Correction to: Predicting risk of metastases and recurrence in soft-tissue sarcomas via Radiomics and Formal Methods.
[This corrects the article DOI: 10.1093/jamiaopen/ooad025.].
Author(s):
DOI: 10.1093/jamiaopen/ooad064
[This corrects the article DOI: 10.1093/jamiaopen/ooad025.].
Author(s):
DOI: 10.1093/jamiaopen/ooad064
Clinical decision support (CDS) alerts can aid in improving patient care. One CDS functionality is the Best Practice Advisory (BPA) alert notification system, wherein BPA alerts are automated alerts embedded in the hospital's electronic medical records (EMR). However, excessive alerts can change clinician behavior; redundant and repetitive alerts can contribute to alert fatigue. Alerts can be optimized through a multipronged strategy. Our study aims to describe these strategies adopted and [...]
Author(s): Ng, Hannah Jia Hui, Kansal, Amit, Abdul Naseer, Jishana Farhad, Hing, Wee Chuan, Goh, Carmen Jia Man, Poh, Hermione, D'souza, Jared Louis Andre, Lim, Er Luen, Tan, Gamaliel
DOI: 10.1093/jamiaopen/ooad056
To describe the infrastructure, tools, and services developed at Stanford Medicine to maintain its data science ecosystem and research patient data repository for clinical and translational research.
Author(s): Callahan, Alison, Ashley, Euan, Datta, Somalee, Desai, Priyamvada, Ferris, Todd A, Fries, Jason A, Halaas, Michael, Langlotz, Curtis P, Mackey, Sean, Posada, José D, Pfeffer, Michael A, Shah, Nigam H
DOI: 10.1093/jamiaopen/ooad054
Public health information systems have historically been siloed with limited interoperability. The State of Minnesota's disease surveillance system (Minnesota Electronic Disease Surveillance System: MEDSS, ∼12 million total reportable events) and immunization information system (Minnesota Immunization Information Connection: MIIC, ∼130 million total immunizations) lacked interoperability between them and data exchange was fully manual. An interoperability tool based on national standards (HL7 and SOAP/web services) for query and response was developed for electronic [...]
Author(s): Rajamani, Sripriya, Chakoian, Hanna, Bieringer, Aaron, Lintelmann, Anna, Sanders, Jeffrey, Ostadkar, Rachel, Saupe, Amy, Grilli, Genny, White, Katie, Solarz, Sarah, Melton, Genevieve B
DOI: 10.1093/jamiaopen/ooad055
To define pregnancy episodes and estimate gestational age within electronic health record (EHR) data from the National COVID Cohort Collaborative (N3C).
Author(s): Jones, Sara E, Bradwell, Katie R, Chan, Lauren E, McMurry, Julie A, Olson-Chen, Courtney, Tarleton, Jessica, Wilkins, Kenneth J, Ly, Victoria, Ljazouli, Saad, Qin, Qiuyuan, Faherty, Emily Groene, Lau, Yan Kwan, Xie, Catherine, Kao, Yu-Han, Liebman, Michael N, Mariona, Federico, Challa, Anup P, Li, Li, Ratcliffe, Sarah J, Haendel, Melissa A, Patel, Rena C, Hill, Elaine L, ,
DOI: 10.1093/jamiaopen/ooad067
This study aims to identify the people living with HIV (PWH) and pre-exposure prophylaxis (PrEP) users in the All of Us (AoU) database by integrating information from both electronic health record (EHR)- and self-reported survey data.
Author(s): Yang, Xueying, Zhang, Jiajia, Cai, Ruilie, Liang, Chen, Olatosi, Bankole, Weissman, Sharon, Li, Xiaoming
DOI: 10.1093/jamiaopen/ooad071
Patient-reported outcome measures (PROMs) are critical to drive patient-centered care and to understanding patients' perspectives on their health status, quality of life, and the overall effectiveness of the care they receive. PROMs are increasingly being used in clinical and research settings, but the mechanisms to aggregate data from different systems can be cumbersome.
Author(s): Espinoza, Juan, Tut, Maurice, Shah, Payal, Kingsbury, Paul, Nagaraj, Gayathri, Meeker, Daniella, Bahroos, Neil
DOI: 10.1093/jamiaopen/ooad074
Text messages used by healthcare organizations to communicate with patients have known limitations for certain populations, especially older adults. This study analyzed text message interactions with over 17 000 patients aged 65 and older during the initial phase of the COVID-19 vaccination campaign. We coded the responses of 4247 patients who responded to this outreach to understand issues they experienced with the text message system. Our analysis highlighted areas for technology [...]
Author(s): Gwynne, Kaelyn, Ratwani, Raj, Dixit, Ram
DOI: 10.1093/jamiaopen/ooad066
We have previously developed a natural language processing pipeline using clinical notes written by epilepsy specialists to extract seizure freedom, seizure frequency text, and date of last seizure text for patients with epilepsy. It is important to understand how our methods generalize to new care contexts.
Author(s): Xie, Kevin, Terman, Samuel W, Gallagher, Ryan S, Hill, Chloe E, Davis, Kathryn A, Litt, Brian, Roth, Dan, Ellis, Colin A
DOI: 10.1093/jamiaopen/ooad070
Efficiently identifying the social risks of patients with serious illnesses (SIs) is the critical first step in providing patient-centered and value-driven care for this medically vulnerable population.
Author(s): Xie, Fagen, Wang, Susan, Viveros, Lori, Rich, Allegra, Nguyen, Huong Q, Padilla, Ariadna, Lyons, Lindsey, Nau, Claudia L
DOI: 10.1093/jamiaopen/ooad082