Author(s): Lu, Chris J, Payne, Amanda, Mork, James G
DOI: 10.1093/jamia/ocaa313
Author(s): Jalali, Mohammad S, Landman, Adam, Gordon, William J
DOI: 10.1093/jamia/ocaa310
Normalizing mentions of medical concepts to standardized vocabularies is a fundamental component of clinical text analysis. Ambiguity-words or phrases that may refer to different concepts-has been extensively researched as part of information extraction from biomedical literature, but less is known about the types and frequency of ambiguity in clinical text. This study characterizes the distribution and distinct types of ambiguity exhibited by benchmark clinical concept normalization datasets, in order to [...]
Author(s): Newman-Griffis, Denis, Divita, Guy, Desmet, Bart, Zirikly, Ayah, Rosé, Carolyn P, Fosler-Lussier, Eric
DOI: 10.1093/jamia/ocaa269
The study sought to evaluate if peer input on outpatient cases impacted diagnostic confidence.
Author(s): Khoong, Elaine C, Fontil, Valy, Rivadeneira, Natalie A, Hoskote, Mekhala, Nundy, Shantanu, Lyles, Courtney R, Sarkar, Urmimala
DOI: 10.1093/jamia/ocaa278
Tuberculosis is the leading cause of death from a single infectious agent. The emergence of antimicrobial resistant Mycobacterium tuberculosis strains makes the problem more severe. Pyrazinamide (PZA) is an important component for short-course treatment regimens and first- and second-line treatment regimens. This research aims for fast diagnosis of M. tuberculosis resistance to PZA and identification of genetic features causing resistance.
Author(s): Zhang, Andrew, Teng, Ling, Alterovitz, Gil
DOI: 10.1093/jamia/ocaa233
Digital medical records have enabled us to employ clinical data in many new and innovative ways. However, these advances have brought with them a complex set of demands for healthcare institutions regarding data sharing with topics such as data ownership, the loss of privacy, and the protection of the intellectual property. The lack of clear guidance from government entities often creates conflicting messages about data policy, leaving institutions to develop [...]
Author(s): Cole, Curtis L, Sengupta, Soumitra, Rossetti Née Collins, Sarah, Vawdrey, David K, Halaas, Michael, Maddox, Thomas M, Gordon, Geoff, Dave, Trushna, Payne, Philip R O, Williams, Andrew E, Estrin, Deborah
DOI: 10.1093/jamia/ocaa260
To present clinicians at the point-of-care with real-world data on the effectiveness of various treatment options in a precision cohort of patients closely matched to the index patient.
Author(s): Tang, Paul C, Miller, Sarah, Stavropoulos, Harry, Kartoun, Uri, Zambrano, John, Ng, Kenney
DOI: 10.1093/jamia/ocaa247
The study sought to describe the contributions of clinical informatics (CI) fellows to their institutions' coronavirus disease 2019 (COVID-19) response.
Author(s): Subash, Meera, Sakumoto, Matthew, Bass, Jeremy, Hong, Peter, Muniyappa, Anoop, Pierce, Logan, Purmal, Colin, Ramaswamy, Priya, Sono, Reiri, Uptegraft, Colby, Feinstein, David, Khanna, Raman
DOI: 10.1093/jamia/ocaa241
Large clinical databases are increasingly used for research and quality improvement. We describe an approach to data quality assessment from the General Medicine Inpatient Initiative (GEMINI), which collects and standardizes administrative and clinical data from hospitals.
Author(s): Verma, Amol A, Pasricha, Sachin V, Jung, Hae Young, Kushnir, Vladyslav, Mak, Denise Y F, Koppula, Radha, Guo, Yishan, Kwan, Janice L, Lapointe-Shaw, Lauren, Rawal, Shail, Tang, Terence, Weinerman, Adina, Razak, Fahad
DOI: 10.1093/jamia/ocaa225