Correction to: Research data warehouse best practices: catalyzing national data sharing through informatics innovation.
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DOI: 10.1093/jamia/ocac207
Author(s):
DOI: 10.1093/jamia/ocac207
Clinical decision support (CDS) alerts may improve health care quality but "alert fatigue" can reduce provider responsiveness. We analyzed how the introduction of competing alerts affected provider adherence to a single depression screening alert.
Author(s): Murad, Douglas A, Tsugawa, Yusuke, Elashoff, David A, Baldwin, Kevin M, Bell, Douglas S
DOI: 10.1093/jamia/ocac191
Inefficient workflows affect many health care stakeholders including patients, caregivers, clinicians, and staff. Widespread health information technology adoption and modern computing provide opportunities for more efficient health care workflows through automation. The Office of the National Coordinator for Health Information Technology (ONC) led a multidisciplinary effort with stakeholders across health care and experts in industrial engineering, computer science, and finance to explore opportunities for automation in health care. The effort [...]
Author(s): Zayas-Cabán, Teresa, Okubo, Tracy H, Posnack, Steven
DOI: 10.1093/jamia/ocac197
To evaluate and understand pregnant patients' perspectives on the implementation of artificial intelligence (AI) in clinical care with a focus on opportunities to improve healthcare technologies and healthcare delivery.
Author(s): Armero, William, Gray, Kathryn J, Fields, Kara G, Cole, Naida M, Bates, David W, Kovacheva, Vesela P
DOI: 10.1093/jamia/ocac200
Clinical informatics remains underappreciated among medical students in part due to a lack of integration into undergraduate medical education (UME). New developments in the study and practice of medicine are traditionally introduced via formal integration into undergraduate medical curricula. While this path has certain advantages, curricular changes are slow and may fail to showcase the breadth of clinical informatics activities. Less formal and more flexible approaches can circumvent these drawbacks [...]
Author(s): Quach, William T, Le, Chi H, Clark, Michael G, McArthur, Evonne, Ancker, Jessica S, Gadd, Cynthia S, Johnson, Kevin B
DOI: 10.1093/jamia/ocac189
Author(s): Alper, Brian S
DOI: 10.1093/jamia/ocac193
Privacy is a concern whenever individual patient health data is exchanged for scientific research. We propose using mixed sum-product networks (MSPNs) as private representations of data and take samples from the network to generate synthetic data that can be shared for subsequent statistical analysis. This anonymization method was evaluated with respect to privacy and information loss.
Author(s): Kroes, Shannon K S, van Leeuwen, Matthijs, Groenwold, Rolf H H, Janssen, Mart P
DOI: 10.1093/jamia/ocac184
Author(s): Petersen, Carolyn, Berner, Eta S, Cardillo, Anthony, Fultz Hollis, Kate, Goodman, Kenneth W, Koppel, Ross, Korngiebel, Diane M, Lehmann, Christoph U, Solomonides, Anthony E, Subbian, Vignesh
DOI: 10.1093/jamia/ocac192
Thoughtful integration of interruptive clinical decision support (CDS) alerts within the electronic health record is essential to guide clinicians on the application of pharmacogenomic results at point of care. St. Jude Children's Research Hospital implemented a preemptive pharmacogenomic testing program in 2011 in a multidisciplinary effort involving extensive education to clinicians about pharmacogenomic implications. We conducted a retrospective analysis of clinicians' adherence to 4783 pharmacogenomically guided CDS alerts that triggered [...]
Author(s): Nguyen, Jenny Q, Crews, Kristine R, Moore, Ben T, Kornegay, Nancy M, Baker, Donald K, Hasan, Murad, Campbell, Patrick K, Dean, Shannon M, Relling, Mary V, Hoffman, James M, Haidar, Cyrine E
DOI: 10.1093/jamia/ocac187
The coronavirus disease 2019 (COVID-19) pandemic has demonstrated the value of real-world data for public health research. International federated analyses are crucial for informing policy makers. Common data models (CDMs) are critical for enabling these studies to be performed efficiently. Our objective was to convert the UK Biobank, a study of 500 000 participants with rich genetic and phenotypic data to the Observational Medical Outcomes Partnership (OMOP) CDM.
Author(s): Papez, Vaclav, Moinat, Maxim, Voss, Erica A, Bazakou, Sofia, Van Winzum, Anne, Peviani, Alessia, Payralbe, Stefan, Kallfelz, Michael, Asselbergs, Folkert W, Prieto-Alhambra, Daniel, Dobson, Richard J B, Denaxas, Spiros
DOI: 10.1093/jamia/ocac203