Correction to: Returning value to communities from the All of Us Research Program through innovative approaches for data use, analysis, dissemination, and research capacity building.
Author(s):
DOI: 10.1093/jamia/ocaf100
Author(s):
DOI: 10.1093/jamia/ocaf100
To evaluate an automated reporting checklist generation tool using large language models and retrieval augmentation generation technology, called RAPID.
Author(s): Li, Zeming, Luo, Xufei, Yang, Zhenhua, Zhang, Huayu, Wang, Bingyi, Ge, Long, Bian, Zhaoxiang, Zou, James, Chen, Yaolong, Zhang, Lu, ,
DOI: 10.1093/jamia/ocaf093
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
Author(s): Patterson, Erica, Yan, Adam Paul, Silver, Shawna, Cardiff, Bren
DOI: 10.1055/a-2776-3303
Author(s): Hassan, Hadeel, Zipursky, Amy R, Rabbani, Naveed, You, Jacqueline G, Tse, Gabriel, Orenstein, Evan, Ray, Mondira, Parsons, Chase, Shin, Stella, Lawton, Gregory, Jessa, Karim, Sung, Lillian, Yan, Adam P
DOI: 10.1055/a-2790-1283
Electronic health record (EHR) usage measures may quantify physician activity at scale and predict practice settings with a high risk for physician burnout, but their relation to experiences is poorly understood.This study aimed to explore the EHR-related experiences and well-being of primary care physicians in comparison to EHR usage measures identified as important for predicting burnout from a machine learning model.Exploratory qualitative study with semi-structured interviews of primary care physicians [...]
Author(s): Tawfik, Daniel, Sebok-Syer, Stefanie S, Bragdon, Cassandra, Brown-Johnson, Cati, Winget, Marcy, Bayati, Mohsen, Shanafelt, Tait, Profit, Jochen
DOI: 10.1055/a-2595-0415
The patient-facing ASTHMAXcel mobile platform has been linked to improved asthma knowledge decreased asthma-related health care utilization (emergency department [ED] visits, hospitalizations), and reduced prednisone use among adult and pediatric patient populations.Given the upfront costs associated with developing mobile health platforms, this paper seeks to estimate the savings attributable to pediatric and adult users of the ASTHMAXcel platform through decreased hospitalizations, ED visits, and prednisone use.Forty adult patients and 39 [...]
Author(s): Nadelmann, Julia, Patel, Milin, Lane, Sarah, Hammock, James, Stark, Allison, Jariwala, Sunit P
DOI: 10.1055/a-2595-3329
While electronic health record (EHR)-based tools for refugee health screening exist, support for other immigrant children has lagged. Reasons include lack of time, difficulty determining screening eligibility, and lack of awareness of screening recommendations. EHR-based tools to promote immigrant child health screening (ICHS) can address these challenges, but guidance is needed for tools that are usable by clinicians and acceptable to immigrant families.Develop useful EHR-based tools to support ICHS while [...]
Author(s): Michel, Jeremy J, Karavite, Dean, White, Daniel, Mudenge, Nadège, Dawson-Hahn, Elizabeth, Yun, Katherine
DOI: 10.1055/a-2594-3633
Approximately 10% of patients have a documented penicillin "allergy"; however, up to 95% have subsequent negative testing. These patients may receive suboptimal antibiotics, leading to longer hospitalizations and higher costs, rates of resistant and nosocomial infections, and all-cause mortality. To mitigate these risks in children, we implemented an inpatient penicillin allergy delabeling protocol and integrated it into the electronic health record (EHR) through a mixed methods approach of clinical decision [...]
Author(s): Plattner, Alexander S, Lockowitz, Christine R, Same, Rebecca G, Abdelnour, Monica, Chin, Samuel, Cormier, Matthew J, Daugherty, Megan S, Grier, Alexandra E, Hampton, Nicholas B, Hofford, Mackenzie R, Mehta, Sarah S, Newland, Jason G, O'Bryan, Kevin S, Sattler, Matthew M, Shah, Mehr Z, Starnes, G Lucas, Yuenger, Valerie, Ellis, Alysa G, Facer, Evan E
DOI: 10.1055/a-2595-4849
Cancer staging is integral to ensuring cancer patients receive appropriate risk-adapted therapy. Discrete cancer staging using a structured staging form helps ensure accurate staging, provides a single source of truth for staging information, and allows for reporting to regulatory authorities. Our institution created pediatric oncology specific discrete staging forms that have been shared with the broader Epic community. By November 2023, baseline utilization of the staging form for patients with [...]
Author(s): Potashner, Renee, Yan, Adam P
DOI: 10.1055/a-2594-3722