVID-19 pandemic, IPC program management and leadership, microbiology and surveillance, education, patient safety, and occupational health were the most important focus of development and should be given due consideration by IPC professionals.</p>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"3 1","pages":"53-66"},"PeriodicalIF":0.0,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.81","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139867294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying a competency improvement strategy for infection prevention and control professionals: A rapid systematic review and cluster analysis","authors":"Nuo Chen, Shunning Li, Zhengling Kuang, Ting Gong, Weilong Zhou, Ying Wang","doi":"10.1002/hcs2.81","DOIUrl":"https://doi.org/10.1002/hcs2.81","url":null,"abstract":"Remarkable progress has been made in infection prevention and control (IPC) in many countries, but some gaps emerged in the context of the coronavirus disease 2019 (COVID‐19) pandemic. Core capabilities such as standard clinical precautions and tracing the source of infection were the focus of IPC in medical institutions during the pandemic. Therefore, the core competences of IPC professionals during the pandemic, and how these contributed to successful prevention and control of the epidemic, should be studied. To investigate, using a systematic review and cluster analysis, fundamental improvements in the competences of infection control and prevention professionals that may be emphasized in light of the COVID‐19 pandemic. We searched the PubMed, Embase, Cochrane Library, Web of Science, CNKI, WanFang Data, and CBM databases for original articles exploring core competencies of IPC professionals during the COVID‐19 pandemic (from January 1, 2020 to February 7, 2023). Weiciyun software was used for data extraction and the Donohue formula was followed to distinguish high‐frequency technical terms. Cluster analysis was performed using the within‐group linkage method and squared Euclidean distance as the metric to determine the priority competencies for development. We identified 46 studies with 29 high‐frequency technical terms. The most common term was “infection prevention and control training” (184 times, 17.3%), followed by “hand hygiene” (172 times, 16.2%). “Infection prevention and control in clinical practice” was the most‐reported core competency (367 times, 34.5%), followed by “microbiology and surveillance” (292 times, 27.5%). Cluster analysis showed two key areas of competence: Category 1 (program management and leadership, patient safety and occupational health, education and microbiology and surveillance) and Category 2 (IPC in clinical practice). During the COVID‐19 pandemic, IPC program management and leadership, microbiology and surveillance, education, patient safety, and occupational health were the most important focus of development and should be given due consideration by IPC professionals.","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"1995 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139807508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constructing an effective evaluation system to identify doctors’ research capabilities","authors":"Xiaojing Hu","doi":"10.1002/hcs2.82","DOIUrl":"10.1002/hcs2.82","url":null,"abstract":"<p>The events of the coronavirus disease 2019 pandemic have emphasized the indispensable role of doctors in promoting public health and well-being [<span>1</span>]. Although medicine and health care are being transformed by technological advances, such as artificial intelligence, big data, genomics, precision medicine, and telemedicine, doctors continue to play a critical role in providing health care. However, a key challenge today is the lack of recognition of doctors by society at large. Hospitals, patients, and public opinion all play a role in evaluating doctors. However, this study will focus on hospitals’ doctor evaluations.</p><p>At the macro level, doctor evaluations influence their value orientation, research directions, and resource allocation. Assessing doctors also impacts their research and behavior at the micro level, as it is a crucial element in their development. It is challenging to build a suitable doctor evaluation system; therefore, doctor evaluations are a common research subject among the global academic community. Various stakeholders have paid attention to this issue, which is still being debated in the literature.</p><p>The global academic community considers an evaluation system based purely on merit and performance to be the most suitable for doctor evaluations [<span>2, 3</span>] with a primary focus on clinical care and scientific research. In addition, doctors are expected to also teach when working at large academic medical centers. Among these three sections, the index for scientific research evaluation accounts for the highest proportion [<span>4</span>]. A survey of 170 universities randomly selected from the CWTS Leiden Ranking revealed that among the 92 universities offering a School of Biomedical Sciences and promoting the accessibility of evaluation criteria, the mentioned policies included peer-reviewed publications, funding, national or international reputations, author order, and journal impact factors in 95%, 67%, 48%, 37%, and 28% of cases, respectively. Furthermore, most institutions clearly indicate their expectations for the minimum number of papers to be published annually [<span>5</span>]. Alawi et al. have shown that in many countries, the evaluation of medical professionals is primarily based on their ability to publish papers and secure research funding [<span>6</span>]. The recognition of these achievements under the existing evaluation system has a significant impact on key evaluation factors, such as performance, publications, work roles, and research awards.