To develop and evaluate a human-LLM (Large Language Model) collaborative approach for systematic ontology updating, demonstrated with the Dietary Lifestyle Ontology (DILON).
Author(s): Jung, Jinsun, Taira, Ricky, Kim, Hyeoneui
DOI: 10.1093/jamia/ocag015
Research on artificial intelligence (AI)-based clinical decision-support (AI-CDS) systems has returned mixed results. Sometimes providing AI-CDS to a clinician will improve decision-making performance, sometimes it will not, and it is not always clear why. This scoping review seeks to clarify existing evidence by identifying clinician-level and technology design factors that impact the effectiveness of AI-assisted decision-making in medicine.
Author(s): Jackson, Nicholas J, Brown, Katherine E, Miller, Rachael, Murrow, Matthew, Cauley, Michael R, Collins, Benjamin X, Novak, Laurie L, Benda, Natalie C, Ancker, Jessica S
DOI: 10.1093/jamia/ocag002
To detail patient challenges, and how technology support addressed them, in a remote patient activation intervention for hemodialysis patients (n = 93) from trained patient mentors (n = 26).
Author(s): Veinot, Tiffany C, Wickens, Megan, Hennessey, Edward, Argentina, Marissa, Eggebrecht, Kara, Zerkle, Alicia, Le, Vu, Collins Damron, Kelli, Velez, Lisa, Bragg-Gresham, Jennifer, Krein, Sarah L, Chatoth, Dinesh, Heung, Michael, Gillespie, Brenda, Murphy, Barbara, Zheng, Kai, Saran, Rajiv
DOI: 10.1093/jamia/ocaf226
We present a set of definitions and a conceptual model to support primary and consulting physician schedule integration into the electronic health record (EHR) in an inpatient setting and show how utilization of this functionality supports patient-centered communication.
Author(s): Hill, Jeremy B, Bernstam, Elmer V, Cui, Licong, Killoran, Peter V
DOI: 10.1093/jamia/ocaf217
Author(s): Alper, Brian S, Dehnbostel, Joanne, Lehmann, Harold
DOI: 10.1093/jamia/ocag024
Physician and advanced practice provider (APP) well-being is a critical focus in healthcare. Emerging technology such as generative artificial intelligence (GAI) scribes reduces physician and APP administrative burden created by electronic health records. Early adopters of this technology have demonstrated promising improvements in clinical documentation, well-being, and cognitive load. However, further exploration across professional roles is warranted.
Author(s): Schneider, Kathryn R, Swann-Thomsen, Hillary E, Ribbens, Terry G, Bahnmaier, Lucas A, Satterfield, Trevor, Pullicar, Reme, Soni, Neeraj
DOI: 10.1093/jamia/ocag005
Author(s): Zablah, Jose, Molina, Yolly, Garcia Loureiro, Antonio
DOI: 10.1093/jamia/ocag023
Author(s): Cheng, Weihao
DOI: 10.1093/jamia/ocag022
Our study aims to assess the time-cost burden reduction of transitioning from manual case reporting to electronic case reporting (eCR) for COVID-19 among healthcare organizations (HCOs) over a 1-year period.
Author(s): Rincón-Guevara, Oscar, Olorukooba, Abdulhakeem A, Eau, Grace, Ritchey, Matthew D, Conn, Laura A, Knicely, Kimberly
DOI: 10.1093/jamia/ocag011
Efficient exchange of health information requires consistent representation of clinical concepts across laboratories, hospitals, and public health systems. LOINC supports this interoperability by standardizing laboratory test codes, but mapping remains difficult when datasets are incomplete, inconsistently formatted, or structurally diverse. These challenges often create a mismatch between algorithmic performance in controlled settings and real-world deployment. This study aimed to develop a biomedical natural language processing (NLP) approach for mapping heterogeneous [...]
Author(s): Naliyatthaliyazchayil, Parvati, Sangam, Venkat Ramana, Amlung, Joseph, Kanter, Andrew S, Purkayastha, Saptarshi, Payne, Jonathan
DOI: 10.1093/jamia/ocag010