Letter to the Editor in response to "Application of a digital quality measure for cancer diagnosis in Epic Cosmos".
Author(s): Soppe, Sarah E, Metwally, Eman, Thompson, Caroline A
DOI: 10.1093/jamia/ocaf025
Author(s): Soppe, Sarah E, Metwally, Eman, Thompson, Caroline A
DOI: 10.1093/jamia/ocaf025
This study aims to evaluate the impact of using a large language model (LLM) for generating draft responses to patient messages in the electronic health record (EHR) system on clinicians and support staff workload and efficiency.We partnered with Epic Systems to implement OpenAI's ChatGPT 4.0 for responding to patient messages. A pilot study was conducted from August 2023 to July 2024 across 13 ambulatory specialties involving 323 participants, including clinicians [...]
Author(s): Proctor, Stephon, Lawton, Greg, Sinha, Shikha
DOI: 10.1055/a-2576-0579
This study develops and validates the confidence-linked and uncertainty-based staged (CLUES) framework by integrating large language models (LLMs) with uncertainty quantification to assist manual chart review while ensuring reliability through a selective human review.
Author(s): Lee, Sumin, Lee, Hyeok-Hee, Lee, Hokyou, Yum, Kyu Sun, Baek, Jang-Hyun, Khil, Jaewon, Lee, Jaeyong, Shin, Sojung, Cho, Minsung, Ahn, Na Yeon, You, Seng Chan, Kim, Hyeon Chang
DOI: 10.1093/jamia/ocaf099
Interruptive clinical decision support (CDS) alerts are intended to improve patient care, but can contribute to alert fatigue, diminishing their effectiveness. The alert demonstrated minimal clinical effect while contributing significantly to alert fatigue.This study aims to evaluate if transitioning a high-firing medication on hold alert from interruptive to noninterruptive would change provider practices.The alert was triggered when at least two medications were held for >48 hours. A pre-post intervention cohort study [...]
Author(s): Knake, Lindsey A, Kettelkamp, Joshua M, Bronson, Alison, Meyer, Nathan, Hacker, Kenneth, Blum, James M
DOI: 10.1055/a-2632-0605
Author(s):
DOI: 10.1093/jamia/ocaf098
This study aims to tackle the critical challenge of adapting deep learning (DL) models for deployment in real-world healthcare settings, specifically focusing on catastrophic forgetting due to distribution shifts between hospital and non-hospital environments. Metabolic syndrome (MetS) is susceptible to misdiagnosis by DL models due to distribution shifts. This work demonstrates the potential of continual learning (CL) to enhance model performance in MetS identification across diverse settings.
Author(s): Liu, Chang, Liu, Zhangdaihong, Liu, Jingjing, Cai, Chenglai, Clifton, David A, Wang, Hui, Yang, Yang
DOI: 10.1093/jamia/ocaf070
Immunotherapies have revolutionized the landscape of cancer treatments. However, our understanding of response patterns in advanced cancers treated with immunotherapy remains limited. By leveraging routinely collected noninvasive longitudinal and multimodal data with artificial intelligence, we could unlock the potential to transform immunotherapy for cancer patients, paving the way for personalized treatment approaches.
Author(s): Yeghaian, Melda, Bodalal, Zuhir, van den Broek, Daan, Haanen, John B A G, Beets-Tan, Regina G H, Trebeschi, Stefano, van Gerven, Marcel A J
DOI: 10.1093/jamia/ocaf074
In dentistry, social determinants of health (SDoH) are potentially recorded in the clinical notes of electronic dental records. The objective of this study was to examine the availability of SDoH data in dental clinical notes and evaluate natural language processing methods to extract SDoH from dental clinical notes.A set of 1,000 dental clinical notes was sampled from a dataset of 105,311 patient visits to a dental clinic and manually annotated [...]
Author(s): Pethani, Farhana, Chapman, Alec, Conway, Mike, Dai, Xiang, Bishay, Demiana, Choh, Victor, He, Alexander, Lim, Su-Elle, Ng, Huey Ying, Mahony, Tanya, Yaacoub, Albert, Karimi, Sarvnaz, Spallek, Heiko, Dunn, Adam G
DOI: 10.1055/a-2616-9858
Online healthcare portals provide access to electronic health information and support clinical communication. Almost no studies have examined perspectives on parental portal access. We aimed to characterize parental and adolescent perspectives on parental portal access.Semi-structured interviews with 51 dyads of parents and adolescents (102 total interviews). We stratified sampling for equal proportions of adolescents with and without chronic illnesses. We analyzed interview transcripts using thematic analysis.Parents and adolescents identified several [...]
Author(s): Sisk, Bryan A, Antes, Alison, Bereitschaft, Christine, Bourgeois, Fabienne, DuBois, James M
DOI: 10.1055/a-2605-4893
Author(s): Wang, Yu, Ye, Xin, Luo, Huiping, Feng, Wei
DOI: 10.1093/jamia/ocaf072