Predictive models: important problems and innovative methods.
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocab274
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocab274
Developing a diverse informatics workforce broadens the research agenda and ensures the growth of innovative solutions that enable equity-centered care. The American Medical Informatics Association (AMIA) established the AMIA First Look Program in 2017 to address workforce disparities among women, including those from marginalized communities. The program exposes women to informatics, furnishes mentors, and provides career resources. In 4 years, the program has introduced 87 undergraduate women, 41% members of [...]
Author(s): Bright, Tiffani J, Williams, Karmen S, Rajamani, Sripriya, Tiase, Victoria L, Senathirajah, Yalini, Hebert, Courtney, McCoy, Allison B
DOI: 10.1093/jamia/ocab246
Guidance is needed on studying engagement and treatment effects in digital health interventions, including levels required for benefit. We evaluated multiple analytic approaches for understanding the association between engagement and clinical outcomes.
Author(s): Nelson, Lyndsay A, Spieker, Andrew J, Mayberry, Lindsay S, McNaughton, Candace, Greevy, Robert A
DOI: 10.1093/jamia/ocab254
To characterize variation in clinical documentation production patterns, how this variation relates to individual resident behavior preferences, and how these choices relate to work hours.
Author(s): Gong, Jen J, Soleimani, Hossein, Murray, Sara G, Adler-Milstein, Julia
DOI: 10.1093/jamia/ocab253
Hospital-acquired infections (HAIs) are associated with significant morbidity, mortality, and prolonged hospital length of stay. Risk prediction models based on pre- and intraoperative data have been proposed to assess the risk of HAIs at the end of the surgery, but the performance of these models lag behind HAI detection models based on postoperative data. Postoperative data are more predictive than pre- or interoperative data since it is closer to the [...]
Author(s): Yang, Haoyu, Tourani, Roshan, Zhu, Ying, Kumar, Vipin, Melton, Genevieve B, Steinbach, Michael, Simon, Gyorgy
DOI: 10.1093/jamia/ocab229
Frailty is a prevalent risk factor for adverse outcomes among patients with chronic lung disease. However, identifying frail patients who may benefit from interventions is challenging using standard data sources. We therefore sought to identify phrases in clinical notes in the electronic health record (EHR) that describe actionable frailty syndromes.
Author(s): Martin, Jacob A, Crane-Droesch, Andrew, Lapite, Folasade C, Puhl, Joseph C, Kmiec, Tyler E, Silvestri, Jasmine A, Ungar, Lyle H, Kinosian, Bruce P, Himes, Blanca E, Hubbard, Rebecca A, Diamond, Joshua M, Ahya, Vivek, Sims, Michael W, Halpern, Scott D, Weissman, Gary E
DOI: 10.1093/jamia/ocab248
Clinical registries-structured databases of demographic, diagnosis, and treatment information-play vital roles in retrospective studies, operational planning, and assessment of patient eligibility for research, including clinical trials. Registry curation, a manual and time-intensive process, is always costly and often impossible for rare or underfunded diseases. Our goal was to evaluate the feasibility of natural language inference (NLI) as a scalable solution for registry curation.
Author(s): Percha, Bethany, Pisapati, Kereeti, Gao, Cynthia, Schmidt, Hank
DOI: 10.1093/jamia/ocab243
Author(s): Daymont, Carrie, Ross, Michelle E, Localio, A Russell, Fiks, Alexander G, Wasserman, Richard C, Grundmeier, Robert W
DOI: 10.1093/jamia/ocab250
This article reports a systematic review of studies containing development and validation of models predicting postacute care destination after adult inpatient hospitalization, summarizes clinical populations and variables, evaluates model performance, assesses risk of bias and applicability, and makes recommendations to reduce bias in future models.
Author(s): Kennedy, Erin E, Bowles, Kathryn H, Aryal, Subhash
DOI: 10.1093/jamia/ocab197
Chatbots are software applications to simulate a conversation with a person. The effectiveness of chatbots in facilitating the recruitment of study participants in research, specifically among racial and ethnic minorities, is unknown. The objective of this study is to compare a chatbot versus telephone-based recruitment in enrolling research participants from a predominantly minority patient population at an urban institution. We randomly allocated adults to receive either chatbot or telephone-based outreach [...]
Author(s): Kim, Yoo Jin, DeLisa, Julie A, Chung, Yu-Che, Shapiro, Nancy L, Kolar Rajanna, Subhash K, Barbour, Edward, Loeb, Jeffrey A, Turner, Justin, Daley, Susan, Skowlund, John, Krishnan, Jerry A
DOI: 10.1093/jamia/ocab240