The purpose of the study was to explore the theoretical underpinnings of effective clinical decision support (CDS) factors using the comparative effectiveness results.
Author(s): Liu, Siru, Reese, Thomas J, Kawamoto, Kensaku, Del Fiol, Guilherme, Weir, Charlene
DOI: 10.1093/jamia/ocab160
Mobile health (mHealth) applications have the potential to improve health awareness. This study reports a quasi-controlled intervention to augment maternal health awareness among tribal pregnant mothers through the mHealth application. Households from 2 independent villages with similar socio-demographics in tribal regions of India were selected as intervention (Village A) and control group (Village B). The control group received government mandated programs through traditional means (orally), whereas the intervention group received [...]
Author(s): Choudhury, Avishek, Asan, Onur, Choudhury, Murari M
DOI: 10.1093/jamia/ocab172
This study investigated how well-suited the International Classification of Diseases, 11th Revision, for Mortality and Morbidity Statistics, (ICD-11 MMS) is for 2 morbidity use cases, patient safety and quality, examining the level of detail captured, and evaluating the necessity for the development of a US clinical modification (CM).
Author(s): Fenton, Susan H, Giannangelo, Kathy L, Stanfill, Mary H
DOI: 10.1093/jamia/ocab163
The study sought to summarize research literature on nursing decision support systems (DSSs ); understand which steps of the nursing care process (NCP) are supported by DSSs, and analyze effects of automated information processing on decision making, care delivery, and patient outcomes.
Author(s): Akbar, Saba, Lyell, David, Magrabi, Farah
DOI: 10.1093/jamia/ocab123
To rapidly develop, validate, and implement a novel real-time mortality score for the COVID-19 pandemic that improves upon sequential organ failure assessment (SOFA) for decision support for a Crisis Standards of Care team.
Author(s): Sottile, Peter D, Albers, David, DeWitt, Peter E, Russell, Seth, Stroh, J N, Kao, David P, Adrian, Bonnie, Levine, Matthew E, Mooney, Ryan, Larchick, Lenny, Kutner, Jean S, Wynia, Matthew K, Glasheen, Jeffrey J, Bennett, Tellen D
DOI: 10.1093/jamia/ocab100
Our aim is to develop a patient engagement technology that makes it easy for patients to access their own medical information and share it with others.
Author(s): Khurshid, Anjum, Oliveira, Eliel, Nordquist, Eric, Lakshminarayanan, Vidya, Abrol, Vishal
DOI: 10.1093/jamiaopen/ooab109
To estimate the risk of hospital admission and mortality from COVID-19 to patients and measure the association of race and area-level social vulnerability with those outcomes.
Author(s): Landman, Joshua M, Steger-May, Karen, Joynt Maddox, Karen E, Hammond, Gmerice, Gupta, Aditi, Rauseo, Adriana M, Zhao, Min, Foraker, Randi E
DOI: 10.1093/jamiaopen/ooab111
COVID-19 mortality forecasting models provide critical information about the trajectory of the pandemic, which is used by policymakers and public health officials to guide decision-making. However, thousands of published COVID-19 mortality forecasts now exist, many with their own unique methods, assumptions, format, and visualization. As a result, it is difficult to compare models and understand under which circumstances a model performs best. Here, we describe the construction and usability of [...]
Author(s): Akre, Samir, Liu, Patrick Y, Friedman, Joseph R, Bui, Alex A T
DOI: 10.1093/jamiaopen/ooab113
[This corrects the article DOI: 10.1093/jamiaopen/ooab029.].
Author(s): Avoundjian, Tigran, Troszak, Lara, Cave, Shayna, Shimada, Stephanie, McInnes, Keith, Midboe, Amanda M
DOI: 10.1093/jamiaopen/ooab105
Author(s): Yang, Kevin, Nambudiri, Vinod E
DOI: 10.1055/s-0041-1740259