The COVID-19 pandemic of 2020 has been a major public health problem and a tremendous disruption to many academic fields, including biomedical informatics. However, Department of Medical Informatics & Clinical Epidemiology (DMICE) faculty and trainees have been very productive during the move to virtual work and this post shares some papers and conference proceedings with comments from the authors who have published them.
Hribar M, Dusek HL, Goldstein IH, Rule A, Chiang MF. Documentation Composition and Efficiency During Scribed and Non Scribed Ophthalmology Visits. Investigative Ophthalmology & Visual Science. 2020;61(7):1587.
Prof. Michelle Hribar notes, “This was a poster abstract for a conference that was cancelled because of the pandemic! The conference was held virtually, but the poster sessions were asynchronous and I opted not to participate. Many of us had to forgo traveling to conferences and instead presented papers and posters in virtual conferences (using Zoom, WebEx, or other video interfaces).” Prof. Hribar also had an AMIA Symposium paper written at the start of the pandemic but wound up having extra time to revise it because conference submission deadlines were delayed: Hribar MR, Dusek HL, Goldstein IH, Rule A, Chiang MF. Methods for Large-Scale Quantitative Analysis of Scribe Impacts on Clinical Documentation. AMIA Annual Symposium Proceedings 2020. To appear.
Womack DM, Hribar MR, Steege LM, Vuckovic NH, Eldredge DH, Gorman PN. Registered Nurse Strain Detection Using Ambient Data: An Exploratory Study of Underutilized Operational Data Streams in the Hospital Workplace. Applied Clinical Informatics. 2020;11(4):598-605.
Prof. Dana Womack states that she “used early days of the pandemic to complete a paper that has been in draft form for some time. The ‘new normal’ of remote work has set in, but even that has hidden benefits of reduced time commuting that can be leveraged to advance work.”
Cohen AM, Chamberlin S, Deloughery T, Nguyen M, Bedrick S, Meninger S, Ko JJ, Amin JJ, Wei AJ, Hersh WR. Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria. PLoS ONE. 2020;15(7):e0235574.
Prof. Aaron Cohen remarked about his PLoS ONE paper, “Our work on detecting undiagnosed patients with the rare disease acute hepatic porphyria (AHP) using the electronic health record is just the ‘tip of the iceberg’ in using the EHR in novel ways to improve clinical care. In the future, we will extend this method to more rare diseases that often remain undiagnosed until young adulthood or later.”
Chamberlin S, Bedrick S, Cohen A, Wang Y, Wen A, Liu H, Hersh W. Evaluation of patient-level retrieval from electronic health record data for a cohort discovery task. JAMIA Open. 2020:ooaa026.
Chamberlin SR, Bedrick SD, Cohen AM, Wang Y, Wen A, Liu S, Liu H, Hersh W. A query taxonomy describes performance of patient-level retrieval from electronic health record data. CEUR Workshop Proceedings. 2020;2551(June):27-33.
Several DMICE faculty collaborated on these publications, and senior author and Prof. William Hersh noted, “Many academic medical centers offer EHR-based patient cohort discovery tools to their researchers, yet the performance of systems for this use is not well characterized. The objective of our research is to assess patient-level information retrieval methods using EHRs for different types of cohort definition retrieval.”
When ask about publishing during the pandemic, Postdoc Steve Chamberlin said, “I didn’t find it that much different! Our work is all data related and somewhat ‘virtual’ anyway. Half of our co-authors work at Mayo Clinic so our interactions have always been virtual. But these projects did start before (the pandemic), then ended once the pandemic had started. It is interesting the taxonomy paper was presented at the Web2020 conference I believe in the end of January, so we still traveled there to present live in Houston. But there were already presenters that could not show up because of the travel restrictions that had already started at that time.
Hersh W. Information Retrieval: A Biomedical and Health Perspective. Switzerland AG: Springer; 2020.
Prof. Hersh also saw the publication of the fourth edition of his textbook on information retrieval, noting, “I had been working on the book since late 2019 and fortunately was able to complete the writing early on in the pandemic, and then went through the usual proof and production process with the publisher, with the book published in September.”
There are a number of other papers and conference proceedings whose authors included since the pandemic began. Among these include:
Ash JS, Chase D, Baron S, Filios MS, Shiffman RN, Marovich S, et al. Clinical Decision Support for Worker Health: A Five-Site Qualitative Needs Assessment in Primary Care Settings. Applied Clinical Informatics. 2020;11(4):635-43.
Ash JS, Corby S, Mohan V, Solberg N, Becton J, Bergstrom R, Orwoll B, Hoekstra C, Gold JA. Safe use of the EHR by medical scribes: A qualitative study. Journal of the American Medical Informatics Association. In press.
Haendel MA, Chute CG, Gersing K. The National COVID Cohort Collaborative (N3C): Rationale, Design, Infrastructure, and Deployment. Journal of the American Medical Informatics Association. 2020: ocaa196.
Hollis KF, Roberts K, Bedrick S, Hersh WR. Addressing the Search Challenges of Precision Medicine with Information Retrieval Systems and Physician Readers. Studies in Health Technology and Informatics. 2020;270:813-7.
Roberts K, Alam T, Bedrick S, Demner-Fushman D, Lo K, Soboroff I, Voorhees E, Wang LL, Hersh WR. TREC-COVID: rationale and structure of an information retrieval shared task for COVID-19. Journal of the American Medical Informatics Association : JAMIA. 2020;27(9):1431-6.
Vasilevsky N, Hosseini M, Teplitzky S, Ilik V, Mohammadi E, Schneider J, et al. Is authorship sufficient for today’s collaborative research? A call for contributor roles. Accountability in Research. 2020:1-21.
Womack DM, Warren C, Hayes M, Stoyles S, Eldredge DH. Evaluation of Electronic Health Record AQ1 –Generated Work Intensity Scores and Nurse Perceptions of Workload Appropriateness. Computers in Nursing. 2020; in press.
The clinical epidemiology half of DMICE has also been highly productive and will be profiled in a future posting.