Correction to: Predicting risk of metastases and recurrence in soft-tissue sarcomas via Radiomics and Formal Methods.
[This corrects the article DOI: 10.1093/jamiaopen/ooad025.].
Author(s):
DOI: 10.1093/jamiaopen/ooad064
[This corrects the article DOI: 10.1093/jamiaopen/ooad025.].
Author(s):
DOI: 10.1093/jamiaopen/ooad064
Clinical decision support (CDS) alerts can aid in improving patient care. One CDS functionality is the Best Practice Advisory (BPA) alert notification system, wherein BPA alerts are automated alerts embedded in the hospital's electronic medical records (EMR). However, excessive alerts can change clinician behavior; redundant and repetitive alerts can contribute to alert fatigue. Alerts can be optimized through a multipronged strategy. Our study aims to describe these strategies adopted and [...]
Author(s): Ng, Hannah Jia Hui, Kansal, Amit, Abdul Naseer, Jishana Farhad, Hing, Wee Chuan, Goh, Carmen Jia Man, Poh, Hermione, D'souza, Jared Louis Andre, Lim, Er Luen, Tan, Gamaliel
DOI: 10.1093/jamiaopen/ooad056
It has been documented that nurses' use of electronic health records (EHRs) impacts clients' health outcomes positively. Some health facilities, primarily privately owned institutions, introduced EHRs for optimal healthcare. Evidence of such and associated factors among nurses must be documented to improve utilization and quality.
Author(s): Ayamolowo, Love B, Irinoye, Omolola O, Olaniyan, Abayomi S
DOI: 10.1093/jamiaopen/ooad059
Weak supervision holds significant promise to improve clinical natural language processing by leveraging domain resources and expertise instead of large manually annotated datasets alone. Here, our objective is to evaluate a weak supervision approach to extract spatial information from radiology reports.
Author(s): Datta, Surabhi, Roberts, Kirk
DOI: 10.1093/jamiaopen/ooad027
The aim of this study was to design and assess the formative usability of a novel patient portal intervention designed to empower patients with diabetes to initiate orders for diabetes-related monitoring and preventive services.
Author(s): Nelson, Lyndsay A, Reale, Carrie, Anders, Shilo, Beebe, Russ, Rosenbloom, S Trent, Hackstadt, Amber, Harper, Kryseana J, Mayberry, Lindsay S, Cobb, Jared G, Peterson, Neeraja, Elasy, Tom, Yu, Zhihong, Martinez, William
DOI: 10.1093/jamiaopen/ooad030
When correcting for the "class imbalance" problem in medical data, the effects of resampling applied on classifier algorithms remain unclear. We examined the effect on performance over several combinations of classifiers and resampling ratios.
Author(s): Welvaars, Koen, Oosterhoff, Jacobien H F, van den Bekerom, Michel P J, Doornberg, Job N, van Haarst, Ernst P, ,
DOI: 10.1093/jamiaopen/ooad033
To develop the architecture for a clinical decision support system (CDSS) linked to the electronic health record (EHR) using the tools provided by Research Electronic Data Capture (REDCap) to assess medication appropriateness in older adults with polypharmacy.
Author(s): Charpentier, Peter A, Mecca, Marcia C, Brandt, Cynthia, Fried, Terri R
DOI: 10.1093/jamiaopen/ooad041
Electronic health records and many legacy systems contain rich longitudinal data that can be used for research; however, they typically are not readily available.
Author(s): Chen, Wansu, Xie, Fagen, Mccarthy, Don P, Reynolds, Kristi L, Lee, Mingsum, Coleman, Karen J, Getahun, Darios, Koebnick, Corinna, Jacobsen, Steve J
DOI: 10.1093/jamiaopen/ooad039
Studies that combine medical record and primary data are typically conducted in a small number of health care facilities (HCFs) covering a limited catchment area; however, depending on the study objectives, validity may be improved by recruiting a more expansive sample of patients receiving care across multiple HCFs. We evaluate the feasibility of a novel protocol to obtain patient medical records from multiple HCFs using a broad representative sampling frame.
Author(s): McMahon, James M, Brasch, Judith, Podsiadly, Eric, Torres, Leilani, Quiles, Robert, Ramos, Evette, Crean, Hugh F, Haberer, Jessica E
DOI: 10.1093/jamiaopen/ooad040
Introduce the CDS-Sandbox, a cloud-based virtual machine created to facilitate Clinical Decision Support (CDS) developers and implementers in the use of FHIR- and CQL-based open-source tools and technologies for building and testing CDS artifacts.
Author(s): Soares, Andrey, Afshar, Majid, Moesel, Chris, Grasso, Michael A, Pan, Eric, Solomonides, Anthony, Richardson, Joshua E, Barone, Eleanor, Lomotan, Edwin A, Schilling, Lisa M
DOI: 10.1093/jamiaopen/ooad038