Abstract
As U.S. healthcare system moves towards digitization, Electronic Health Records (EHRs) are increasingly adopted by medical providers. However, EHR documentation is not only time-consuming but also difficult to complete in real-time, leading to delayed, missing, or erroneous data entry. This challenge is more evident in time-critical and hands-busy clinical domains, such as Emergency Medical Services (EMS). In recent years, smart glasses have gained momentum in supporting various aspects of clinical care. However, limited research has examined the potential of smart glasses in automating electronic documentation during fast-paced medical work. In this paper, we report the design, development, and preliminary evaluations of a novel system combining smart glasses and EHRs and leveraging natural language processing (NLP) techniques to enable hands-free, real-time documentation in the context of EMS care. Although optimization is needed, our system prototype represents a substantive departure from the status quo in the documentation technology for emergency care providers, and has a high potential to enable real-time documentation while accounting for care providers’ cognitive and physical constraints imposed by the time-critical medical environment.
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Downing, N.L., Bates, D.W., Longhurst, C.A.: Physician burnout in the electronic health record era: are we ignoring the real cause? American College of Physicians (2018)
Zulman, D.M., Shah, N.H., Verghese, A.: Evolutionary pressures on the electronic health record: caring for complexity. JAMA 316(9), 923–924 (2016)
Tollefsen, W.W., et al.: iRevive: a pre-hospital database system for emergency medical services. Int. J. Healthc. Technol. Manag. 6(4–6), 454–469 (2005)
Hertzum, M., Manikas, M.I., á Torkilsheyggi, A.: Grappling with the future: the messiness of pilot implementation in information systems design. Health Inform. J. 25(2), 372–388 (2019)
Sarcevic, A., Burd, R.S.: Information handover in time-critical work. In: Proceedings of the ACM 2009 International Conference on Supporting Group Work, pp. 301–310 (2009)
Holzman, T.G.: Computer-human interface solutions for emergency medical care. Interactions 6(3), 13–24 (1999)
Laudermilch, D.J., Schiff, M.A., Nathens, A.B., Rosengart, M.R.: Lack of emergency medical services documentation is associated with poor patient outcomes: a validation of audit filters for prehospital trauma care. J. Am. Coll. Surg. 210(2), 220–227 (2010)
Zhang, Z., et al.: Data work and decision making in emergency medical services: a distributed cognition perspective. Proc. ACM Human-Comput. Interact. 5(CSCW2), 1–32 (2021)
Momen, K.S.: Identifying nursing activities to estimate the risk of cross-contamination. University of Toronto, Canada (2012)
Pilerot, O., Maurin Söderholm, H.: A conceptual framework for investigating documentary practices in prehospital emergency care. Inf. Res. 24(4), colis1931 (2019)
Aldaz, G., et al.: Hands-free image capture, data tagging and transfer using Google Glass: a pilot study for improved wound care management. PloS One 10(4), e0121179 (2015)
Jonas, S., Hannig, A., Spreckelsen, C., Deserno, T.M.: Wearable technology as a booster of clinical care. In Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations, pp. 90390F. International Society for Optics and Photonics, Washington, USA (2014)
Mitrasinovic, S., et al.: Clinical and surgical applications of smart glasses. Technol. Health Care 23(4), 381–401 (2015)
Lee, J.-S., Tsai, C.-T., Pen, C.-H., Lu, H.-C.: A real time collaboration system for teleradiology consultation. Int. J. Med. Inform. 72(1–3), 73–79 (2003)
Noorian, A.R., et al.: Use of wearable technology in remote evaluation of acute stroke patients: feasibility and reliability of a Google Glass-based device. J. Stroke Cerebrovas. Dis. 28(10), 104258 (2019)
