Discussion Paper: Social accountability for students in a machine learning era

Williams, Logan Z. J.; Grainger, Rebecca

doi:10.11157/fohpe.v21i1.363

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…As well as accounting for variation in student skills and confidence and addressing potential cognitive bias from digital natives, this curriculum will need to address future areas in technology. A contemporary HI curriculum needs to cover participatory health (Qudah & Luetsch, 2019), machine learning (Williams & Grainger, 2020) and genomic medicine (Topol, 2019) and be flexible enough to include new technologies as they emerge.…”

Section: Discussionmentioning

confidence: 99%

“…They should also be able to optimise, share, store and retrieve data for problem solving and decision making. Furthermore, they should be able to critically appraise and adopt into practice, if suitable, new information and communication technologies from mobile apps to machine learning (Gray et al, 2014;Williams & Grainger, 2020). Despite these benefits, use of technology can be challenging and frustrating for some individuals if they do not understand the underlying science (Fridsma, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Student perspectives on health informatics in a medical curriculum: A case study

Townsley,

Sumner,

O'Neill

et al. 2024

FoHPE

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Introduction: Health informatics (HI) is the study and practice of technology used to improve the quality and efficiency of healthcare. Formal HI teaching lacks visibility in most Australasian medical schools. In this study, medical students collected data from their peers and recent graduates on the teaching and learning of HI to inform development of a needs-based integrated HI curriculum. Methods: This mixed-methods case study of our medical degree program used clinically relevant vignettes to explore student confidence and opinions on HI. Current HI learning was benchmarked against recommendations. Recent graduates from University of Otago Medical School participated in an online survey (n = 26), and five focus group interviews of final-year medical students (n = 17) were carried out by a peer student. Results: More than half of the participants surveyed felt confident in most HI topics, though many were less confident in telemedicine, evaluating electronic resources for patient use, data communication and data storage. Most students recalled learning some HI principles and agreed these should be integrated within their degree. Students highlighted that HI curriculum development should consider students’ self-identity as digital natives and the need for clinically situated, relevant and authentic learning to avoid tensions between theoretical HI concepts and clinical environments. Conclusion: Medical students are critical consumers of potential HI curriculum content and expressed clear preferences for clinically relevant and up-to-date HI content. Key challenges in developing an HI curriculum will be ensuring a student-centered, authentic, contemporary and future-focused curriculum, with relevance demonstrated to digital native students.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Student perspectives on health informatics in a medical curriculum: A case study

Townsley,

Sumner,

O'Neill

et al. 2024

FoHPE

View full text Add to dashboard Cite

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Clinical informatics training in medical school education curricula: a scoping review

Zainal

Tan

Xin

et al. 2022

Journal of the American Medical Informatics Association

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Objectives This scoping review evaluates the existing literature on clinical informatics (CI) training in medical schools. It aims to determine the essential components of a CI curriculum in medical schools, identify methods to evaluate the effectiveness of a CI-focused education, and understand its delivery modes. Materials and Methods This review was informed by the methodological guidance of the Joanna Briggs Institute. Three electronic databases including PubMed, Scopus, and Web of Science were searched for articles discussing CI between January 2010 and December 2021. Results Fifty-nine out of 3055 articles were included in our final analysis. Components of CI education include its utilization in clinical practice, ethical implications, key CI-related concepts, and digital health. Evaluation of educational effectiveness entails external evaluation by organizations external to the teaching institute, and internal evaluation from within the teaching institute. Finally, modes of delivery include various pedagogical strategies and teaching CI using a multidisciplinary approach. Discussion Given the broad discussion on the required competencies, we propose 4 recommendations in CI delivery. These include situating CI curriculum within specific contexts, developing evidence-based guidelines for a robust CI education, developing validated assessment techniques to evaluate curriculum effectiveness, and equipping educators with relevant CI training. Conclusion The literature reveals that CI training in the core curricula will complement if not enhance clinical skills, reiterating the need to equip students with relevant CI competencies. Furthermore, future research needs to comprehensively address current gaps in CI training in different contexts, evaluation methodologies, and delivery modes to facilitate structured training.

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Artificial intelligence and big data from digital health applications: publication trends and analysis

Arslantaş

2024

JHOM

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PurposeThe integration of big data with artificial intelligence in the field of digital health has brought a new dimension to healthcare service delivery. AI technologies that provide value by using big data obtained in the provision of health services are being added to each passing day. There are also some problems related to the use of AI technologies in health service delivery. In this respect, it is aimed to understand the use of digital health, AI and big data technologies in healthcare services and to analyze the developments and trends in the sector.Design/methodology/approachIn this research, 191 studies published between 2016 and 2023 on digital health, AI and its sub-branches and big data were analyzed using VOSviewer and Rstudio Bibliometrix programs for bibliometric analysis. We summarized the type, year, countries, journals and categories of publications; matched the most cited publications and authors; explored scientific collaborative relationships between authors and determined the evolution of research over the years through keyword analysis and factor analysis of publications. The content of the publications is briefly summarized.FindingsThe data obtained showed that significant progress has been made in studies on the use of AI technologies and big data in the field of health, but research in the field is still ongoing and has not yet reached saturation.Research limitations/implicationsAlthough the bibliometric analysis study conducted has comprehensively covered the literature, a single database has been utilized and limited to some keywords in order to reach the most appropriate publications on the subject.Practical implicationsThe analysis has addressed important issues regarding the use of developing digital technologies in health services and is thought to form a basis for future researchers.Originality/valueIn today’s world, where significant developments are taking place in the field of health, it is necessary to closely follow the development of digital technologies in the health sector and analyze the current situation in order to guide both stakeholders and those who will work in this field.

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Discussion Paper: Social accountability for students in a machine learning era

Cited by 3 publications

References 7 publications

Student perspectives on health informatics in a medical curriculum: A case study

Student perspectives on health informatics in a medical curriculum: A case study

Clinical informatics training in medical school education curricula: a scoping review

Artificial intelligence and big data from digital health applications: publication trends and analysis

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