Strengthening our profession by defining clinical and health informatics practice.
Author(s): Fridsma, Douglas B
DOI: 10.1093/jamia/ocz060
Author(s): Fridsma, Douglas B
DOI: 10.1093/jamia/ocz060
Estimate the impact on clinical practice of using a mobile device-based electronic clinical decision support (mECDS) tool within a national standardization project.
Author(s): Kerns, Ellen K, Staggs, Vincent S, Fouquet, Sarah D, McCulloh, Russell J
DOI: 10.1093/jamia/ocz011
Most healthcare providers are reluctant to use health apps for healthcare because there is no rigorous way of choosing the best app for their patient or consumer. Accordingly, we developed a new method of app selection that fully considers target users' needs. This study verified whether health apps selected based on target users' needs can influence health-related factors.
Author(s): Lee, Jisan, Kim, Jeongeun
DOI: 10.1093/jamia/ocz019
Patient-powered research networks (PPRNs) are a valuable source of patient-generated information. Diagnosis code-based algorithms developed by PPRNs can be used to query health plans' claims data to identify patients for research opportunities. Our objective was to implement privacy-preserving record linkage processes between PPRN members' and health plan enrollees' data, compare linked and nonlinked members, and measure disease-specific confirmation rates for specific health conditions.
Author(s): Agiro, Abiy, Chen, Xiaoxue, Eshete, Biruk, Sutphen, Rebecca, Bourquardez Clark, Elizabeth, Burroughs, Cristina M, Nowell, W Benjamin, Curtis, Jeffrey R, Loud, Sara, McBurney, Robert, Merkel, Peter A, Sreih, Antoine G, Young, Kalen, Haynes, Kevin
DOI: 10.1093/jamia/ocz012
In the context of patient broad consent for future research uses of their identifiable health record data, we compare the effectiveness of interactive trust-enhanced e-consent, interactive-only e-consent, and standard e-consent (no interactivity, no trust enhancement).
Author(s): Harle, Christopher A, Golembiewski, Elizabeth H, Rahmanian, Kiarash P, Brumback, Babette, Krieger, Janice L, Goodman, Kenneth W, Mainous, Arch G, Moseley, Ray E
DOI: 10.1093/jamia/ocz015
The collection and use of a family health history are important for assessing the patient's risk of disease, but history taking is often impeded by practical barriers in the office. Provision for patient-computer dialogue, linked with the electronic health record, may enable patients to contribute their history while bypassing these barriers. We sought to assess the patient experience using such a tool.
Author(s): Bajracharya, Adarsha S, Crotty, Bradley H, Kowoloff, Hollis B, Safran, Charles, Slack, Warner V
DOI: 10.1093/jamia/ocz008
We aim to evaluate the effectiveness of advanced deep learning models (eg, capsule network [CapNet], adversarial training [ADV]) for single-domain and multidomain relation extraction from electronic health record (EHR) notes.
Author(s): Li, Fei, Yu, Hong
DOI: 10.1093/jamia/ocz018
Physicians can spend more time completing administrative tasks in their electronic health record (EHR) than engaging in direct face time with patients. Increasing rates of burnout associated with EHR use necessitate improvements in how EHRs are developed and used. Although EHR design often bears the brunt of the blame for frustrations expressed by physicians, the EHR user experience is influenced by a variety of factors, including decisions made by entities [...]
Author(s): Tutty, Michael A, Carlasare, Lindsey E, Lloyd, Stacy, Sinsky, Christine A
DOI: 10.1093/jamia/ocz021
The study sought to design, pilot, and evaluate a federated data completeness tracking system (CTX) for assessing completeness in research data extracted from electronic health record data across the Accessible Research Commons for Health (ARCH) Clinical Data Research Network.
Author(s): Estiri, Hossein, Klann, Jeffrey G, Weiler, Sarah R, Alema-Mensah, Ernest, Joseph Applegate, R, Lozinski, Galina, Patibandla, Nandan, Wei, Kun, Adams, William G, Natter, Marc D, Ofili, Elizabeth O, Ostasiewski, Brian, Quarshie, Alexander, Rosenthal, Gary E, Bernstam, Elmer V, Mandl, Kenneth D, Murphy, Shawn N
DOI: 10.1093/jamia/ocz014
Telemedicine can facilitate population health management by extending the reach of providers to efficiently care for high-risk, high-utilization populations. However, for telemedicine to be maximally useful, data collected using telemedicine technologies must be reliable and readily available to healthcare providers. To address current gaps in integration of patient-generated health data into the electronic health record (EHR), we examined 2 patient-facing platforms, Epic MyChart and Apple HealthKit, both of which facilitated [...]
Author(s): Lewinski, Allison A, Drake, Connor, Shaw, Ryan J, Jackson, George L, Bosworth, Hayden B, Oakes, Megan, Gonzales, Sarah, Jelesoff, Nicole E, Crowley, Matthew J
DOI: 10.1093/jamia/ocz039