Cicero, M.X., et al.: Do you see what I see? Insights from using google glass for disaster telemedicine triage. Prehosp. Disaster Med. 30(1), 4 (2015)
Broach, J., et al.: Usability and reliability of smart glasses for secondary triage during mass casualty incidents. In Proceedings of the Annual Hawaii International Conference on System Sciences, p. 1416. IEEE, New York (2018)
Schaer, R., Melly, T., Muller, H., Widmer, A.: Using smart glasses in medical emergency situations, a qualitative pilot study. In: 2016 IEEE Wireless Health (WH), pp. 1–5. IEEE, New York, USA (2016)
Schlosser, P., Matthews, B., Salisbury, I., Sanderson, P., Hayes, S.: Head-Worn displays for emergency medical services staff: properties of prehospital work, use cases, and design considerations. In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1–14. ACM, New York (2021)
Saarinen, K., Aho, M.: Does the implementation of a clinical information system decrease the time intensive care nurses spend on documentation of care? Acta Anaesthesiol. Scand. 49(1), 62–65 (2005)
Davidson, S.J., Zwemer, F.L., Nathanson, L.A., Sable, K.N., Khan, A.N.: Where’s the beef? The promise and the reality of clinical documentation. Acad. Emerg. Med. 11(11), 1127–1134 (2004)
Chen, Y.: Documenting transitional information in EMR. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1787–1796. ACM, New York (2010)
Jagannath, S., Sarcevic, A., Young, V., Myers, S.: Temporal rhythms and patterns of electronic documentation in time-critical medical work. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–13. ACM, New York (2019)
Sarcevic, A., Ferraro, N.: On the use of electronic documentation systems in fast-paced, time-critical medical settings. Interact. Comput. 29(2), 203–219 (2017)
Bossen, C., Pine, K.H., Cabitza, F., Ellingsen, G., Piras, E.M.: Data work in healthcare: an Introduction. SAGE Publications Sage UK, London (2019)
Sarcevic, A.: “Who's scribing?” documenting patient encounter during trauma resuscitation. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1899–1908. ACM, New York (2010)
Meystre, S., Haug, P.J.: Natural language processing to extract medical problems from electronic clinical documents: performance evaluation. J. Biomed. Inform. 39(6), 589–599 (2006)
Rosales, R., Farooq, F., Krishnapuram, B., Yu, S., Fung, G.: Automated identification of medical concepts and assertions in medical text. In: AMIA Annual Symposium Proceedings, p. 682. American Medical Informatics Association, Maryland (2010)
Li, Q., Wu, Y.-F.B.: Identifying important concepts from medical documents. J. Biomed. Inform. 39(6), 668–679 (2006)
Preum, S.M., Shu, S., Alemzadeh, H., Stankovic, J.A.: Emscontext: EMS protocol-driven concept extraction for cognitive assistance in emergency response. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 13350–13355. AAAI Press, California (2020)
Rahman, M.A., Preum, S.M., Williams, R., Alemzadeh, H., Stankovic, J.A.: GRACE: generating summary reports automatically for cognitive assistance in emergency response. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 13356–13362. AAAI Press, California (2020)
Noma, H., Ohmura, A., Kuwahara, N., Kogure, K.: Wearable sensors for auto-event-recording on medical nursing-user study of ergonomic design. In: Eighth International Symposium on Wearable Computers, pp. 8–15. IEEE, New York (2004)
Klein, G.O., Singh, K., von Heideken, J.: Smart glasses—a new tool in medicine. Stud. Health Technol. Inform. 216, 901 (2015)
Aungst, T., Lewis, T.: Potential uses of wearable technology in medicine: lessons learnt from Google Glass. Int. J. Clin. Pract. 69(10), 1179–1183 (2015)
Yu, J., Ferniany, W., Guthrie, B., Parekh, S.G., Ponce, B.: Lessons learned from google glass: telemedical spark or unfulfilled promise? Surg. Innov. 23(2), 156–165 (2016)
Klinker, K., Wiesche, M., Krcmar, H.: Digital transformation in health care: augmented reality for hands-free service innovation. Inf. Syst. Front. 22, 1–13 (2019)
