Building on Diana Forsythe's legacy: the value of human experience and context in biomedical and health informatics.
Author(s): Unertl, Kim M, Abraham, Joanna, Bakken, Suzanne
DOI: 10.1093/jamia/ocaa337
Author(s): Unertl, Kim M, Abraham, Joanna, Bakken, Suzanne
DOI: 10.1093/jamia/ocaa337
The study sought to examine the effects of technology-supported exercise programs on the knee pain, physical function, and quality of life of individuals with knee osteoarthritis and/or chronic knee pain by a systematic review and meta-analysis of randomized controlled trials.
Author(s): Chen, Tianrong, Or, Calvin Kalun, Chen, Jiayin
DOI: 10.1093/jamia/ocaa282
We conducted an online experimental survey to evaluate attitudes toward an authorization for contact (AFC) program allowing researchers to contact patients about studies based on electronic record review. A total of 1070 participants were randomly assigned to 1 of 3 flyers varying in design and framing. Participants were asked to select concerns about and reasons for signing up for AFC. Logistic regression and latent class analysis were conducted. The most [...]
Author(s): Niyibizi, Nyiramugisha K, Speight, Candace D, Gregor, Charlie, Ko, Yi-An, Kraft, Stephanie A, Mitchell, Andrea R, Phillips, Bradley G, Porter, Kathryn M, Shah, Seema K, Sugarman, Jeremy, Wilfond, Benjamin S, Dickert, Neal W
DOI: 10.1093/jamia/ocaa214
Peer mentors have been proven to improve diabetes outcomes, especially among diverse patients. Delivering peer mentoring via remote strategies (phone, text, mobile applications) is critical, especially in light of the recent pandemic. We conducted a real-world evaluation of a remote diabetes intervention in a safety-net delivery system in New York. We summarized the uptake, content, and pre-post clinical effectiveness for English- and Spanish-speaking participants. Of patients who could be reached [...]
Author(s): Lyles, Courtney R, Sarkar, Urmimala, Patel, Urvashi, Lisker, Sarah, Stark, Allison, Guzman, Vanessa, Patel, Ashwin
DOI: 10.1093/jamia/ocaa251
Information gaps that accompany hurricanes and floods limit researchers' ability to determine the impact of disasters on population health. Defining key use cases for sharing complex disaster data with research communities and facilitators, and barriers to doing so are key to promoting population health research for disaster recovery.
Author(s): Phuong, Jimmy, Bandaragoda, Christina J, Haldar, Shefali, Stephens, Kari A, Ordonez, Patricia, Mooney, Sean D, Hartzler, Andrea L
DOI: 10.1093/jamia/ocaa195
To determine interest in and barriers to video visits in safety-net patients with diverse age, racial/ethnic, or linguistic background.
Author(s): Khoong, Elaine C, Butler, Blythe A, Mesina, Omar, Su, George, DeFries, Triveni B, Nijagal, Malini, Lyles, Courtney R
DOI: 10.1093/jamia/ocaa234
This research brief contains results from a national survey about telehealth use reported in a random sample of U.S. nursing homes.
Author(s): Alexander, Gregory L, Powell, Kimberly R, Deroche, Chelsea B
DOI: 10.1093/jamia/ocaa253
Hiring medical scribes to document in the electronic health record (EHR) on behalf of providers could pose patient safety risks because scribes often have no clinical training. The aim of this study was to investigate the effect of scribes on patient safety. This included identification of best practices to assure that scribe use of the EHR is not a patient safety risk.
Author(s): Ash, Joan S, Corby, Sky, Mohan, Vishnu, Solberg, Nicholas, Becton, James, Bergstrom, Robby, Orwoll, Benjamin, Hoekstra, Christopher, Gold, Jeffrey A
DOI: 10.1093/jamia/ocaa199
Although women in the field of biomedical informatics (BMI) are part of a golden era, little is known about their lived experiences as informaticians. Guided by feminist standpoint theory, this study aims to understand the impact of social change in the Kingdom of Saudi Arabia- in the form of new policies supporting women and health technological advancements-in the field of BMI and its women informaticians.
Author(s): Aldekhyyel, Raniah N, Almulhem, Jwaher A, Binkheder, Samar, Muaygil, Ruaim A, Aldekhyyel, Shahad N
DOI: 10.1093/jamia/ocaa165
The study sought to outline how a clinical risk prediction model for identifying patients at risk of infection is perceived by home care nurses, and to inform how the output of the model could be integrated into a clinical workflow.
Author(s): Dowding, Dawn, Russell, David, McDonald, Margaret V, Trifilio, Marygrace, Song, Jiyoun, Brickner, Carlin, Shang, Jingjing
DOI: 10.1093/jamia/ocaa267