American Medical Informatics Association

ObjectiveTo introduce Linkja, an open-source, certified, Privacy-Preserving Record Linkage (PPRL) tool with the primary objective of facilitating secure and efficient record linkage across diverse datasets, while preserving individual privacy, providing a comprehensive and privacy-centric approach to program assessments. ApproachLinkja has been used to evaluate Chicago’s Flexible Housing Pool program by securely linking various datasets, including Homeless Management Information Systems (HMIS), Electronic Health Records, Jail records, Medical Examiner reports, and Public Health data. Data contributors used separate honest brokers for record linkage, and generation of salt and cryptography keys. ResultsLinkja enabled this multi-sector linkage by facilitating legal and data sharing agreements, avoided licensing fees and procurement processes for all parties, and provided a de-identified for analysis. The insights gleaned from the analysis motivated the FHP program to plan a follow-up evaluation that will add emergency serviced records from a separate City of Chicago department. The successful linkage provided a nuanced understanding of the association between stable housing and reduced healthcare utilization. ConclusionsLinkja's cryptographic certification ensures the highest standards of security during data linkage, safeguarding sensitive information. The matching rules, validated on hard-to-match populations, prove essential in maintaining accuracy and reliability in the linkage process. ImplicationsThe open-source nature of Linkja promotes transparency and collaboration in the development and enhancement of privacy-preserving record linkage techniques. This tool has broad implications for sectors dealing with sensitive data, fostering responsible data-sharing practices, and enabling secure collaborative research initiatives without compromising individual privacy.

The use of multiple choice questions in exams remains a common choice in education for various reasons, such as ease of assessment, perceived objectivity, and the ability to provide rapid feedback especially in large classes. Research shows that the use of multiple choice questions can strengthen retention of information, especially involving alternative wrong answers, as well as measure students' basic understanding in various subjects. However, to create quality multiple choice questions, an in-depth evaluation of the question elements is required, including item analysis to ensure the validity, reliability and fairness of the assessment. The results of this research using quantitative descriptive methods show that most of the questions can be improved, while a small number need to be rejected. The research conclusions suggest that rejected items should not be reused, while items that need to be corrected should be improved to improve the overall quality of the exam. Thus, analyzing the quality of multiple choice questions is crucial for increasing the effectiveness of assessment, especially in higher education contexts such as nursing and medical education.

Neural networks have achieved great success in many tasks. However, their black-box nature limits their use in sensitive areas such as medical applications in which both performance in accuracy and intelligibility are critically important. In this talk, I will discuss our recent research on explainable deep tabular learning, a specific kind of deep learning models for tabular data which is very common in medical and healthcare applications. In particular, I will show how the concept-based learning models and example-based learning models can be designed for explainable deep tabular learning. I will also discuss their applications in biomedicine and healthcare.

The paper proposes a methodology that emphasis techno-pedagogy, namely the constructivist and the adaptive intelligent learning of specialized semiology of COVID-19. An e-learning built on a constructivist pedagogy with a technology such adaptive intelligent environment, can be individualized (adaptive learning), can enhance learners' interactions with others (collaborative learning), and transforming the role of the teacher as facilitators of learning and assessor of competency. To make our system intelligent, we cope with Artificial Intelligence and Big data.

African green monkeys (AGMs), Chlorocebus pygerythrus, are a natural host for a lentivirus related to HIV, SIV. SIV-infected AGMs rarely progress to AIDS despite robust viral replication. Though multiple mechanisms are involved, a primary component is the animals' ability to downregulate CD4 expression on mature CD4+ Th cells, rendering these cells resistant to infection by SIV. These CD8αα+ T cells retain functional characteristics of CD4+ Th cells while simultaneously acquiring abilities of cytotoxic CD8αβ+ T cells. To determine mechanisms underlying functional differences between T cell subsets in AGMs, chromatin accessibility in purified populations was determined by assay for transposase-accessible chromatin sequencing. Differences in chromatin accessibility alone were sufficient to cluster cells by subtype, and accessibility at the CD4 locus reflected changes in CD4 expression. DNA methylation at the CD4 locus also correlated with inaccessible chromatin. By associating accessible regions with nearby genes, gene expression was found to correlate with accessibility changes. T cell and immune system activation pathways were identified when comparing regions that changed accessibility from CD4+ T cells to CD8αα+ T cells. Different transcription factor binding sites are revealed as chromatin accessibility changes, and these differences may elicit downstream changes in differentiation. This comprehensive description of the epigenetic landscape of AGM T cells identified genes and pathways that could have translational value in therapeutic approaches recapitulating the protective effects CD4 downregulation.

