Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocaf097
Machine learning algorithms can advance clinical care, including identifying mental health conditions. These algorithms are often developed without considering the perspectives of the affected populations. This study describes the process of incorporating end-user perspectives into the development and implementation planning of a prediction algorithm for new perinatal depression onset.
Author(s): Williams, Kelly, Nikolajski, Cara, Rodriguez, Samantha, Kwok, Elaine, Gopalan, Priya, Simhan, Hyagriv, Krishnamurti, Tamar
DOI: 10.1093/jamia/ocaf086
To examine the effects of message framing and visualization framing on the comprehension of personal health records and subsequent self-care behavioral intention among young and middle-older aged adults.
Author(s): Liu, Kaifeng, Sun, Zhiyan, Ren, Xinyuan, Tao, Da
DOI: 10.1093/jamia/ocaf085
Health-care institutions customize electronic health record (EHR) configurations to reflect their unique workflows and patient care priorities. Ensuring EHR alignment across sites facilitates seamless information exchange. We developed a pipeline for EHR flowsheet alignment between health-care organizations. The pipeline is augmented by mapping flowsheet data fields to concepts in the Clinical Care Classification (CCC) nursing terminology.
Author(s): Fan, Hao, Rossetti, Sarah C, Thate, Jennifer, Mugoya, Rosemary, Lai, Albert M, Yen, Po-Yin
DOI: 10.1093/jamia/ocaf076