Correction to: Inpatient nurses' preferences and decisions with risk information visualization.
Author(s):
DOI: 10.1093/jamia/ocaf028
Author(s):
DOI: 10.1093/jamia/ocaf028
Author(s): Shyr, Cathy, Harris, Paul A
DOI: 10.1093/jamia/ocaf026
Effective postoperative care is crucial for the success of total joint arthroplasty (TJA) and prevention of unnecessary emergency department (ED) visits. We explore the feasibility and acceptability of utilizing an Interactive Voice Response System (IVRS) to enhance postoperative monitoring in primary TJA patients.
Author(s): Ayala-Ortiz, Jose L, McCrosson, Matthew, Jacob, Roshan, Vinoth, Aryan, Mehta, Tapan, Al-Hardan, Waleed, McGwin, Gerald, Naranje, Sameer
DOI: 10.1055/a-2539-1283
Developing equitable, sustainable informatics solutions is key to scalability and long-term success for projects in the global health informatics (GHI) domain. This paper presents key strategies for incorporating principles of health equity in the GHI project lifecycle.
Author(s): Campbell, Elizabeth, Bear Don't Walk, Oliver J, Fraser, Hamish, Gichoya, Judy, Wagholikar, Kavishwar B, Kanter, Andrew S, Holl, Felix, Craig, Sansanee
DOI: 10.1093/jamia/ocaf015
Digital health equity, the opportunity for all to engage with digital health tools to support good health outcomes, is an emerging priority across the world. The field of digital health equity would benefit from a comprehensive and systematic understanding of digital health, digital equity, and health equity, with a focus on real-world applications. We conducted a scoping review to identify and describe published frameworks and concepts relevant to digital health [...]
Author(s): Kim, Katherine K, Backonja, Uba
DOI: 10.1093/jamia/ocaf017
Objective Experiences sharing complex workflow-integrated clinical decision support (CDS) across health systems are sparse and not well reported. This case study presents the sharing of a hybrid electronic health record (EHR)-native and SMART-compatible CDS tool for automating provision of smoking cessation treatment for caregivers during pediatric visits. Materials & Methods We conducted a comprehensive needs assessment using socio-technical frameworks to identify workflow gaps and technical requirements. A multidisciplinary team of [...]
Author(s): Saleh, Sameh Nagui, Kim, Eric, Thayer, Jeritt G, Nabi, Emara, Karavite, Dean, Winickoff, Jonathan, Fiks, Alexander, Jenssen, Brian P, Riley, Nicholas, Grundmeier, Robert W
DOI: 10.1055/a-2535-5823
Applying large language models (LLMs) to the clinical domain is challenging due to the context-heavy nature of processing medical records. Retrieval-augmented generation (RAG) offers a solution by facilitating reasoning over large text sources. However, there are many parameters to optimize in just the retrieval system alone. This paper presents an ablation study exploring how different embedding models and pooling methods affect information retrieval for the clinical domain.
Author(s): Myers, Skatje, Miller, Timothy A, Gao, Yanjun, Churpek, Matthew M, Mayampurath, Anoop, Dligach, Dmitriy, Afshar, Majid
DOI: 10.1093/jamia/ocae308
To assess the potential to adapt an existing technology regulatory model, namely the Clinical Laboratory Improvement Amendments (CLIA), for clinical artificial intelligence (AI).
Author(s): Jackson, Brian R, Sendak, Mark P, Solomonides, Anthony, Balu, Suresh, Sittig, Dean F
DOI: 10.1093/jamia/ocae296
Event capture in clinical trials is resource-intensive, and electronic medical records (EMRs) offer a potential solution. This study develops algorithms for EMR-based death and hospitalization capture and compares them with traditional event capture methods.
Author(s): Rahafrooz, Maryam, Elbers, Danne C, Gopal, Jay R, Ren, Junling, Chan, Nathan H, Yildirim, Cenk, Desai, Akshay S, Santos, Abigail A, Murray, Karen, Havighurst, Thomas, Udell, Jacob A, Farkouh, Michael E, Cooper, Lawton, Gaziano, J Michael, Vardeny, Orly, Mao, Lu, Kim, KyungMann, Gagnon, David R, Solomon, Scott D, Joseph, Jacob
DOI: 10.1093/jamia/ocae303
The study aimed to assess the usage and impact of a private and secure instance of a generative artificial intelligence (GenAI) application in a large academic health center. The goal was to understand how employees interact with this technology and the influence on their perception of skill and work performance.
Author(s): Malhotra, Kiran, Wiesenfeld, Batia, Major, Vincent J, Grover, Himanshu, Aphinyanaphongs, Yindalon, Testa, Paul, Austrian, Jonathan S
DOI: 10.1093/jamia/ocae285