Active Participation and Engagement of Residents in Clinical Informatics.
Author(s): Quirós, Fernán Gonzalez Bernaldo de, Baum, Analía, Lira, Antonio
DOI: 10.1055/s-0038-1676970
Author(s): Quirós, Fernán Gonzalez Bernaldo de, Baum, Analía, Lira, Antonio
DOI: 10.1055/s-0038-1676970
Excess physician work hours contribute to burnout and medical errors. Self-report of work hours is burdensome and often inaccurate. We aimed to validate a method that automatically determines provider shift duration based on electronic health record (EHR) timestamps across multiple inpatient settings within a single institution.
Author(s): Dziorny, Adam C, Orenstein, Evan W, Lindell, Robert B, Hames, Nicole A, Washington, Nicole, Desai, Bimal
DOI: 10.1055/s-0038-1676819
Local implementation of guidelines for pneumonia care is strongly recommended, but the context of care that affects implementation is poorly understood. In a learning health care system, computerized clinical decision support (CDS) provides an opportunity to both improve and track practice, providing insights into the implementation process.
Author(s): Jones, Barbara E, Collingridge, Dave S, Vines, Caroline G, Post, Herman, Holmen, John, Allen, Todd L, Haug, Peter, Weir, Charlene R, Dean, Nathan C
DOI: 10.1055/s-0038-1676587
Connected medical devices and electronic health records have added important functionality to patient care, but have also introduced a range of cybersecurity concerns. When a healthcare organization suffers from a cybersecurity incident, its incident response strategies are critical to the success of its recovery.
Author(s): Jalali, Mohammad S, Russell, Bethany, Razak, Sabina, Gordon, William J
DOI: 10.1093/jamia/ocy148
Conduct a cluster analysis of inpatient portal (IPP) users from an academic medical center to improve understanding of who uses these portals and how.
Author(s): Fareed, Naleef, Walker, Daniel, Sieck, Cynthia J, Taylor, Robert, Scarborough, Seth, Huerta, Timothy R, McAlearney, Ann Scheck
DOI: 10.1093/jamia/ocy147
This study evaluates whether a web-based educational program for patients who read their mental health notes online improves patient-clinician communication and increases patient activation.
Author(s): Denneson, Lauren M, Pisciotta, Maura, Hooker, Elizabeth R, Trevino, Amira, Dobscha, Steven K
DOI: 10.1093/jamia/ocy134
Querying electronic health records (EHRs) to find patients meeting study criteria is an efficient method of identifying potential study participants. We aimed to measure the effectiveness of EHR-driven recruitment in the context of ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness)-a pragmatic trial aiming to recruit 15 000 patients.
Author(s): Pfaff, Emily, Lee, Adam, Bradford, Robert, Pae, Jinhee, Potter, Clarence, Blue, Paul, Knoepp, Patricia, Thompson, Kristie, Roumie, Christianne L, Crenshaw, David, Servis, Remy, DeWalt, Darren A
DOI: 10.1093/jamia/ocy138
Lesbian, gay, bisexual, transgender, and queer (LGBTQ) people experience significant health disparities across the life course and require health care that addresses their unique needs. Collecting information on the sexual orientation and gender identity (SO/GI) of patients and entering SO/GI data in electronic health records has been recommended by the Institute of Medicine, the Joint Commission, and the Health Resources and Services Administration as fundamental to improving access to and [...]
Author(s): Grasso, Chris, McDowell, Michal J, Goldhammer, Hilary, Keuroghlian, Alex S
DOI: 10.1093/jamia/ocy137
We describe and evaluate the mapping of computerized tomography (CT) terms from 40 hospitals participating in a health information exchange (HIE) to a standard terminology.
Author(s): Peng, Paul, Beitia, Anton Oscar, Vreeman, Daniel J, Loo, George T, Delman, Bradley N, Thum, Frederick, Lowry, Tina, Shapiro, Jason S
DOI: 10.1093/jamia/ocy135
We developed and validated an algorithm that uses combinations of extractable electronic-health-record (EHR) indicators (diagnosis codes, orders for laboratories, medications, and referrals) that denote widely-recommended clinician practice behaviors: attention to overweight/obesity/body mass index alone (BMI Alone), with attention to hypertension/other comorbidities (BMI/Medical Risk), or neither (No Attention). Data inputs used for each EHR indicator were refined through iterative chart review to identify and resolve modifiable coding errors. Validation was performed [...]
Author(s): Turer, Christy B, Skinner, Celette S, Barlow, Sarah E
DOI: 10.1093/jamia/ocy126