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Curriculum for Early Exposure to Clinical Informatics and Data Science for Noninformatics Trainees to Promote Interest and Inclusion in Informatics

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Title: Curriculum for Early Exposure to Clinical Informatics and Data Science for Noninformatics Trainees to Promote Interest and Inclusion in Informatics
Authors: Akshay Ravi, Benjamin Weia, Matthew Sakumoto, Aris Oates, Xinran Liu
Source: ACI Open. :e79-e86
Publisher Information: Georg Thieme Verlag KG, 2023.
Publication Year: 2023
Subject Terms: 03 medical and health sciences, 0302 clinical medicine, 4. Education, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Description: Background Curricula aimed at increasing exposure to informatics and practical data analytics among medical trainees could increase their effectiveness in clinical research, quality improvement, and clinical operations. Objectives The Clinical Informatics Data Science (CI-DS) pathway is a cross-disciplinary curriculum aimed at improving informatics exposure among medical trainees. We describe the development of this novel curriculum, the inaugural cohort, and lessons learned. Methods The CI-DS pathway is framed around upfront informatics didactics followed by a longitudinal, experiential training focused on mentorship, clinical data extraction/machine learning, and health technology governance. The curriculum was evaluated based on pre- and postpathway surveys completed by learners and logs of the elective activities selected by learners. Results The CI-DS pathway attracted 19 learners across 12 medical subspecialties, from medical students to fellows. Baseline surveys showed limited exposure to informatics across learners. The top three longitudinal activities completed were participating in electronic health record (EHR) governance meetings, data science supplemental courses, and designated mentorship meetings. Comparison of baseline with postpathway surveys demonstrated significant improvements in learner self-reported confidence in appraising an EHR modification ticket, accessing UCSF's deidentified data, exploring a database with basic structured query language (SQL), extracting data using SQL, and interpreting machine learning models. Conclusion An early exposure curriculum in clinical informatics with training in data extraction and governance can successfully recruit a diverse array of learners and improve confidence in practical informatics skills. We reflect on the strengths and weaknesses of this curriculum, and summarize the lessons learned to guide others in creating similar curricula for noninformatics clinicians.
Document Type: Article
Language: English
ISSN: 2566-9346
DOI: 10.1055/s-0043-1775971
Rights: CC BY
Accession Number: edsair.doi...........a007d3f0207d8343d9ed8d155f6b957e
Database: OpenAIRE
Description
Abstract:Background Curricula aimed at increasing exposure to informatics and practical data analytics among medical trainees could increase their effectiveness in clinical research, quality improvement, and clinical operations. Objectives The Clinical Informatics Data Science (CI-DS) pathway is a cross-disciplinary curriculum aimed at improving informatics exposure among medical trainees. We describe the development of this novel curriculum, the inaugural cohort, and lessons learned. Methods The CI-DS pathway is framed around upfront informatics didactics followed by a longitudinal, experiential training focused on mentorship, clinical data extraction/machine learning, and health technology governance. The curriculum was evaluated based on pre- and postpathway surveys completed by learners and logs of the elective activities selected by learners. Results The CI-DS pathway attracted 19 learners across 12 medical subspecialties, from medical students to fellows. Baseline surveys showed limited exposure to informatics across learners. The top three longitudinal activities completed were participating in electronic health record (EHR) governance meetings, data science supplemental courses, and designated mentorship meetings. Comparison of baseline with postpathway surveys demonstrated significant improvements in learner self-reported confidence in appraising an EHR modification ticket, accessing UCSF's deidentified data, exploring a database with basic structured query language (SQL), extracting data using SQL, and interpreting machine learning models. Conclusion An early exposure curriculum in clinical informatics with training in data extraction and governance can successfully recruit a diverse array of learners and improve confidence in practical informatics skills. We reflect on the strengths and weaknesses of this curriculum, and summarize the lessons learned to guide others in creating similar curricula for noninformatics clinicians.
ISSN:25669346
DOI:10.1055/s-0043-1775971