Literature DB >> 33475754

Evaluation of Attention Switching and Duration of Electronic Inbox Work Among Primary Care Physicians.

Tracy A Lieu1,2, E Margaret Warton1, Jeffrey A East2,3,4, Mark F Moeller2,5, Stephanie Prausnitz1, Manuel Ballesca2,5, Gloria Mark6, Fatema Akbar6, Sameer Awsare2, Yi-Fen Irene Chen2, Mary E Reed1.   

Abstract

Importance: Primary care physicians (PCPs) report multitasking during workdays while processing electronic inbox messages, but scant systematic information exists on attention switching and its correlates in the health care setting.
Objectives: To describe PCPs' frequency of attention switching associated with electronic inbox work, identify potentially modifiable factors associated with attention switching and inbox work duration, and compare the relative association of attention switching and other factors with inbox work duration. Design, Setting, and Participants: This cross-sectional study of the work of 1275 PCPs in an integrated group serving 4.5 million patients used electronic health record (EHR) access logs from March 1 to 31, 2018, to evaluate PCPs' frequency of attention switching. Statistical analysis was performed from October 15, 2018, to August 28, 2020. Main Outcomes and Measures: Attention switching was defined as switching between the electronic inbox, other EHR work, and non-EHR periods. Inbox work duration included minutes spent on electronic inbox message views and related EHR tasks. Multivariable models controlled for the exposures.
Results: The 1275 PCPs studied (721 women [56.5%]; mean [SD] age, 45.9 [8.5] years) had a mean (SD) of 9.0 (7.6) years of experience with the medical group and received a mean (SD) of 332.6 (148.3) (interquartile range, 252-418) new inbox messages weekly. On workdays, PCPs made a mean (SD) of 79.4 (21.8) attention switches associated with inbox work and did a mean (SD) 64.2 (18.7) minutes of inbox work over the course of 24 hours on workdays. In the model for attention switching, each additional patient secure message beyond the reference value was associated with 0.289 (95% CI, 0.217-0.362) additional switches, each additional results message was associated with 0.203 (95% CI, 0.127-0.278) additional switches, each additional request message was associated with 0.190 (95% CI, 0.124-0.257) additional switches, and each additional administrative message was associated with 0.262 (95% CI, 0.166-0.358) additional switches. Having a panel (a list of patients assigned to a primary care team) with more elderly patients (0.144 switches per percentage increase [95% CI, 0.009-0.278]) and higher inbox work duration (0.468 switches per additional minute of inbox work [95% CI, 0.411-0.524]) were also associated with higher attention switching involving the inbox. In the model for inbox work duration, each additional patient secure message beyond the reference value was associated with 0.151 (95% CI, 0.085-0.217) additional minutes, each additional results message was associated with 0.338 (95% CI, 0.272-0.404) additional minutes, each additional request message was associated with 0.101 (95% CI, 0.041-0.161) additional minutes, and each additional administrative message was associated with 0.179 (95% CI, 0.093-0.265) additional minutes. A higher percentage of the panel's patients initiating messages (0.386 minutes per percentage increase [95% CI, 0.026-0.745]) and attention switches (0.373 minutes per switch [95% CI, 0.328-0.419]) were also associated with higher inbox work duration. In addition, working at a medical center where all PCPs had high inbox work duration was independently associated with high or low inbox work duration. Conclusions and Relevance: This study suggests that PCPs make frequent attention switches during workdays while processing electronic inbox messages. Message quantity was associated with both attention switching and inbox work duration. Physician and patient panel characteristics had less association with attention switching and inbox work duration. Assisting PCPs with message quantity might help modulate both attention switching and inbox work duration.

Entities:  

Year:  2021        PMID: 33475754      PMCID: PMC7821028          DOI: 10.1001/jamanetworkopen.2020.31856

Source DB:  PubMed          Journal:  JAMA Netw Open        ISSN: 2574-3805


  21 in total

1.  Executive control of cognitive processes in task switching.

Authors:  J S Rubinstein; D E Meyer; J E Evans
Journal:  J Exp Psychol Hum Percept Perform       Date:  2001-08       Impact factor: 3.332

2.  Association of interruptions with an increased risk and severity of medication administration errors.

Authors:  Johanna I Westbrook; Amanda Woods; Marilyn I Rob; William T M Dunsmuir; Richard O Day
Journal:  Arch Intern Med       Date:  2010-04-26

3.  Practicing Clinicians' Recommendations to Reduce Burden from the Electronic Health Record Inbox: a Mixed-Methods Study.