Holton, J.A.: The coding process and its challenges. The Sage Handbook of Grounded Theory 3, 265–289 (2007)
Hartson, R., Pyla, P.S.: The UX Book: Process and Guidelines for Ensuring a Quality User Experience. Elsevier (2012)
Zhang, Z., Sarcevic, A., Bossen, C.: Constructing common information spaces across distributed emergency medical teams. In: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, pp. 934–947. ACM, New York (2017)
Zhang, Z., Sarcevic, A., Burd, R.S.: Supporting information use and retention of pre-hospital information during trauma resuscitation: a qualitative study of pre-hospital communications and information needs. In: AMIA Annual Symposium Proceedings, p. 1579. American Medical Informatics Association, Maryland (2013)
Aronson, A.R.: MetaMap: mapping text to the UMLS metathesaurus. Bethesda, MD: NLM, NIH, DHHS 1, 26 (2006)
Sager, N., Lyman, M., Bucknall, C., Nhan, N., Tick, L.J.: Natural language processing and the representation of clinical data. J. Am. Med. Inform. Assoc. 1(2), 142–160 (1994)
Kormilitzin, A., Vaci, N., Liu, Q., Nevado-Holgado, A.: Med7: a transferable clinical natural language processing model for electronic health records. Artif. Intell. Med. 102086 (2021)
Manning, C.D., et al.: The Stanford CoreNLP natural language processing toolkit. In: Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics, pp. 55–60. Association for Computational Linguistics, Pennsylvania (2014)
Chinchor, N., Sundheim, B.M.: MUC-5 evaluation metrics. In: Fifth Message Understanding Conference (MUC-5): Proceedings of a Conference Held in Baltimore, Maryland (1993)
Zeng, X., Li, Y., Zhai, Y., Zhang, Y.: Counterfactual generator: a weakly-supervised method for named entity recognition. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 7270–7280. Association for Computational Linguistics, Pennsylvania (2020)
Thieu, T., et al.: A comprehensive study of mobility functioning information in clinical notes: entity hierarchy, corpus annotation, and sequence labeling. Int. J. Med. Inform. 147, 104351 (2021)
Sen, S., Ekbal, A., Bhattacharyya, P.: Parallel corpus filtering based on fuzzy string matching. In: Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pp. 289–293. Association for Computational Linguistics, Pennsylvania (2019)
Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions, and reversals. Sov. Phys. Doklady 10(8), 707–710 (1966)
Romare, C., Hass, U., Skär, L.: Healthcare professionals’ views of smart glasses in intensive care: a qualitative study. Intensive Crit. Care Nurs. 45, 66–71 (2018)
Maruri, H.A.C., et al.: V-Speech: noise-robust speech capturing glasses using vibration sensors. Proc. ACM Interact. Mob. Wearable Ubiquit. Technol. 2(4), 1–23 (2018)
Dawson, D.E.: National emergency medical services information system (NEMSIS). Prehosp. Emerg. Care 10(3), 314–316 (2006)
Li, J., Sun, A., Han, J., Li, C.: A survey on deep learning for named entity recognition. arXiv preprint arXiv:1812.09449 (2018)
Gehrmann, S., et al.: Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives. PloS One 13(2), e0192360 (2018)
Acknowledgement
This work was supported by National Science Foundation (NSF) Award #1948292. We would like to thank the ESO company for sharing their EHR system with us so we can create a hypothetical EHR system based on their design. We also want to thank our research participants for providing valuable feedback.
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Zhang, Z., Luo, X., Harris, R., George, S., Finkelstein, J. (2022). Hands-Free Electronic Documentation in Emergency Care Work Through Smart Glasses. In: Smits, M. (eds) Information for a Better World: Shaping the Global Future. iConference 2022. Lecture Notes in Computer Science(), vol 13193. Springer, Cham. https://doi.org/10.1007/978-3-030-96960-8_21
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