</p><p>Doctors in Chinese hospitals are assessed primarily on the inclusion of their scientific publications in the Science Citation Index (SCI). The number of published papers indexed in SCI significantly influences their professional ranking and likelihood of promotion. Hence, many young Chinese doctors feel under pressure to publish academic papers in addition to performing their clinical duties [<span>7</span>]. According to the Nati","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"3 1","pages":"67-72"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.82","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139822796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic evaluation of the performance of GPT-4 and PaLM2 to diagnose comorbidities in MIMIC-IV patients","authors":"Peter Sarvari,&nbsp;Zaid Al-fagih,&nbsp;Abdullatif Ghuwel,&nbsp;Othman Al-fagih","doi":"10.1002/hcs2.79","DOIUrl":"10.1002/hcs2.79","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Given the strikingly high diagnostic error rate in hospitals, and the recent development of Large Language Models (LLMs), we set out to measure the diagnostic sensitivity of two popular LLMs: GPT-4 and PaLM2. Small-scale studies to evaluate the diagnostic ability of LLMs have shown promising results, with GPT-4 demonstrating high accuracy in diagnosing test cases. However, larger evaluations on real electronic patient data are needed to provide more reliable estimates.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>To fill this gap in the literature, we used a deidentified Electronic Health Record (EHR) data set of about 300,000 patients admitted to the Beth Israel Deaconess Medical Center in Boston. This data set contained blood, imaging, microbiology and vital sign information as well as the patients' medical diagnostic codes. Based on the available EHR data, doctors curated a set of diagnoses for each patient, which we will refer to as ground truth diagnoses. We then designed carefully-written prompts to get patient diagnostic predictions from the LLMs and compared this to the ground truth diagnoses in a random sample of 1000 patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Based on the proportion of correctly predicted ground truth diagnoses, we estimated the diagnostic hit rate of GPT-4 to be 93.9%. PaLM2 achieved 84.7% on the same data set. On these 1000 randomly selected EHRs, GPT-4 correctly identified 1116 unique diagnoses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The results suggest that artificial intelligence (AI) has the potential when working alongside clinicians to reduce cognitive errors which lead to hundreds of thousands of misdiagnoses every year. However, human oversight of AI remains essential: LLMs cannot replace clinicians, especially when it comes to human understanding and empathy. Furthermore, a significant number of challenges in incorporating AI into health care exist, including ethical, liability and regulatory barriers.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"3 1","pages":"3-18"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.79","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139686292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning from socially driven frugal innovation to design the future of healthcare: A case of mobile Primary Health Center","authors":"Md Haseen Akhtar,&nbsp;Janakarajan Ramkumar","doi":"10.1002/hcs2.80","DOIUrl":"10.1002/hcs2.80","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Aim</h3>\u0000 \u0000 <p>Despite their flaws, the low-cost but powerful economical solutions can ensure everyone has access to health. The main aim of this study is to extract characteristics of frugal innovation (FI) and social innovation (SI) for Primary Health Centers (PHCs) in low resource settings (LRS) for sustainable development. We will use the gained insights to design the mobile primary healthcare infrastructure using FI and SI strategies. There is a lack of methodology to design sustainable healthcare infrastructure for LRS. There is a gap in the literature about building sustainable infrastructure to provide basic healthcare facilities essential to the community. This article studies several factors necessary for designing sustainable infrastructure from the lens of FI, SI, and sustainability to develop a mobile healthcare infrastructure for last-mile people.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Started with purposive sampled case studies to find out factors and criteria that most affect the success for an innovation to be frugal, social, and sustainable. The established criteria were used to design, develop, and deploy the mobile Primary Health Center (mPHC). Moving forward, we tested the system designed with stakeholders to gather insights. At this stage we found the feedback loop from the stakeholders and the role of interdisciplinary discussions between experts, medical officers, nurses, patient, and other staff of PHCs during the design, development, deployment, and test stage to be useful in taking design decisions efficiently.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The designed healthcare infrastructure of mPHC through the aspects of FI and SI proves to be efficient in providing key healthcare services to LRS.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Focusing on essential capabilities and optimizing performance with technology, methodologies, and processes reduces costs in an innovation. Focus on socially inclusive and rebalancing power disparities, overcome societal challenges and improve human capabilities will create a sustainable and novel solution.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"3 1","pages":"19-31"},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hcs2.80","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139875881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}