Authors:  Daniel R Murphy; Tyler Satterly; Traber D Giardina; Dean F Sittig; Hardeep Singh
Journal:  J Gen Intern Med       Date:  2019-07-10       Impact factor: 5.128

4.  Are specific elements of electronic health record use associated with clinician burnout more than others?

Authors:  Ross W Hilliard; Jacqueline Haskell; Rebekah L Gardner
Journal:  J Am Med Inform Assoc       Date:  2020-07-01       Impact factor: 4.497

5.  Physicians' electronic inbox work patterns and factors associated with high inbox work duration.

Authors:  Fatema Akbar; Gloria Mark; E Margaret Warton; Mary E Reed; Stephanie Prausnitz; Jeffrey A East; Mark F Moeller; Tracy A Lieu
Journal:  J Am Med Inform Assoc       Date:  2021-04-23       Impact factor: 4.497

6.  Tethered to the EHR: Primary Care Physician Workload Assessment Using EHR Event Log Data and Time-Motion Observations.

Authors:  Brian G Arndt; John W Beasley; Michelle D Watkinson; Jonathan L Temte; Wen-Jan Tuan; Christine A Sinsky; Valerie J Gilchrist
Journal:  Ann Fam Med       Date:  2017-09       Impact factor: 5.166

7.  Electronic Health Record Logs Indicate That Physicians Split Time Evenly Between Seeing Patients And Desktop Medicine.

Authors:  Ming Tai-Seale; Cliff W Olson; Jinnan Li; Albert S Chan; Criss Morikawa; Meg Durbin; Wei Wang; Harold S Luft
Journal:  Health Aff (Millwood)       Date:  2017-04-01       Impact factor: 6.301

8.  Metrics for assessing physician activity using electronic health record log data.

Authors:  Christine A Sinsky; Adam Rule; Genna Cohen; Brian G Arndt; Tait D Shanafelt; Christopher D Sharp; Sally L Baxter; Ming Tai-Seale; Sherry Yan; You Chen; Julia Adler-Milstein; Michelle Hribar
Journal:  J Am Med Inform Assoc       Date:  2020-04-01       Impact factor: 4.497

9.  Allocation of Physician Time in Ambulatory Practice: A Time and Motion Study in 4 Specialties.

Authors:  Christine Sinsky; Lacey Colligan; Ling Li; Mirela Prgomet; Sam Reynolds; Lindsey Goeders; Johanna Westbrook; Michael Tutty; George Blike
Journal:  Ann Intern Med       Date:  2016-09-06       Impact factor: 25.391

10.  An Exploration of Barriers, Facilitators, and Suggestions for Improving Electronic Health Record Inbox-Related Usability: A Qualitative Analysis.

Authors:  Daniel R Murphy; Traber D Giardina; Tyler Satterly; Dean F Sittig; Hardeep Singh
Journal:  JAMA Netw Open       Date:  2019-10-02
View more
  3 in total

1.  Predicting physician burnout using clinical activity logs: Model performance and lessons learned.

Authors:  Sunny S Lou; Hanyang Liu; Benjamin C Warner; Derek Harford; Chenyang Lu; Thomas Kannampallil
Journal:  J Biomed Inform       Date:  2022-02-05       Impact factor: 6.317

2.  Improving the turnaround times of infectious disease markers reporting in an NHS stem cell department.

Authors:  Ying Li; Nathan Proudlove
Journal:  BMJ Open Qual       Date:  2022-06

3.  Measuring and Maximizing Undivided Attention in the Context of Electronic Health Records.

Authors:  You Chen; Julia Adler-Milstein; Christine A Sinsky
Journal:  Appl Clin Inform       Date:  2022-07-05       Impact factor: 2.762

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.