Measurement and automation of workflows for improved clinician interaction: upgrading EHRs for 21st century healthcare value.
Author(s): Bakken, Suzanne, Baker, Christina
DOI: 10.1093/jamia/ocac217
Author(s): Bakken, Suzanne, Baker, Christina
DOI: 10.1093/jamia/ocac217
How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced [...]
Author(s): Morris, Alan H, Horvat, Christopher, Stagg, Brian, Grainger, David W, Lanspa, Michael, Orme, James, Clemmer, Terry P, Weaver, Lindell K, Thomas, Frank O, Grissom, Colin K, Hirshberg, Ellie, East, Thomas D, Wallace, Carrie Jane, Young, Michael P, Sittig, Dean F, Suchyta, Mary, Pearl, James E, Pesenti, Antinio, Bombino, Michela, Beck, Eduardo, Sward, Katherine A, Weir, Charlene, Phansalkar, Shobha, Bernard, Gordon R, Thompson, B Taylor, Brower, Roy, Truwit, Jonathon, Steingrub, Jay, Hiten, R Duncan, Willson, Douglas F, Zimmerman, Jerry J, Nadkarni, Vinay, Randolph, Adrienne G, Curley, Martha A Q, Newth, Christopher J L, Lacroix, Jacques, Agus, Michael S D, Lee, Kang Hoe, deBoisblanc, Bennett P, Moore, Frederick Alan, Evans, R Scott, Sorenson, Dean K, Wong, Anthony, Boland, Michael V, Dere, Willard H, Crandall, Alan, Facelli, Julio, Huff, Stanley M, Haug, Peter J, Pielmeier, Ulrike, Rees, Stephen E, Karbing, Dan S, Andreassen, Steen, Fan, Eddy, Goldring, Roberta M, Berger, Kenneth I, Oppenheimer, Beno W, Ely, E Wesley, Pickering, Brian W, Schoenfeld, David A, Tocino, Irena, Gonnering, Russell S, Pronovost, Peter J, Savitz, Lucy A, Dreyfuss, Didier, Slutsky, Arthur S, Crapo, James D, Pinsky, Michael R, James, Brent, Berwick, Donald M
DOI: 10.1093/jamia/ocac143
A panel sponsored by the American College of Medical Informatics (ACMI) at the 2021 AMIA Symposium addressed the provocative question: "Are Electronic Health Records dumbing down clinicians?" After reviewing electronic health record (EHR) development and evolution, the panel discussed how EHR use can impair care delivery. Both suboptimal functionality during EHR use and longer-term effects outside of EHR use can reduce clinicians' efficiencies, reasoning abilities, and knowledge. Panel members explored [...]
Author(s): Melton, Genevieve B, Cimino, James J, Lehmann, Christoph U, Sengstack, Patricia R, Smith, Joshua C, Tierney, William M, Miller, Randolph A
DOI: 10.1093/jamia/ocac163
The Supreme Court recently overturned settled case law that affirmed a pregnant individual's Constitutional right to an abortion. While many states will commit to protect this right, a large number of others have enacted laws that limit or outright ban abortion within their borders. Additional efforts are underway to prevent pregnant individuals from seeking care outside their home state. These changes have significant implications for delivery of healthcare as well [...]
Author(s): Clayton, Ellen Wright, Embí, Peter J, Malin, Bradley A
DOI: 10.1093/jamia/ocac155
Expansive growth in the use of health information technology (HIT) has dramatically altered medicine without translating to fully realized improvements in healthcare delivery. Bridging this divide will require healthcare professionals with all levels of expertise in clinical informatics. However, due to scarce opportunities for exposure and training in informatics, medical students remain an underdeveloped source of potential informaticists. To address this gap, our institution developed and implemented a 5-tiered clinical [...]
Author(s): Hare, Allison J, Soegaard Ballester, Jacqueline M, Gabriel, Peter E, Adusumalli, Srinath, Hanson, C William
DOI: 10.1093/jamia/ocac209
A hallmark of personalized medicine and nutrition is to identify effective treatment plans at the individual level. Lifestyle interventions (LIs), from diet to exercise, can have a significant effect over time, especially in the case of food intolerances and allergies. The large set of candidate interventions, make it difficult to evaluate which intervention plan would be more favorable for any given individual. In this study, we aimed to develop a [...]
Author(s): Eetemadi, Ameen, Tagkopoulos, Ilias
DOI: 10.1093/jamia/ocac186
To develop and test an accurate deep learning model for predicting new onset delirium in hospitalized adult patients.
Author(s): Liu, Siru, Schlesinger, Joseph J, McCoy, Allison B, Reese, Thomas J, Steitz, Bryan, Russo, Elise, Koh, Brian, Wright, Adam
DOI: 10.1093/jamia/ocac210
To determine whether novel measures of contextual factors from multi-site electronic health record (EHR) audit log data can explain variation in clinical process outcomes.
Author(s): Rose, Christian, Thombley, Robert, Noshad, Morteza, Lu, Yun, Clancy, Heather A, Schlessinger, David, Li, Ron C, Liu, Vincent X, Chen, Jonathan H, Adler-Milstein, Julia
DOI: 10.1093/jamia/ocac201
To propose an approach for semantic and functional data harmonization related to sex and gender constructs in electronic health records (EHRs) and other clinical systems for implementors, as outlined in the National Academies of Sciences, Engineering, and Medicine (NASEM) report Measuring Sex, Gender Identity, and Sexual Orientation and the Health Level 7 (HL7) Gender Harmony Project (GHP) product brief "Gender Harmony-Modeling Sex and Gender Representation, Release 1."
Author(s): Baker, Kellan E, Compton, D'Lane, Fechter-Leggett, Ethan D, Grasso, Chris, Kronk, Clair A
DOI: 10.1093/jamia/ocac205
Distributed learning avoids problems associated with central data collection by training models locally at each site. This can be achieved by federated learning (FL) aggregating multiple models that were trained in parallel or training a single model visiting sites sequentially, the traveling model (TM). While both approaches have been applied to medical imaging tasks, their performance in limited local data scenarios remains unknown. In this study, we specifically analyze FL [...]
Author(s): Souza, Raissa, Mouches, Pauline, Wilms, Matthias, Tuladhar, Anup, Langner, Sönke, Forkert, Nils D
DOI: 10.1093/jamia/ocac204