SummaryObjectives: To summarize the activities of the International Academy of Health Sciences Informatics (IAHSI) in 2021 and welcome its 2021 Class of Fellows.Methods: Report on governance, strategic directions, newly elected fellows, plenary meetings, and other activities of the Academy.Results: As in 2020, all of the Academy's activities were carried out virtually due to the COVID-19 pandemic. In 2021, new Board members were elected. Strategic activities in data standards and interoperability and in mentorship moved forward. A new class of 26 Fellows was elected, bringing the total membership of the Academy to 204 Fellows from all regions of the world. In addition, a virtual plenary meeting was held.Conclusions: The Academy has continued to pursue its role as the honorific society globally for biomedical and health informatics. Expansion of strategic activities and membership will continue moving forward.

The widespread adoption of electronic health records and a simultaneous increase in regulatory demands have led to an acceleration of documentation requirements among clinicians. The corresponding burden from documentation requirements is a central contributor to clinician burnout and can lead to an increased risk of suboptimal patient care. To address the problem of documentation burden, the 25 by 5: Symposium to Reduce Documentation Burden on United States Clinicians by 75% by 2025 (Symposium) was organized to provide a forum for experts to discuss the current state of documentation burden and to identify specific actions aimed at dramatically reducing documentation burden for clinicians. The Symposium consisted of six weekly sessions with 33 presentations. The first four sessions included panel presentations discussing the challenges related to documentation burden. The final two sessions consisted of breakout groups aimed at engaging attendees in establishing interventions for reducing clinical documentation burden. Steering Committee members analyzed notes from each breakout group to develop a list of action items. The Steering Committee synthesized and prioritized 82 action items into Calls to Action among three stakeholder groups: Providers and Health Systems, Vendors, and Policy and Advocacy Groups. Action items were then categorized into as short-, medium-, or long-term goals. Themes that emerged from the breakout groups' notes include the following: accountability, evidence is critical, education and training, innovation of technology, and other miscellaneous goals (e.g., vendors will improve shared knowledge databases). The Symposium successfully generated a list of interventions for short-, medium-, and long-term timeframes as a launching point to address documentation burden in explicit action-oriented ways. Addressing interventions to reduce undue documentation burden placed on clinicians will necessitate collaboration among all stakeholders.

The study sought to develop a comprehensive and current description of what Clinical Informatics Subspecialty (CIS) physician diplomates do and what they need to know. Three independent subject matter expert panels drawn from and representative of the 1695 CIS diplomates certified by the American Board of Preventive Medicine contributed to the development of a draft CIS delineation of practice (DoP). An online survey was distributed to all CIS diplomates in July 2018 to validate the draft DoP. A total of 316 (18.8%) diplomates completed the survey. Survey respondents provided domain, task, and knowledge and skill (KS) ratings; qualitative feedback on the completeness of the DoP; and detailed professional background and demographic information. This practice analysis resulted in a validated, comprehensive, and contemporary DoP comprising 5 domains, 42 tasks, and 139 KS statements. The DoP that emerged from this study differs from the 2009 CIS Core Content in 2 respects. First, the DoP reflects the growth in amount, types, and utilization of health data through the addition of a practice domain, tasks, and KS statements focused on data analytics and governance. Second, the final DoP describes CIS practice in terms of tasks in addition to identifying knowledge required for competent practice. This study (1) articulates CIS diplomate tasks and knowledge used in practice, (2) provides data that will enable the American Board of Preventive Medicine CIS examination to align with current practice, (3) informs clinical informatics fellowship program requirements, and (4) provides insight into maintenance of certification requirements.

The widespread adoption and use of electronic health records and their use to enable learning health systems (LHS) holds great promise to accelerate both evidence-generating medicine (EGM) and evidence-based medicine (EBM), thereby enabling a LHS. In 2016, AMIA convened its 10th annual Policy Invitational to discuss issues key to facilitating the EGM-EBM paradigm at points-of-care (nodes), across organizations (networks), and to ensure viability of this model at scale (sustainability). In this article, we synthesize discussions from the conference and supplements those deliberations with relevant context to inform ongoing policy development. Specifically, we explore and suggest public policies needed to facilitate EGM-EBM activities on a national scale, particularly those policies that can enable and improve clinical and health services research at the point-of-care, accelerate biomedical discovery, and facilitate translation of findings to improve the health of individuals and populations.