Search

Background:  Over the past 30 years, the American Medical Informatics Association (AMIA) has played a pivotal role in fostering a collaborative community for professionals in biomedical and health informatics. As an interdisciplinary association, AMIA brings together individuals with clinical, research, and computer expertise and emphasizes the use of data to enhance biomedical research and clinical work. The need for a recognition program within AMIA, acknowledging applied informatics skills by members, led to the establishment of the Fellows of AMIA (FAMIA) Recognition Program in 2018., Objectives:  To outline the evolution of the FAMIA program and shed light on its origins, development, and impact. This report explores factors that led to the establishment of FAMIA, considerations affecting its development, and the objectives FAMIA seeks to achieve within the broader context of AMIA., Methods:  The development of FAMIA is examined through a historical lens, encompassing key milestones, discussions, and decisions that shaped the program. Insights into the formation of FAMIA were gathered through discussions within AMIA membership and leadership, including proposals, board-level discussions, and the involvement of key stakeholders. Additionally, the report outlines criteria for FAMIA eligibility and the pathways available for recognition, namely the Certification Pathway and the Long-Term Experience Pathway., Results:  The FAMIA program has inducted five classes, totaling 602 fellows. An overview of disciplines, roles, and application pathways for FAMIA members is provided. A comparative analysis with other fellow recognition programs in related fields showcases the unique features and contributions of FAMIA in acknowledging applied informatics., Conclusion:  Now in its sixth year, FAMIA acknowledges the growing influence of applied informatics within health information professionals, recognizing individuals with experience, training, and a commitment to the highest level of applied informatics and the science associated with it., Competing Interests: The authors have no conflict of interests to disclose regarding this study., (Thieme. All rights reserved.)

Developing a diverse informatics workforce broadens the research agenda and ensures the growth of innovative solutions that enable equity-centered care. The American Medical Informatics Association (AMIA) established the AMIA First Look Program in 2017 to address workforce disparities among women, including those from marginalized communities. The program exposes women to informatics, furnishes mentors, and provides career resources. In 4 years, the program has introduced 87 undergraduate women, 41% members of marginalized communities, to informatics. Participants from the 2019 and 2020 cohorts reported interest in pursuing a career in informatics increased from 57% to 86% after participation, and 86% of both years' attendees responded that they would recommend the program to others. A June 2021 LinkedIn profile review found 50% of participants working in computer science or informatics, 4% pursuing informatics graduate degrees, and 32% having completed informatics internships, suggesting AMIA First Look has the potential to increase informatics diversity., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

There is a critical need need for multi-institutional, large-scale, international applied clinical informatics research, given the global, widespread use of commercially-available electronic health records with different designs, capabilities, configurations, and implementation strategies. The Clinical Informatics Research Collaborative (CIRCLE) aims to identify and develop best practices for safe and effective health information technology design, development, implementation, use, and evaluation.

We developed the Biomedical Informatics Researchers ranking website (rank.informatics-review.com) to overcome many of the limitations of previous scientific productivity ranking strategies. The website is composed of four key components that work together to create an automatically updating ranking website: (1) list of biomedical informatics researchers, (2) Google Scholar scraper, (3) display page, and (4) updater. The site has been useful to other groups in evaluating researchers, such as tenure and promotions committees in interpreting the various citation statistics reported by candidates. Creation of the Biomedical Informatics Researchers ranking website highlights the vast differences in scholarly productivity among members of the biomedical informatics research community.

Background: Correlation of data within electronic health records is necessary for implementation of various clinical decision support functions, including patient summarization. A key type of correlation is linking medications to clinical problems; while some databases of problem-medication links are available, they are not robust and depend on problems and medications being encoded in particular terminologies. Crowdsourcing represents one approach to generating robust knowledge bases across a variety of terminologies, but more sophisticated approaches are necessary to improve accuracy and reduce manual data review requirements., Objective: We sought to develop and evaluate a clinician reputation metric to facilitate the identification of appropriate problem-medication pairs through crowdsourcing without requiring extensive manual review., Approach: We retrieved medications from our clinical data warehouse that had been prescribed and manually linked to one or more problems by clinicians during e-prescribing between June 1, 2010 and May 31, 2011. We identified measures likely to be associated with the percentage of accurate problem-medication links made by clinicians. Using logistic regression, we created a metric for identifying clinicians who had made greater than or equal to 95% appropriate links. We evaluated the accuracy of the approach by comparing links made by those physicians identified as having appropriate links to a previously manually validated subset of problem-medication pairs., Results: Of 867 clinicians who asserted a total of 237,748 problem-medication links during the study period, 125 had a reputation metric that predicted the percentage of appropriate links greater than or equal to 95%. These clinicians asserted a total of 2464 linked problem-medication pairs (983 distinct pairs). Compared to a previously validated set of problem-medication pairs, the reputation metric achieved a specificity of 99.5% and marginally improved the sensitivity of previously described knowledge bases., Conclusion: A reputation metric may be a valuable measure for identifying high quality clinician-entered, crowdsourced data., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Objective: The field of clinical informatics has expanded substantially in the six decades since its inception. Early research focused on simple demonstrations that health information technology (HIT) such as electronic health records (EHRs), computerized provider order entry (CPOE), and clinical decision support (CDS) systems were feasible and potentially beneficial in clinical practice., Methods: In this review, we present recent evidence on clinical informatics in the United States covering three themes: 1) clinical informatics systems and interventions for providers, including EHRs, CPOE, CDS, and health information exchange; 2) consumer health informatics systems, including personal health records and web-based and mobile HIT; and 3) methods and governance for clinical informatics, including EHR usability; data mining, text mining, natural language processing, privacy, and security., Results: Substantial progress has been made in demonstrating that various clinical informatics methodologies and applications improve the structure, process, and outcomes of various facets of the healthcare system., Conclusion: Over the coming years, much more will be expected from the field. As we move past the "early adopters" in Rogers' diffusion of innovations' curve through the "early majority" and into the "late majority," there will be a crucial need for new research methodologies and clinical applications that have been rigorously demonstrated to work (i.e., to improve health outcomes) in multiple settings with different types of patients and clinicians.