It is time for computable evidence synthesis: The COVID-19 Knowledge Accelerator initiative.
Author(s): Alper, Brian S, Richardson, Joshua E, Lehmann, Harold P, Subbian, Vignesh
DOI: 10.1093/jamia/ocaa114
Author(s): Alper, Brian S, Richardson, Joshua E, Lehmann, Harold P, Subbian, Vignesh
DOI: 10.1093/jamia/ocaa114
The study sought to evaluate early lessons from a remote patient monitoring engagement and education technology solution for patients with coronavirus disease 2019 (COVID-19) symptoms.
Author(s): Annis, Tucker, Pleasants, Susan, Hultman, Gretchen, Lindemann, Elizabeth, Thompson, Joshua A, Billecke, Stephanie, Badlani, Sameer, Melton, Genevieve B
DOI: 10.1093/jamia/ocaa097
The study sought to describe the development, implementation, and requirements of laboratory information system (LIS) functionality to manage test ordering, registration, sample flow, and result reporting during the coronavirus disease 2019 (COVID-19) pandemic.
Author(s): Weemaes, Matthias, Martens, Steven, Cuypers, Lize, Van Elslande, Jan, Hoet, Katrien, Welkenhuysen, Joris, Goossens, Ria, Wouters, Stijn, Houben, Els, Jeuris, Kirsten, Laenen, Lies, Bruyninckx, Katrien, Beuselinck, Kurt, André, Emmanuel, Depypere, Melissa, Desmet, Stefanie, Lagrou, Katrien, Van Ranst, Marc, Verdonck, Ann K L C, Goveia, Jermaine
DOI: 10.1093/jamia/ocaa081
Patient transitions into home health care (HHC) often occur without the transfer of information needed for critical clinical decisions and the plan of care. Owing to a lack of universally implemented standards, there is wide variation in information transfer. We sought to characterize missing information at HHC admission.
Author(s): Sockolow, Paulina S, Bowles, Kathryn H, Wojciechowicz, Christine, Bass, Ellen J
DOI: 10.1093/jamia/ocaa087
Evidence derived from existing health-care data, such as administrative claims and electronic health records, can fill evidence gaps in medicine. However, many claim such data cannot be used to estimate causal treatment effects because of the potential for observational study bias; for example, due to residual confounding. Other concerns include P hacking and publication bias. In response, the Observational Health Data Sciences and Informatics international collaborative launched the Large-scale Evidence [...]
Author(s): Schuemie, Martijn J, Ryan, Patrick B, Pratt, Nicole, Chen, RuiJun, You, Seng Chan, Krumholz, Harlan M, Madigan, David, Hripcsak, George, Suchard, Marc A
DOI: 10.1093/jamia/ocaa103
The US National Library of Medicine regularly collects summary data on direct use of Unified Medical Language System (UMLS) resources. The summary data sources include UMLS user registration data, required annual reports submitted by registered users, and statistics on downloads and application programming interface calls. In 2019, the National Library of Medicine analyzed the summary data on 2018 UMLS use. The library also conducted a scoping review of the literature [...]
Author(s): Amos, Liz, Anderson, David, Brody, Stacy, Ripple, Anna, Humphreys, Betsy L
DOI: 10.1093/jamia/ocaa084
The study sought to examine the association between clinician burnout and measures of electronic health record (EHR) workload and efficiency, using vendor-derived EHR action log data.
Author(s): Hilliard, Ross W, Haskell, Jacqueline, Gardner, Rebekah L
DOI: 10.1093/jamia/ocaa092
Coordination ellipsis is a linguistic phenomenon abound in medical text and is challenging for concept normalization because of difficulty in recognizing elliptical expressions referencing 2 or more entities accurately. To resolve this bottleneck, we aim to contribute a generalizable method to reconstruct concepts from medical coordinated elliptical expressions in a variety of biomedical corpora.
Author(s): Yuan, Chi, Wang, Yongli, Shang, Ning, Li, Ziran, Zhao, Ruxin, Weng, Chunhua
DOI: 10.1093/jamia/ocaa109
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocaa132