JAMIA Article
Correction to: The Potential Implications of Informatics for Value-Based Care.
September 28, 2026
Author(s):
DOI: 10.1093/jamia/ocag165
Author(s):
DOI: 10.1093/jamia/ocag165
To externally validate a pediatric surgical site infection (SSI) prediction model, assess institutional and temporal transportability, and evaluate recalibration strategies to support adaptation of registry-derived predictions for clinical decision support (CDS).
Author(s): Chan, Carrie T, Pletcher, Mark J, Balakrishnan, Karthik, Hswen, Yulin, Scheffler, Aaron
DOI: 10.1093/jamia/ocag162
To develop an electronic health record (EHR)-based multimorbidity-weighted index (eMWI) using computable phenotypes mapped to the Observational Medical Outcomes Partnership (OMOP) common data model and previously validated physical functioning-based condition weights.
Author(s): Wei, Melissa Y, Kang, Ashley J, Klomhaus, Alexandra M, Chen, Lucia Y, Bell, Douglas S, Elashoff, David, Tseng, Chi-Hong
DOI: 10.1093/jamia/ocag161
Older adults face disproportionate risk of diagnostic errors in primary care, yet effective diagnostic decision support systems (DDSSs) remain lacking. Existing artificial intelligence (AI)-based DDSSs rely on gold-standard labels infeasible to obtain, have narrow diagnostic scope, and fail to reflect real-world uncertainty. We developed and validated a deep learning DDSS using imitation learning and collective clinician intelligence to generate diagnostic and order recommendations.
Author(s): Streiffer, Christopher D, Press, Matthew J, Bishop, Nicholas S, Schmid, Benjamin E, Sliwa, Alyssa, Vyas, Anuradha L, Ungar, Lyle H, Peifer, MaryAnne, Weissman, Gary E
DOI: 10.1093/jamia/ocag132
Pregnant and breastfeeding women, along with children, represent populations persistently underrepresented in clinical research, leading to uncertainty in clinical decision-making. This study investigated the landscape of pharmacology research concerning pharmacokinetics (PK), pharmaco-epidemiology (PE), and clinical trials (CT) within maternal and pediatric patient populations.
Author(s): Liu, Xiaofu, O'Kane, Aislinn M, Wang, Lei, Shendre, Aditi, Ma, Hanson, Zhang, Yichuan, Jiang, Haoran, Chiang, Chien-Wei, Zaidi, Syed S, Aboshady, Omar A, So, Gerald, Tillman, Emma M, Kirkpatrick, Lindsey M, Rahurkar, Saurabh, Cheng, Lijun, Ouyang, Jiayi, Wei, Ping, Zhu, Zhimo, Li, Shangjia, Huang, Yirui, Wang, Lingling, Cao, Weidan, Liu, Jianing, Oteng, Samuel-Richard, Goodwin, Andrew, Deypalubos, Jiezel Ann Faith, Zhang, Shijun, Bies, Robert, Quinney, Sara K, Li, Lang
DOI: 10.1093/jamia/ocag130
To develop and validate an open-source evaluation framework that assesses clinical AI diagnostic systems across multiple clinically relevant dimensions (accuracy, cost, time, invasiveness, physician effort, and safety behaviors), addressing the limitations of accuracy-only benchmarks.
Author(s): Sorka, Moran, Gorenshtein, Alon, Abramovitch, Hillel, Soontrapa, Pannathat, Shelly, Shahar, Aran, Dvir
DOI: 10.1093/jamia/ocag143
To understand how hospitals receive and use data on patients' health-related social needs (HRSN) from external sources, and how methods of receipt relate to use.
Author(s): Richwine, Chelsea, Chang, Wei, Iott, Bradley
DOI: 10.1093/jamia/ocag092
To examine the evolving role and application of SNOMED CT (SCT) during 2020-2025, a period marked by the COVID-19 pandemic and accelerated adoption of artificial intelligence (AI) in healthcare.
Author(s): Chang, Eunsuk, Mostafa, Javed
DOI: 10.1093/jamia/ocag094
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocag141
To determine whether a greater volume of health information exchange (HIE) between care delivery systems improves patient outcomes and whether effects differ between community care and Veterans Health Administration (VHA) direct care settings.
Author(s): Zhang, Abbie, Lipsey, Daniel, Figueroa, Stuart, Price, Megan E, Nebeker, Jonathan, Pan, Eric Chung Ren, Griffith, Kevin, Pizer, Steven D
DOI: 10.1093/jamia/ocag125