Emergency medicine residents spend over 7.5 months of their 3‐year residency on the electronic health record

Abstract

Background: Use of the electronic health record (EHR) is a standard component of modern patient care. Although EHRs have improved since inception, cumbersome workflows decrease the time for residents to spend on clinical and educational activities. This study aims to quantify the time spent interacting with the EHR during a 3-year emergency medicine (EM) residency. Methods: System records of time spent actively engaged in EHR use were analyzed for 98 unique EM residents over a period of 5 years from July 2015 to June 2020. Time spent on the EHR was totaled to give a career time, with a "work month" defined as a 4-week period of 70.5 h per week, based on Accreditation Council for Graduate Medical Education work hour restrictions for EM residents. Engagement in specific activities such as chart review, documentation preparation, and order entry were separately analyzed. Results: Over their 3-year training, a resident interacted with the EHR for 2,171 continuous hours. This amounts to 30.8 work weeks or 7.7 work months. Chart review was the most time-intensive activity at 11.42 weeks. Documentation accounted for 9.91 weeks, with an average career total of 7,280 notes created. Additionally, each resident spent 4.57 weeks on order entry, with 46,347 orders entered during training. While the number of charts opened increased after first year of residency, average time spent on each activity per patient decreased. Conclusions: This unique study quantifies the total time an EM resident spends on the EHR during a 3-year residency. Use of the EHR accounted for over 7.5 work months or nearly 21% of their training. Residents spend a substantial portion of their training interacting with the EHR and workflow improvements to reduce EHR time are critical for maximizing training time.

Using event logs to observe interactions with electronic health records: an updated scoping review shows increasing use of vendor-derived measures

“… 75 , 93 , 94 , 113 Only one of the experimental studies was a randomized controlled trial. 75 Across both observational and experimental studies, 41 articles compared EHR use across different groups of users including comparisons by specialty (14 studies), 4 , 7 , 25 , 29 , 31 , 36 , 42 , 48 , 51 , 58 , 59 , 85 , 105 , 115 clinical role (12), 24 , 26 , 33 , 37 , 46 , 65 , 76 , 95 , 99 , 106 , 108 , 115 gender (8), 19 , 34 , 47 , 49 , 66 , 68 , 70 , 106 year in residency (8), 31 , 32 , 35 , 39 , 52 , 56 , 57 , 95 organization (3), 24 , 44 , 75 and country (1). 27 Vendor-measure studies were more likely than investigator-measure studies to make such comparisons of EHR use by user group (65% vs 25...…”

“… 2–4 , 24 , 26 , 27 , 31 , 34–36 , 38 , 40 , 41 , 43–46 , 48–50 , 52 , 54 , 55 , 59 , 62 , 66 , 69–71 , 79 , 95 The next most popular denominators were number of appointments (12 articles), 24 , 25 , 29 , 30 , 32 , 35 , 38 , 40 , 42 , 44 , 72 , 77 and patients (9 articles). 26 , 31 , 39 , 41 , 51 , 53 , 56 , 57 , 98 Eleven other denominators were also used including EHR time per hour of clinic, per 8 h of clinic, per clinic session, per shift, per week, per month, per quarter, per year, per procedure, per note, and per residency.…”

“…Three of the most frequently mentioned limitations echo those observed in the prior review of audit log research 11 : EHR logs do not provide a full view of clinical activity which can involve physical and digital interactions outside the EHR (22 articles), 3 , 26 , 34 , 43 , 55 , 57 , 58 , 61 , 65 , 68 , 73 , 74 , 84–86 , 89 , 91 , 92 , 95 , 103 , 109 , 112 qualitative methods are needed to better understand the context and motivation for observed work (15 articles), 32 , 46 , 53 , 62 , 64 , 68 , 72 , 80 , 85 , 91 , 96 , 97 , 101 , 115 , 118 and logs may not contain enough detail to observe complex workflows (13 articles). 4 , 26 , 32 , 43 , 51 , 56 , 59 , 69 , 75 , 81 , 89 , 90 , 99…”