Direct Secure Messaging in Practice-Recommendations for Improvements.
Author(s): Arvisais-Anhalt, Simone, Wickenhauser, Kathryn Ayers, Lusk, Katherine, Lehmann, Christoph U, McCormack, James L, Feterik, Kristian
DOI: 10.1055/s-0042-1753540
Author(s): Arvisais-Anhalt, Simone, Wickenhauser, Kathryn Ayers, Lusk, Katherine, Lehmann, Christoph U, McCormack, James L, Feterik, Kristian
DOI: 10.1055/s-0042-1753540
We previously developed and validated a predictive model to help clinicians identify hospitalized adults with coronavirus disease 2019 (COVID-19) who may be ready for discharge given their low risk of adverse events. Whether this algorithm can prompt more timely discharge for stable patients in practice is unknown.
Author(s): Major, Vincent J, Jones, Simon A, Razavian, Narges, Bagheri, Ashley, Mendoza, Felicia, Stadelman, Jay, Horwitz, Leora I, Austrian, Jonathan, Aphinyanaphongs, Yindalon
DOI: 10.1055/s-0042-1750416
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocac042
After 25 years of service to the American Medical Informatics Association (AMIA), Ms Karen Greenwood, the Executive Vice President and Chief Operating Officer, is leaving the organization. In this perspective, we reflect on her accomplishments and her effect on the organization and the field of informatics nationally and globally. We also express our appreciation and gratitude for Ms Greenwood's role at AMIA.
Author(s): Lehmann, Christoph U, Brennan, Patricia F, Detmer, Don E, Jackson, Gretchen P, Ohno-Machado, Lucila, Safran, Charles, Williamson, Jeffrey J, Shortliffe, Edward H
DOI: 10.1093/jamia/ocac039
Electronic health records (EHRs) enable investigation of the association between phenotypes and risk factors. However, studies solely relying on potentially error-prone EHR-derived phenotypes (ie, surrogates) are subject to bias. Analyses of low prevalence phenotypes may also suffer from poor efficiency. Existing methods typically focus on one of these issues but seldom address both. This study aims to simultaneously address both issues by developing new sampling methods to select an optimal [...]
Author(s): Liu, Xiaokang, Chubak, Jessica, Hubbard, Rebecca A, Chen, Yong
DOI: 10.1093/jamia/ocab267
Problem lists represent an integral component of high-quality care. However, they are often inaccurate and incomplete. We studied the effects of alerts integrated into the inpatient and outpatient computerized provider order entry systems to assist in adding problems to the problem list when ordering medications that lacked a corresponding indication.
Author(s): Grauer, Anne, Kneifati-Hayek, Jerard, Reuland, Brian, Applebaum, Jo R, Adelman, Jason S, Green, Robert A, Lisak-Phillips, Jeanette, Liebovitz, David, Byrd, Thomas F, Kansal, Preeti, Wilkes, Cheryl, Falck, Suzanne, Larson, Connie, Shilka, John, VanDril, Elizabeth, Schiff, Gordon D, Galanter, William L, Lambert, Bruce L
DOI: 10.1093/jamia/ocab285
Actualizing the vision of Global Digital Health is a central issue on the Global Health Diplomacy agenda. The COVID-reinforced need for accelerated digital health progress will require political structures and processes to build a foundation for Global Digital Health. Simultaneously, Global Health Diplomacy uses digital technologies in its enactment. Both phenomena have driven interest in the term "Digital Health Diplomacy." A review of the literature revealed 2 emerging but distinct [...]
Author(s): Godinho, Myron Anthony, Martins, Henrique, Al-Shorbaji, Najeeb, Quintana, Yuri, Liaw, Siaw-Teng
DOI: 10.1093/jamia/ocab282
Given that electronic clinical quality measures (eCQMs) are playing a central role in quality improvement applications nationwide, a stronger evidence base demonstrating their reliability is critically needed. To assess the reliability of electronic health record-extracted data elements and measure results for the Elective Delivery and Exclusive Breast Milk Feeding measures (vs manual abstraction) among a national sample of US acute care hospitals, as well as common sources of discrepancies and [...]
Author(s): Schmaltz, Stephen, Vaughn, Jocelyn, Elliott, Tricia
DOI: 10.1093/jamia/ocab276
Author(s): Miller, Randolph A, Shortliffe, Edward H
DOI: 10.1093/jamia/ocac026
Population health management (PHM) is an important approach to promote wellness and deliver health care to targeted individuals who meet criteria for preventive measures or treatment. A critical component for any PHM program is a data analytics platform that can target those eligible individuals.
Author(s): Bradshaw, Richard L, Kawamoto, Kensaku, Kaphingst, Kimberly A, Kohlmann, Wendy K, Hess, Rachel, Flynn, Michael C, Nanjo, Claude J, Warner, Phillip B, Shi, Jianlin, Morgan, Keaton, Kimball, Kadyn, Ranade-Kharkar, Pallavi, Ginsburg, Ophira, Goodman, Melody, Chambers, Rachelle, Mann, Devin, Narus, Scott P, Gonzalez, Javier, Loomis, Shane, Chan, Priscilla, Monahan, Rachel, Borsato, Emerson P, Shields, David E, Martin, Douglas K, Kessler, Cecilia M, Del Fiol, Guilherme
DOI: 10.1093/jamia/ocac028