Corrigendum to: Real world evidence in cardiovascular medicine: assuring data validity in electronic health record-based studies.
Author(s):
DOI: 10.1093/jamia/ocz184
Author(s):
DOI: 10.1093/jamia/ocz184
We aimed to impute uncoded self-harm in administrative claims data of individuals with major mental illness (MMI), characterize self-harm incidence, and identify factors associated with coding bias.
Author(s): Kumar, Praveen, Nestsiarovich, Anastasiya, Nelson, Stuart J, Kerner, Berit, Perkins, Douglas J, Lambert, Christophe G
DOI: 10.1093/jamia/ocz173
This study focuses on the task of automatically assigning standardized (topical) subject headings to free-text sentences in clinical nursing notes. The underlying motivation is to support nurses when they document patient care by developing a computer system that can assist in incorporating suitable subject headings that reflect the documented topics. Central in this study is performance evaluation of several text classification methods to assess the feasibility of developing such a [...]
Author(s): Moen, Hans, Hakala, Kai, Peltonen, Laura-Maria, Suhonen, Henry, Ginter, Filip, Salakoski, Tapio, Salanterä, Sanna
DOI: 10.1093/jamia/ocz150
Linking emergency medical services (EMS) electronic patient care reports (ePCRs) to emergency department (ED) records can provide clinicians access to vital information that can alter management. It can also create rich databases for research and quality improvement. Unfortunately, previous attempts at ePCR and ED record linkage have had limited success. In this study, we use supervised machine learning to derive and validate an automated record linkage algorithm between EMS ePCRs [...]
Author(s): Redfield, Colby, Tlimat, Abdulhakim, Halpern, Yoni, Schoenfeld, David W, Ullman, Edward, Sontag, David A, Nathanson, Larry A, Horng, Steven
DOI: 10.1093/jamia/ocz176
The study sought to describe the literature describing clinical reasoning ontology (CRO)-based clinical decision support systems (CDSSs) and identify and classify the medical knowledge and reasoning concepts and their properties within these ontologies to guide future research.
Author(s): Dissanayake, Pavithra I, Colicchio, Tiago K, Cimino, James J
DOI: 10.1093/jamia/ocz169
Electronic medical records (EMRs) can support medical research and discovery, but privacy risks limit the sharing of such data on a wide scale. Various approaches have been developed to mitigate risk, including record simulation via generative adversarial networks (GANs). While showing promise in certain application domains, GANs lack a principled approach for EMR data that induces subpar simulation. In this article, we improve EMR simulation through a novel pipeline that [...]
Author(s): Zhang, Ziqi, Yan, Chao, Mesa, Diego A, Sun, Jimeng, Malin, Bradley A
DOI: 10.1093/jamia/ocz161
Our objectives were to identify educational interventions designed to equip medical students or residents with knowledge or skills related to various uses of electronic health records (EHRs), summarize and synthesize the results of formal evaluations of these initiatives, and compare the aims of these initiatives with the prescribed EHR-specific competencies for undergraduate and postgraduate medical education.
Author(s): Rajaram, Akshay, Hickey, Zachary, Patel, Nimesh, Newbigging, Joseph, Wolfrom, Brent
DOI: 10.1093/jamia/ocz178
Many policymakers and advocates assume that directed and query-based health information exchange (HIE) work together to meet organizations' interoperability needs, but this is not grounded in a substantial evidence base. This study sought to clarify the relationship between the usage of these 2 approaches to HIE.
Author(s): Vest, Joshua R, Unruh, Mark A, Casalino, Lawrence P, Shapiro, Jason S
DOI: 10.1093/jamia/ocz134
The study sought to assess the feasibility of nationwide chronic disease surveillance using data aggregated through a multisite collaboration of customers of the same electronic health record (EHR) platform across the United States.
Author(s): Tarabichi, Yasir, Goyden, Jake, Liu, Rujia, Lewis, Steven, Sudano, Joseph, Kaelber, David C
DOI: 10.1093/jamia/ocz172
Academic medical centers and health systems are increasingly challenged with supporting appropriate secondary use of clinical data. Enterprise data warehouses have emerged as central resources for these data, but often require an informatician to extract meaningful information, limiting direct access by end users. To overcome this challenge, we have developed Leaf, a lightweight self-service web application for querying clinical data from heterogeneous data models and sources.
Author(s): Dobbins, Nicholas J, Spital, Clifford H, Black, Robert A, Morrison, Jason M, de Veer, Bas, Zampino, Elizabeth, Harrington, Robert D, Britt, Bethene D, Stephens, Kari A, Wilcox, Adam B, Tarczy-Hornoch, Peter, Mooney, Sean D
DOI: 10.1093/jamia/ocz165