The relationship between biomedical and health informatics and society: is it time for a social contract?
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocad169
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocad169
Foundational domains are the building blocks of educational programs. The lack of foundational domains in undergraduate health informatics (HI) education can adversely affect the development of rigorous curricula and may impede the attainment of CAHIIM accreditation of academic programs.
Author(s): Khairat, Saif, Feldman, Sue S, Rana, Arif, Faysel, Mohammad, Purkayastha, Saptarshi, Scotch, Matthew, Eldredge, Christina
DOI: 10.1093/jamia/ocad147
Rare disease research requires data sharing networks to power translational studies. We describe novel use of Research Electronic Data Capture (REDCap), a web application for managing clinical data, by the National Mesothelioma Virtual Bank, a federated biospecimen, and data sharing network.
Author(s): Rashid, Rumana, Copelli, Susan, Silverstein, Jonathan C, Becich, Michael J
DOI: 10.1093/jamia/ocad132
Patient-clinician communication provides valuable explicit and implicit information that may indicate adverse medical conditions and outcomes. However, practical and analytical approaches for audio-recording and analyzing this data stream remain underexplored. This study aimed to 1) analyze patients' and nurses' speech in audio-recorded verbal communication, and 2) develop machine learning (ML) classifiers to effectively differentiate between patient and nurse language.
Author(s): Zolnoori, Maryam, Vergez, Sasha, Sridharan, Sridevi, Zolnour, Ali, Bowles, Kathryn, Kostic, Zoran, Topaz, Maxim
DOI: 10.1093/jamia/ocad139
To determine whether the Office of the National Coordinator's policy change restricting the use of "gag clauses" in contracts between electronic health record (EHR) vendors and healthcare facilities increased the prevalence of screenshots in peer-reviewed literature.
Author(s): Bapna, Monika, Miller, Kristen, Ratwani, Raj M
DOI: 10.1093/jamia/ocad138
Little is known about proactive risk assessment concerning emergency department (ED) visits and hospitalizations in patients with heart failure (HF) who receive home healthcare (HHC) services. This study developed a time series risk model for predicting ED visits and hospitalizations in patients with HF using longitudinal electronic health record data. We also explored which data sources yield the best-performing models over various time windows.
Author(s): Chae, Sena, Davoudi, Anahita, Song, Jiyoun, Evans, Lauren, Hobensack, Mollie, Bowles, Kathryn H, McDonald, Margaret V, Barrón, Yolanda, Rossetti, Sarah Collins, Cato, Kenrick, Sridharan, Sridevi, Topaz, Maxim
DOI: 10.1093/jamia/ocad129
Sexual and gender minority (SGM) older adults experience greater health disparities compared to non-SGM older adults. The SGM older adult population is growing rapidly. To address this disparity and gain a better understanding of their unique challenges in healthcare relies on accurate data collection. We conducted a secondary data analysis of 2018-2022 electronic health record data for older adults aged ≥50 years, in 1 large academic health system to determine [...]
Author(s): May, Jennifer T, Myers, John, Noonan, Devon, McConnell, Eleanor, Cary, Michael P
DOI: 10.1093/jamia/ocad130
Health organizations and systems rely on increasingly sophisticated informatics infrastructure. Without anti-racist expertise, the field risks reifying and entrenching racism in information systems. We consider ways the informatics field can recognize institutional, systemic, and structural racism and propose the use of the Public Health Critical Race Praxis (PHCRP) to mitigate and dismantle racism in digital forms. We enumerate guiding questions for stakeholders along with a PHCRP-Informatics framework. By focusing on [...]
Author(s): Platt, Jodyn, Nong, Paige, Merid, Beza, Raj, Minakshi, Cope, Elizabeth, Kardia, Sharon, Creary, Melissa
DOI: 10.1093/jamia/ocad123
We extended a 2013 literature review on electronic health record (EHR) data quality assessment approaches and tools to determine recent improvements or changes in EHR data quality assessment methodologies.
Author(s): Lewis, Abigail E, Weiskopf, Nicole, Abrams, Zachary B, Foraker, Randi, Lai, Albert M, Payne, Philip R O, Gupta, Aditi
DOI: 10.1093/jamia/ocad120
Incorporating artificial intelligence (AI) into clinics brings the risk of automation bias, which potentially misleads the clinician's decision-making. The purpose of this study was to propose a potential strategy to mitigate automation bias.
Author(s): Wang, Ding-Yu, Ding, Jia, Sun, An-Lan, Liu, Shang-Gui, Jiang, Dong, Li, Nan, Yu, Jia-Kuo
DOI: 10.1093/jamia/ocad118