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      A patient-centered digital scribe for automatic medical documentation

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          Abstract

          Objective

          We developed a digital scribe for automatic medical documentation by utilizing elements of patient-centered communication. Excessive time spent on medical documentation may contribute to physician burnout. Patient-centered communication may improve patient satisfaction, reduce malpractice rates, and decrease diagnostic testing expenses. We demonstrate that patient-centered communication may allow providers to simultaneously talk to patients and efficiently document relevant information.

          Materials and Methods

          We utilized two elements of patient-centered communication to document patient history. One element was summarizing, which involved providers recapping information to confirm an accurate understanding of the patient. Another element was signposting, which involved providers using transition questions and statements to guide the conversation. We also utilized text classification to allow providers to simultaneously perform and document the physical exam. We conducted a proof-of-concept study by simulating patient encounters with two medical students.

          Results

          For history sections, the digital scribe was about 2.7 times faster than both typing and dictation. For physical exam sections, the digital scribe was about 2.17 times faster than typing and about 3.12 times faster than dictation. Results also suggested that providers required minimal training to use the digital scribe, and that they improved at using the system to document history sections.

          Conclusion

          Compared to typing and dictation, a patient-centered digital scribe may facilitate effective patient communication. It may also be more reliable compared to previous approaches that solely use machine learning. We conclude that a patient-centered digital scribe may be an effective tool for automatic medical documentation.

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          Most cited references69

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          MIMIC-III, a freely accessible critical care database

          MIMIC-III (‘Medical Information Mart for Intensive Care’) is a large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital. Data includes vital signs, medications, laboratory measurements, observations and notes charted by care providers, fluid balance, procedure codes, diagnostic codes, imaging reports, hospital length of stay, survival data, and more. The database supports applications including academic and industrial research, quality improvement initiatives, and higher education coursework.
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            Burnout and satisfaction with work-life balance among US physicians relative to the general US population.

            Despite extensive data about physician burnout, to our knowledge, no national study has evaluated rates of burnout among US physicians, explored differences by specialty, or compared physicians with US workers in other fields. We conducted a national study of burnout in a large sample of US physicians from all specialty disciplines using the American Medical Association Physician Masterfile and surveyed a probability-based sample of the general US population for comparison. Burnout was measured using validated instruments. Satisfaction with work-life balance was explored. Of 27 276 physicians who received an invitation to participate, 7288 (26.7%) completed surveys. When assessed using the Maslach Burnout Inventory, 45.8% of physicians reported at least 1 symptom of burnout. Substantial differences in burnout were observed by specialty, with the highest rates among physicians at the front line of care access (family medicine, general internal medicine, and emergency medicine). Compared with a probability-based sample of 3442 working US adults, physicians were more likely to have symptoms of burnout (37.9% vs 27.8%) and to be dissatisfied with work-life balance (40.2% vs 23.2%) (P < .001 for both). Highest level of education completed also related to burnout in a pooled multivariate analysis adjusted for age, sex, relationship status, and hours worked per week. Compared with high school graduates, individuals with an MD or DO degree were at increased risk for burnout (odds ratio [OR], 1.36; P < .001), whereas individuals with a bachelor's degree (OR, 0.80; P = .048), master's degree (OR, 0.71; P = .01), or professional or doctoral degree other than an MD or DO degree (OR, 0.64; P = .04) were at lower risk for burnout. Burnout is more common among physicians than among other US workers. Physicians in specialties at the front line of care access seem to be at greatest risk.
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              Scikit-Learn: Machine Learning in Python

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                Author and article information

                Journal
                JAMIA Open
                JAMIA Open
                jamiaoa
                JAMIA Open
                Oxford University Press
                2574-2531
                January 2021
                17 February 2021
                17 February 2021
                : 4
                : 1
                : ooab003
                Affiliations
                [1 ] Department of Translational Biomedical Science, University of Rochester Medical Center , Rochester, New York, USA
                [2 ] Department of Medicine and Pediatrics, University of Rochester Medical Center , Rochester, New York, USA
                [3 ] Department of Computer Science, University of Rochester , Rochester, New York, USA
                [4 ] Department of Pediatrics, University of Rochester Medical Center , Rochester, New York, USA
                Author notes
                Corresponding Author: Jesse Wang, Department of Translational Biomedical Science, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14622, USA ( jesse_wang@ 123456urmc.rochester.edu )
                Author information
                http://orcid.org/0000-0001-8269-1930
                Article
                ooab003
                10.1093/jamiaopen/ooab003
                8349503
                34377960
                cb841d0a-3065-49d2-b76f-5f62450858c5
                © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 23 September 2020
                : 08 December 2020
                : 10 January 2021
                : 12 January 2021
                Page count
                Pages: 9
                Funding
                Funded by: National Institute of General Medical Science, DOI 10.13039/100000057;
                Award ID: T32 GM07356
                Funded by: National Center for Advancing Translational Sciences, DOI 10.13039/100006108;
                Award ID: TL1 TR000096
                Categories
                Research and Applications
                AcademicSubjects/SCI01530
                AcademicSubjects/MED00010
                AcademicSubjects/SCI01060

                digital scribe,physician burnout,medical documentation,patient-centered communication

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