Measuring and Maximizing Undivided Attention in the Context of Electronic Health Records.
Author(s): Chen, You, Adler-Milstein, Julia, Sinsky, Christine A
DOI: 10.1055/a-1892-1437
Author(s): Chen, You, Adler-Milstein, Julia, Sinsky, Christine A
DOI: 10.1055/a-1892-1437
To utilize metrics from physician action logs to analyze volume, physician efficiency and burden as impacted by telemedicine implementation during the COVID-19 (coronavirus disease 2019) pandemic, and physician characteristics such as gender, years since graduation, and specialty category.
Author(s): Ruan, Elise, Beiser, Moshe, Lu, Vivian, Paul, Soaptarshi, Ni, Jason, Nazar, Nijas, Liu, Jianyou, Kim, Mimi, Epstein, Eric, Keller, Marla, Kitsis, Elizabeth, Tomer, Yaron, Jariwala, Sunit P
DOI: 10.1055/a-1877-2745
Introducing an electronic medical record (EMR) system into a complex health care environment fundamentally changes clinical workflows and documentation processes and, hence, has implications for patient safety. After a multisite "big-bang" EMR implementation across our large public health care organization, a quality improvement program was developed and implemented to monitor clinician adoption, documentation quality, and compliance with workflows to support high-quality patient care.
Author(s): Jedwab, Rebecca M, Franco, Michael, Owen, Denise, Ingram, Anna, Redley, Bernice, Dobroff, Naomi
DOI: 10.1055/s-0042-1756369
A computerized 12-lead electrocardiogram (ECG) can automatically generate diagnostic statements, which are helpful for clinical purposes. Standardization is required for big data analysis when using ECG data generated by different interpretation algorithms. The common data model (CDM) is a standard schema designed to overcome heterogeneity between medical data. Diagnostic statements usually contain multiple CDM concepts and also include non-essential noise information, which should be removed during CDM conversion. Existing CDM [...]
Author(s): Choi, Sunho, Joo, Hyung Joon, Kim, Yoojoong, Kim, Jong-Ho, Seok, Junhee
DOI: 10.1055/s-0042-1756427
Computerized clinical decision support (CDS) used in electronic health record systems (EHRs) has led to positive outcomes as well as unintended consequences, such as alert fatigue. Characteristics of the EHR session can be used to restrict CDS tools and increase their relevance, but implications of this approach are not rigorously studied.
Author(s): Salmasian, Hojjat, Rubins, David, Bates, David W
DOI: 10.1055/s-0042-1756426
To improve timely access to quality HIV research data, the Rakai Health Sciences Program (RHSP) Data Mart was developed to store cohort study data from a legacy database platform in a modernized system using standard data management processes. The RHSP Data Mart was developed on a Microsoft SQL Server platform using Microsoft SQL Server Integration Services with custom data mappings and queries. The data mart stores 20+ years of longitudinal [...]
Author(s): Ndyanabo, Anthony, Footer, Kevin, Ahmed, Tanvir, Glogowski, Alex, Whalen, Christopher, Ssekasanvu, Joseph, Ssentongo, Lloyd, Lutalo, Tom, Nalugoda, Fred, Ha, Grace K, Rosenthal, Alex
DOI: 10.1093/jamiaopen/ooac032
Evaluate an initiative to distribute video-enabled tablets and cell phones to individuals enrolled in Veterans Health Affairs supportive housing program during the COVID-19 pandemic.
Author(s): Wray, Charlie M, Van Campen, James, Hu, Jiaqi, Slightam, Cindie, Heyworth, Leonie, Zulman, Donna M
DOI: 10.1093/jamiaopen/ooac027
Computer-aided decision tools may speed recognition of acute respiratory distress syndrome (ARDS) and promote consistent, timely treatment using lung-protective ventilation (LPV). This study evaluated implementation and service (process) outcomes with deployment and use of a clinical decision support (CDS) synchronous alert tool associated with existing computerized ventilator protocols and targeted patients with possible ARDS not receiving LPV.
Author(s): Knighton, Andrew J, Kuttler, Kathryn G, Ranade-Kharkar, Pallavi, Allen, Lauren, Throne, Taylor, Jacobs, Jason R, Carpenter, Lori, Winberg, Carrie, Johnson, Kyle, Shrestha, Neer, Ferraro, Jeffrey P, Wolfe, Doug, Peltan, Ithan D, Srivastava, Rajendu, Grissom, Colin K
DOI: 10.1093/jamiaopen/ooac050
Machine learning has the potential to improve identification of patients for appropriate diagnostic testing and treatment, including those who have rare diseases for which effective treatments are available, such as acute hepatic porphyria (AHP). We trained a machine learning model on 205 571 complete electronic health records from a single medical center based on 30 known cases to identify 22 patients with classic symptoms of AHP that had neither been diagnosed [...]
Author(s): Hersh, William R, Cohen, Aaron M, Nguyen, Michelle M, Bensching, Katherine L, Deloughery, Thomas G
DOI: 10.1093/jamiaopen/ooac053
Opioid Overdose Network is an effort to generalize and adapt an existing research data network, the Accrual to Clinical Trials (ACT) Network, to support design of trials for survivors of opioid overdoses presenting to emergency departments (ED). Four institutions (Medical University of South Carolina [MUSC], Dartmouth Medical School [DMS], University of Kentucky [UK], and University of California San Diego [UCSD]) worked to adapt the ACT network. The approach that was [...]
Author(s): Lenert, Leslie A, Zhu, Vivienne, Jennings, Lindsey, McCauley, Jenna L, Obeid, Jihad S, Ward, Ralph, Hassanpour, Saeed, Marsch, Lisa A, Hogarth, Michael, Shipman, Perry, Harris, Daniel R, Talbert, Jeffery C
DOI: 10.1093/jamiaopen/ooac055