Quantitative and qualitative methods advance the science of clinical workflow research.
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocad056
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocad056
This study aimed to assess Uganda's readiness for implementing a national Point-of-Care (PoC) electronic clinical data capture platform that can function in near real-time.
Author(s): Nabukenya, Josephine, Egwar, Andrew Alunyu, Drumright, Lydia, Semwanga, Agnes Rwashana, Kasasa, Simon
DOI: 10.1093/jamia/ocad034
The development of phenotypes using electronic health records is a resource-intensive process. Therefore, the cataloging of phenotype algorithm metadata for reuse is critical to accelerate clinical research. The Department of Veterans Affairs (VA) has developed a standard for phenotype metadata collection which is currently used in the VA phenomics knowledgebase library, CIPHER (Centralized Interactive Phenomics Resource), to capture over 5000 phenotypes. The CIPHER standard improves upon existing phenotype library metadata [...]
Author(s): Honerlaw, Jacqueline, Ho, Yuk-Lam, Fontin, Francesca, Gosian, Jeffrey, Maripuri, Monika, Murray, Michael, Sangar, Rahul, Galloway, Ashley, Zimolzak, Andrew J, Whitbourne, Stacey B, Casas, Juan P, Ramoni, Rachel B, Gagnon, David R, Cai, Tianxi, Liao, Katherine P, Gaziano, J Michael, Muralidhar, Sumitra, Cho, Kelly
DOI: 10.1093/jamia/ocad030
Observational studies can impact patient care but must be robust and reproducible. Nonreproducibility is primarily caused by unclear reporting of design choices and analytic procedures. This study aimed to: (1) assess how the study logic described in an observational study could be interpreted by independent researchers and (2) quantify the impact of interpretations' variability on patient characteristics.
Author(s): Ostropolets, Anna, Albogami, Yasser, Conover, Mitchell, Banda, Juan M, Baumgartner, William A, Blacketer, Clair, Desai, Priyamvada, DuVall, Scott L, Fortin, Stephen, Gilbert, James P, Golozar, Asieh, Ide, Joshua, Kanter, Andrew S, Kern, David M, Kim, Chungsoo, Lai, Lana Y H, Li, Chenyu, Liu, Feifan, Lynch, Kristine E, Minty, Evan, Neves, Maria Inês, Ng, Ding Quan, Obene, Tontel, Pera, Victor, Pratt, Nicole, Rao, Gowtham, Rappoport, Nadav, Reinecke, Ines, Saroufim, Paola, Shoaibi, Azza, Simon, Katherine, Suchard, Marc A, Swerdel, Joel N, Voss, Erica A, Weaver, James, Zhang, Linying, Hripcsak, George, Ryan, Patrick B
DOI: 10.1093/jamia/ocad009
Vaccines are crucial components of pandemic responses. Over 12 billion coronavirus disease 2019 (COVID-19) vaccines were administered at the time of writing. However, public perceptions of vaccines have been complex. We integrated social media and surveillance data to unravel the evolving perceptions of COVID-19 vaccines.
Author(s): Wang, Hanyin, Li, Yikuan, Hutch, Meghan R, Kline, Adrienne S, Otero, Sebastian, Mithal, Leena B, Miller, Emily S, Naidech, Andrew, Luo, Yuan
DOI: 10.1093/jamia/ocad029
The All of Us Research Program makes individual-level data available to researchers while protecting the participants' privacy. This article describes the protections embedded in the multistep access process, with a particular focus on how the data was transformed to meet generally accepted re-identification risk levels.
Author(s): Xia, Weiyi, Basford, Melissa, Carroll, Robert, Clayton, Ellen Wright, Harris, Paul, Kantacioglu, Murat, Liu, Yongtai, Nyemba, Steve, Vorobeychik, Yevgeniy, Wan, Zhiyu, Malin, Bradley A
DOI: 10.1093/jamia/ocad021
We conducted a systematic review to characterize and critically appraise developed prediction models based on structured electronic health record (EHR) data for adverse drug event (ADE) diagnosis and prognosis in adult hospitalized patients.
Author(s): Yasrebi-de Kom, Izak A R, Dongelmans, Dave A, de Keizer, Nicolette F, Jager, Kitty J, Schut, Martijn C, Abu-Hanna, Ameen, Klopotowska, Joanna E
DOI: 10.1093/jamia/ocad014
There are over 363 customized risk models of the American College of Cardiology and the American Heart Association (ACC/AHA) pooled cohort equations (PCE) in the literature, but their gains in clinical utility are rarely evaluated. We build new risk models for patients with specific comorbidities and geographic locations and evaluate whether performance improvements translate to gains in clinical utility.
Author(s): Xu, Yizhe, Foryciarz, Agata, Steinberg, Ethan, Shah, Nigam H
DOI: 10.1093/jamia/ocad017
Post-acute sequalae of SARS-CoV-2 infection (PASC) is not well defined in pediatrics given its heterogeneity of presentation and severity in this population. The aim of this study is to use novel methods that rely on data mining approaches rather than clinical experience to detect conditions and symptoms associated with pediatric PASC.
Author(s): Lorman, Vitaly, Rao, Suchitra, Jhaveri, Ravi, Case, Abigail, Mejias, Asuncion, Pajor, Nathan M, Patel, Payal, Thacker, Deepika, Bose-Brill, Seuli, Block, Jason, Hanley, Patrick C, Prahalad, Priya, Chen, Yong, Forrest, Christopher B, Bailey, L Charles, Lee, Grace M, Razzaghi, Hanieh
DOI: 10.1093/jamiaopen/ooad016
This study aimed to understand how a metaverse-based (virtual) workspace can be used to support the communication and collaboration in an academic health informatics lab.
Author(s): Zhu, Siyi, Vennemeyer, Scott, Xu, Catherine, Wu, Danny T Y
DOI: 10.1093/jamiaopen/ooad010