Innovative informatics interventions to improve health and health care.
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocac255
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocac255
There is increasing interest in using artificial intelligence (AI) in pathology to improve accuracy and efficiency. Studies of clinicians' perceptions of AI have found only moderate acceptability, suggesting further research is needed regarding integration into clinical practice. This study aimed to explore stakeholders' theories concerning how and in what contexts AI is likely to become integrated into pathology.
Author(s): King, Henry, Williams, Bethany, Treanor, Darren, Randell, Rebecca
DOI: 10.1093/jamia/ocac254
While opioid addiction, treatment, and recovery are receiving attention, not much has been done on adaptive interventions to prevent opioid use disorder (OUD). To address this, we identify opioid prescription and opioid consumption as promising targets for adaptive interventions and present a design framework.
Author(s): Singh, Neetu, Varshney, Upkar
DOI: 10.1093/jamia/ocac253
Enabling clinicians to formulate individualized clinical management strategies from the sea of molecular data remains a fundamentally important but daunting task. Here, we describe efforts towards a new paradigm in genomics-electronic health record (HER) integration, using a standardized suite of FHIR Genomics Operations that encapsulates the complexity of molecular data so that precision medicine solution developers can focus on building applications.
Author(s): Dolin, Robert H, Heale, Bret S E, Alterovitz, Gil, Gupta, Rohan, Aronson, Justin, Boxwala, Aziz, Gothi, Shaileshbhai R, Haines, David, Hermann, Arthur, Hongsermeier, Tonya, Husami, Ammar, Jones, James, Naeymi-Rad, Frank, Rapchak, Barbara, Ravishankar, Chandan, Shalaby, James, Terry, May, Xie, Ning, Zhang, Powell, Chamala, Srikar
DOI: 10.1093/jamia/ocac246
Online health communities (OHCs) have been identified as important outlets for social support and community connection for adolescents and young adults (AYAs) living with chronic illnesses. Despite evident benefits, there remains a gap in research on methods to maximize sustained patient engagement within OHCs. This study assessed per-patient daily commenting rates over time, as well as associations with program staff and volunteer-facilitated events and engagement.
Author(s): Walker, Andrew L, Swygert, Anna, Marchi, Emily, Lebeau, Kelsea, Haardörfer, Regine, Livingston, Melvin D
DOI: 10.1093/jamia/ocac252
SNOMED CT is the largest clinical terminology worldwide. Quality assurance of SNOMED CT is of utmost importance to ensure that it provides accurate domain knowledge to various SNOMED CT-based applications. In this work, we introduce a deep learning-based approach to uncover missing is-a relations in SNOMED CT.
Author(s): Abeysinghe, Rashmie, Zheng, Fengbo, Bernstam, Elmer V, Shi, Jay, Bodenreider, Olivier, Cui, Licong
DOI: 10.1093/jamia/ocac248
The aim of this study was to identify racial and ethnic disparities in patient portal offers, access, and use and to examine the role of providers in facilitating access to electronic health information (EHI) by offering patient portals and encouraging their use.
Author(s): Richwine, Chelsea, Johnson, Christian, Patel, Vaishali
DOI: 10.1093/jamia/ocac227
Accurate and rapid phenotyping is a prerequisite to leveraging electronic health records for biomedical research. While early phenotyping relied on rule-based algorithms curated by experts, machine learning (ML) approaches have emerged as an alternative to improve scalability across phenotypes and healthcare settings. This study evaluates ML-based phenotyping with respect to (1) the data sources used, (2) the phenotypes considered, (3) the methods applied, and (4) the reporting and evaluation methods [...]
Author(s): Yang, Siyue, Varghese, Paul, Stephenson, Ellen, Tu, Karen, Gronsbell, Jessica
DOI: 10.1093/jamia/ocac216
Author(s):
DOI: 10.1093/jamia/ocac224
To access the accuracy of the Logical Observation Identifiers Names and Codes (LOINC) mapping to local laboratory test codes that is crucial to data integration across time and healthcare systems.
Author(s): McDonald, Clement J, Baik, Seo H, Zheng, Zhaonian, Amos, Liz, Luan, Xiaocheng, Marsolo, Keith, Qualls, Laura
DOI: 10.1093/jamia/ocac215