Implementation and Integration of Risk Evaluation and Mitigation Strategies into the Health Care System.
Author(s): Neyarapally, George A, Millikan, Edward D, Manzo, Claudia
DOI: 10.1055/s-0043-1767683
Author(s): Neyarapally, George A, Millikan, Edward D, Manzo, Claudia
DOI: 10.1055/s-0043-1767683
Despite widespread adoption of electronic health records (EHRs), these systems have significant room for improved efficiency and efficacy. While the idea of crowdsourcing EHR improvement ideas has been reported, little is known about how this might work across an integrated health care delivery system in practice.
Author(s): Rajamani, Geetanjali, Diethelm, Molly, Gunderson, Melissa A, Talluri, Venkata S M, Motz, Patricia, Steinhaus, Jennifer M, LaFlamme, Anne E, Jarabek, Bryan, Christiaansen, Tori, Blade, Jeffrey T, Badlani, Sameer, Melton, Genevieve B
DOI: 10.1055/s-0043-1767684
The 21st Century Cures Act information blocking final rule mandated the immediate and electronic release of health care data in 2020. There is anecdotal concern that a significant amount of information is documented in notes that would breach adolescent confidentiality if released electronically to a guardian.
Author(s): Bedgood, Michael, Rabbani, Naveed, Brown, Conner, Goldstein, Rachel, Carlson, Jennifer L, Steinberg, Ethan, Powell, Austin, Pageler, Natalie M, Morse, Keith
DOI: 10.1055/s-0043-1767682
Reuse of health care data for various purposes, such as the care process, for quality measurement, research, and finance, will become increasingly important in the future; therefore, "Collect Once Use Many Times" (COUMT). Clinical information models (CIMs) can be used for content standardization. Data collection for national quality registries (NQRs) often requires manual data entry or batch processing. Preferably, NQRs collect required data by extracting data recorded during the health [...]
Author(s): Schepens, Maike H J, Trompert, Annemarie C, van Hooff, Miranda L, van der Velde, Erik, Kallewaard, Marjon, Verberk-Jonkers, Iris J A M, Cense, Huib A, Somford, Diederik M, Repping, Sjoerd, Tromp, Selma C, Wouters, Michel W J M
DOI: 10.1055/s-0043-1767681
Residents of the Bronx suffer marked health disparities due to socioeconomic and other factors. The coronavirus disease 2019 pandemic worsened these health outcome disparities and health care access disparities, especially with the abrupt transition to online care.
Author(s): Lane, Sarah, Fitzsimmons, Emma, Zelefksy, Abraham, Klein, Jonathan, Kaur, Savneet, Viswanathan, Shankar, Garg, Madhur, Feldman, Jonathan M, Jariwala, Sunit P
DOI: 10.1055/a-2041-4500
Inflammatory bowel disease (IBD) commonly leads to iron deficiency anemia (IDA). Rates of screening and treatment of IDA are often low. A clinical decision support system (CDSS) embedded in an electronic health record could improve adherence to evidence-based care. Rates of CDSS adoption are often low due to poor usability and fit with work processes. One solution is to use human-centered design (HCD), which designs CDSS based on identified user [...]
Author(s): Miller, Steven D, Murphy, Zachary, Gray, Joshua H, Marsteller, Jill, Oliva-Hemker, Maria, Maslen, Andrew, Lehmann, Harold P, Nagy, Paul, Hutfless, Susan, Gurses, Ayse P
DOI: 10.1055/a-2040-0578
Identifying children ready for transfer out of the pediatric intensive care unit (PICU) is an area that may benefit from clinical decision support (CDS). We previously implemented a quality improvement (QI) initiative to accelerate the transfer evaluation of non-medically complex PICU patients with viral bronchiolitis receiving floor-appropriate respiratory support.
Author(s): Martin, Blake, Mulhern, Brendan, Majors, Melissa, Rolison, Elise, McCombs, Tiffany, Smith, Grant, Fisher, Colin, Diaz, Elizabeth, Downen, Dana, Brittan, Mark
DOI: 10.1055/a-2036-0337
Patient and provider-facing screening tools for social determinants of health have been explored in a variety of contexts; however, effective screening and resource referral remain challenging, and less is known about how patients perceive chatbots as potential social needs screening tools. We investigated patient perceptions of a chatbot for social needs screening using three implementation outcome measures: acceptability, feasibility, and appropriateness.
Author(s): Langevin, Raina, Berry, Andrew B L, Zhang, Jinyang, Fockele, Callan E, Anderson, Layla, Hsieh, Dennis, Hartzler, Andrea, Duber, Herbert C, Hsieh, Gary
DOI: 10.1055/a-2035-5342
This study aimed to (1) determine the impact of COVID-19 (coronavirus disease 2019) and the corresponding increase in use of telemedicine on volume, efficiency, and burden of electronic health record (EHR) usage by residents and fellows; and (2) to compare these metrics with those of attending physicians.
Author(s): Mani, Kyle, Canarick, Jay, Ruan, Elise, Liu, Jianyou, Kitsis, Elizabeth, Jariwala, Sunit P
DOI: 10.1055/a-2031-9437
The health care field is experiencing widespread electronic health record (EHR) adoption. New medical professional liability (i.e., malpractice) cases will likely involve the review of data extracted from EHRs as well as EHR workflows, audit logs, and even the potential role of the EHR in causing harm.
Author(s): Sittig, Dean F, Wright, Adam
DOI: 10.1055/a-2018-9932