Electronic Consultations (eConsults) for Safe and Equitable Coordination of Virtual Outpatient Specialty Care.
Author(s): Lee, Michelle S, Nambudiri, Vinod E
DOI: 10.1055/s-0040-1719181
Author(s): Lee, Michelle S, Nambudiri, Vinod E
DOI: 10.1055/s-0040-1719181
In the last decade, expanding use of health information technology (IT) across the United States has created opportunities for use of electronic health data for health services and biomedical research, but efforts may be hampered by limited data access, data quality, and system functionality. We identify five opportunities to advance the use of health IT for health services and biomedical research, which informed a federal government-led, collaborative effort to develop [...]
Author(s): Zayas-Cabán, Teresa, Wald, Jonathan S
DOI: 10.1093/jamiaopen/ooaa037
The study sought to describe the literature related to the development of methods for auditing the Unified Medical Language System (UMLS), with particular attention to identifying errors and inconsistencies of attributes of the concepts in the UMLS Metathesaurus.
Author(s): Zheng, Ling, He, Zhe, Wei, Duo, Keloth, Vipina, Fan, Jung-Wei, Lindemann, Luke, Zhu, Xinxin, Cimino, James J, Perl, Yehoshua
DOI: 10.1093/jamia/ocaa108
Concept normalization, the task of linking phrases in text to concepts in an ontology, is useful for many downstream tasks including relation extraction, information retrieval, etc. We present a generate-and-rank concept normalization system based on our participation in the 2019 National NLP Clinical Challenges Shared Task Track 3 Concept Normalization.
Author(s): Xu, Dongfang, Gopale, Manoj, Zhang, Jiacheng, Brown, Kris, Begoli, Edmon, Bethard, Steven
DOI: 10.1093/jamia/ocaa080
The study sought to evaluate the feasibility of using Unified Medical Language System (UMLS) semantic features for automated identification of reports about patient safety incidents by type and severity.
Author(s): Wang, Ying, Coiera, Enrico, Magrabi, Farah
DOI: 10.1093/jamia/ocaa082
To understand the impact of the shift to virtual medicine induced by coronavirus disease 2019 (COVID-19) has had on the workflow of medical scribes.
Author(s): Gold, Jeffrey A, Becton, James, Ash, Joan S, Corby, Sky, Mohan, Vishnu
DOI: 10.1055/s-0040-1721396
When hospitals are subject to prolonged surges in patients, such as during the coronavirus disease 2019 (COVID-19) pandemic, additional clinicians may be needed to care for the rapid increase of acutely ill patients. How might we quickly prepare a large number of ambulatory-based clinicians to care for hospitalized patients using the inpatient workflow of the electronic health record (EHR)?
Author(s): Altman, Richard L, Anstett, Tyler, Simpson, Jennifer R, Del Pino-Jones, Amira, Lin, Chen-Tan, Pell, Jonathan
DOI: 10.1055/s-0040-1719042
Although federal regulations mandate documentation of structured race data according to Office of Management and Budget (OMB) categories in electronic health record (EHR) systems, many institutions have reported gaps in EHR race data that hinder secondary use for population-level research focused on underserved populations. When evaluating race data available for research purposes, we found our institution's enterprise EHR contained structured race data for only 51% (1.6 million) of patients.
Author(s): Cusick, Marika M, Sholle, Evan T, Davila, Marcos A, Kabariti, Joseph, Cole, Curtis L, Campion, Thomas R
DOI: 10.1055/s-0040-1718756
We deployed a Remote Patient Monitoring (RPM) program to monitor patients with coronavirus disease 2019 (COVID-19) upon hospital discharge. We describe the patient characteristics, program characteristics, and clinical outcomes of patients in our RPM program.
Author(s): Gordon, William J, Henderson, Daniel, DeSharone, Avital, Fisher, Herrick N, Judge, Jessica, Levine, David M, MacLean, Laura, Sousa, Diane, Su, Mack Y, Boxer, Robert
DOI: 10.1055/s-0040-1721039
Geriatric clinical care is a multidisciplinary assessment designed to evaluate older patients' (age 65 years and above) functional ability, physical health, and cognitive well-being. The majority of these patients suffer from multiple chronic conditions and require special attention. Recently, hospitals utilize various artificial intelligence (AI) systems to improve care for elderly patients. The purpose of this systematic literature review is to understand the current use of AI systems, particularly machine [...]
Author(s): Choudhury, Avishek, Renjilian, Emily, Asan, Onur
DOI: 10.1093/jamiaopen/ooaa034