CC BY 4.0 · ACI open 2024; 08(02): e62-e68
DOI: 10.1055/s-0044-1788621
Research Article

Enhancing Secure Messaging in Electronic Health Records: Evaluating the Impact of Emoji Chat Reactions on the Volume of Interruptive Notifications

John Will
1   MCIT Department of Health Informatics, NYU Langone Health, New York, New York, United States
,
William Small
1   MCIT Department of Health Informatics, NYU Langone Health, New York, New York, United States
2   Department of Medicine, NYU Grossman School of Medicine, New York, New York, United States
,
Eduardo Iturrate
1   MCIT Department of Health Informatics, NYU Langone Health, New York, New York, United States
2   Department of Medicine, NYU Grossman School of Medicine, New York, New York, United States
,
Paul Testa
1   MCIT Department of Health Informatics, NYU Langone Health, New York, New York, United States
3   Ronald O. Perelman Department of Emergency Medicine, NYU Grossman School of Medicine, New York, New York, United States
,
Jonah Feldman
1   MCIT Department of Health Informatics, NYU Langone Health, New York, New York, United States
4   Department of Medicine, NYU Grossman Long Island, School of Medicine, Mineola, New York, United States
› Institutsangaben

Funding None declared.

Abstract

Background Electronic health record secure messaging (EHRSM) is an increasingly utilized tool for communication among clinicians. However, there is concern about the growing quantity of disruptions it presents via interruptive notification.

Objectives The primary aim of this study is to assess whether introducing emoji reactions, which do not trigger push notifications in EHRSM, can alleviate the burden of interruptive notifications. The second aim is to use messaging notification metadata to identify subgroups that might benefit from targeted interventions to aid the adoption of this innovation.

Methods We implemented the emoji reaction feature into EHRSM across a large academic health system. We evaluated the volume of push notifications 11 weeks before (pre-emoji period) and after (post-emoji period) introducing emoji reactions in EHRSM. Notification metadata was categorized by user type, and users were stratified based on notification volume.

Results There were 1,387,506 fewer push notifications in the post-emoji period (a decrease of 4.7%). Subgroups of users with increasing mean daily push notifications in the pre-emoji period were associated with decreasing mean daily push notifications in the post-emoji period. Among the eight user subgroups, six experienced a significant reduction in interruptive notifications, with the pharmacy and “other” subgroups not observing a reduction. Users in the top quartile of notification volume saw the greatest reduction in burden across each user subgroup.

Conclusion Integrating emoji reactions into EHRSM across a large academic health system significantly reduced the burden of push notifications among EHRSM users. Utilizing messaging notification metadata allowed us to identify subgroups that require additional intervention.

Protection of Human and Animal Subjects

We completed NYULH's self-certification form determining our work does not involve human subjects and does not require Institutional Review Board review.




Publikationsverlauf

Eingereicht: 17. November 2023

Angenommen: 27. Juni 2024

Artikel online veröffentlicht:
25. Juli 2024

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 
  • References

  • 1 Baratta LR, Harford D, Sinsky CA, Kannampallil T, Lou SS. Characterizing the patterns of electronic health record-integrated secure messaging use: cross-sectional study. J Med Internet Res 2023; 25 (01) e48583
  • 2 O'Leary KJ, Liebovitz DM, Wu RC. et al. Hospital-based clinicians' use of technology for patient care-related communication: a national survey. J Hosp Med 2017; 12 (07) 530-535
  • 3 Martin G, Khajuria A, Arora S, King D, Ashrafian H, Darzi A. The impact of mobile technology on teamwork and communication in hospitals: a systematic review. J Am Med Inform Assoc 2019; 26 (04) 339-355
  • 4 Nguyen C, McElroy LM, Abecassis MM, Holl JL, Ladner DP. The use of technology for urgent clinician to clinician communications: a systematic review of the literature. Int J Med Inform 2015; 84 (02) 101-110
  • 5 Kellogg KM, Puthumana JS, Fong A, Adams KT, Ratwani RM. Understanding the types and effects of clinical interruptions and distractions recorded in a multihospital patient safety reporting system. J Patient Saf 2021; 17 (08) e1394-e1400
  • 6 Khairat S, Whitt S, Craven CK, Pak Y, Shyu CR, Gong Y. Investigating the impact of intensive care unit interruptions on patient safety events and electronic health records use: an observational study. J Patient Saf 2021; 17 (04) e321-e326
  • 7 Nijor S, Rallis G, Lad N, Gokcen E. Patient safety issues from information overload in electronic medical records. J Patient Saf 2022; 18 (06) e999-e1003
  • 8 Pickering BW, Herasevich V, Ahmed A, Gajic O. Novel representation of clinical information in the ICU: developing user interfaces which reduce information overload. Appl Clin Inform 2010; 1 (02) 116-131
  • 9 Aziz S, Barber J, Singh A, Alayari A, Rassbach CE. Resident and nurse perspectives on the use of secure text messaging systems. J Hosp Med 2022; 17 (11) 880-887
  • 10 Tai-Seale M, Dillon EC, Yang Y. et al. Physicians' well-being linked to in-basket messages generated by algorithms in electronic health records. Health Aff (Millwood) 2019; 38 (07) 1073-1078
  • 11 Small W, Iturrate E, Austrian J, Genes N. Electronic health record messaging patterns of health care professionals in inpatient medicine. JAMA Netw Open 2023; 6 (12) e2349136-e2349136
  • 12 He S, Lee J, Davis K. Interpreting emoji-a language for enhancing communication in health care. JAMA Netw Open 2023; 6 (06) e2318073
  • 13 Equator Network. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. The EQUATOR Network. Accessed March 6, 2023 at: https://www.equator-network.org/reporting-guidelines/strobe/
  • 14 SQL Developer. Oracle.com, 2022. Accessed April 12, 2024 at: www.oracle.com/database/sqldeveloper/
  • 15 IBM SPSS Statistics. Accessed April 12, 2024 at: www.ibm.com/products/spss-statistics/
  • 16 Quan SD, Wu RC, Rossos PG. et al. It's not about pager replacement: an in-depth look at the interprofessional nature of communication in healthcare. J Hosp Med 2013; 8 (03) 137-143
  • 17 Knight E, Sanderson P, Neal A, Ballard T. Interruptions in healthcare: modeling dynamic processes and effects at a team level. Appl Ergon 2023; 112: 104051-104051