Physicians’ electronic inbox work patterns and factors associated with high inbox work duration

Akbar, Fatema; Mark, Gloria; Warton, E. Margaret; Reed, Mary; Prausnitz, Stephanie; East, Jeffrey A; Moeller, Mark F; Lieu, Tracy A.

doi:10.1093/jamia/ocaa229

Cited by 35 publications

(39 citation statements)

References 27 publications

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“…Of this time, on average, approximately 33% of this time is spent on documentation, 13% on inbox activity, and 12% on orders ( Figure 2 ). 16 , 19 , 20 These values and proportions are consistent with previous literature 16 , 19 , 20 , 29 and can provide a benchmark for future measurement of standardized EHR use. Consistent with a case study from UCSF, 30 we found that female physicians spend more time on the EHR than their male colleagues, even after controlling for age, health system, medical specialty, and number of clinical hours scheduled.…”

Section: Discussionsupporting

confidence: 88%

Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis

Melnick

Ong

Fong

et al. 2021

Journal of the American Medical Informatics Association

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Objective To derive 7 proposed core electronic health record (EHR) use metrics across 2 healthcare systems with different EHR vendor product installations and examine factors associated with EHR time. Materials and Methods A cross-sectional analysis of ambulatory physicians EHR use across the Yale-New Haven and MedStar Health systems was performed for August 2019 using 7 proposed core EHR use metrics normalized to 8 hours of patient scheduled time. Results Five out of 7 proposed metrics could be measured in a population of nonteaching, exclusively ambulatory physicians. Among 573 physicians (Yale-New Haven N = 290, MedStar N = 283) in the analysis, median EHR-Time8 was 5.23 hours. Gender, additional clinical hours scheduled, and certain medical specialties were associated with EHR-Time8 after adjusting for age and health system on multivariable analysis. For every 8 hours of scheduled patient time, the model predicted these differences in EHR time (P < .001, unless otherwise indicated): female physicians +0.58 hours; each additional clinical hour scheduled per month −0.01 hours; practicing cardiology −1.30 hours; medical subspecialties −0.89 hours (except gastroenterology, P = .002); neurology/psychiatry −2.60 hours; obstetrics/gynecology −1.88 hours; pediatrics −1.05 hours (P = .001); sports/physical medicine and rehabilitation −3.25 hours; and surgical specialties −3.65 hours. Conclusions For every 8 hours of scheduled patient time, ambulatory physicians spend more than 5 hours on the EHR. Physician gender, specialty, and number of clinical hours practicing are associated with differences in EHR time. While audit logs remain a powerful tool for understanding physician EHR use, additional transparency, granularity, and standardization of vendor-derived EHR use data definitions are still necessary to standardize EHR use measurement.

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Section: Discussionsupporting

confidence: 88%

Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis

Melnick

Ong

Fong

et al. 2021

Journal of the American Medical Informatics Association

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“…Previous studies on EHR use patterns have quantified the time spent on different EHR activities within and outside of work hours [ 14 , 24 ]. However, variation among physicians is not well studied, and no previous study has attempted to characterize physicians based on their patterns of daily inbox use.…”

Section: Discussionmentioning

confidence: 99%

“…For EHR inbox management, a 2017 study [ 14 ] using EHR logs found that time spent in the inbox accounted for 24% of total EHR time, and of the time spent in the inbox, a larger proportion was spent after work hours compared with the time spent on other EHR activities. A study reported that 86% of surveyed physicians worked outside of work hours to respond to inbox messages [ 23 ], whereas another study reported that 37% of inbox work was done outside of work hours [ 24 ]. In addition to the time it takes within and outside of work hours, inbox-related burden has been attributed to the volume and source of EHR messages [ 5 , 7 ] and information overload from notifications (ie, asynchronous alerts) [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

Physician Stress During Electronic Health Record Inbox Work: In Situ Measurement With Wearable Sensors

Akbar¹,

Mark²,

Prausnitz³

et al. 2021

JMIR Med Inform

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Background Increased work through electronic health record (EHR) messaging is frequently cited as a factor of physician burnout. However, studies to date have relied on anecdotal or self-reported measures, which limit the ability to match EHR use patterns with continuous stress patterns throughout the day. Objective The aim of this study is to collect EHR use and physiologic stress data through unobtrusive means that provide objective and continuous measures, cluster distinct patterns of EHR inbox work, identify physicians’ daily physiologic stress patterns, and evaluate the association between EHR inbox work patterns and physician physiologic stress. Methods Physicians were recruited from 5 medical centers. Participants (N=47) were given wrist-worn devices (Garmin Vivosmart 3) with heart rate sensors to wear for 7 days. The devices measured physiological stress throughout the day based on heart rate variability (HRV). Perceived stress was also measured with self-reports through experience sampling and a one-time survey. From the EHR system logs, the time attributed to different activities was quantified. By using a clustering algorithm, distinct inbox work patterns were identified and their associated stress measures were compared. The effects of EHR use on physician stress were examined using a generalized linear mixed effects model. Results Physicians spent an average of 1.08 hours doing EHR inbox work out of an average total EHR time of 3.5 hours. Patient messages accounted for most of the inbox work time (mean 37%, SD 11%). A total of 3 patterns of inbox work emerged: inbox work mostly outside work hours, inbox work mostly during work hours, and inbox work extending after hours that were mostly contiguous to work hours. Across these 3 groups, physiologic stress patterns showed 3 periods in which stress increased: in the first hour of work, early in the afternoon, and in the evening. Physicians in group 1 had the longest average stress duration during work hours (80 out of 243 min of valid HRV data; P=.02), as measured by physiological sensors. Inbox work duration, the rate of EHR window switching (moving from one screen to another), the proportion of inbox work done outside of work hours, inbox work batching, and the day of the week were each independently associated with daily stress duration (marginal R2=15%). Individual-level random effects were significant and explained most of the variation in stress (conditional R2=98%). Conclusions This study is among the first to demonstrate associations between electronic inbox work and physiological stress. We identified 3 potentially modifiable factors associated with stress: EHR window switching, inbox work duration, and inbox work outside work hours. Organizations seeking to reduce physician stress may consider system-based changes to reduce EHR window switching or inbox work duration or the incorporation of inbox management time into work hours.

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“…Importantly, we found that MyChart messaging comprised nearly half of all RCs. Although the convenience and availability of such messaging overall has facilitated provider–patient communication in the era of digital healthcare, the administrative burdens of responding to RCs may have also increased for providers, 22,23 novel solutions to reduce RC burden are needed. Recently, Common Procedural Terminology codes 99421‐3 were introduced by the American Medical Association 24,25 to allow providers to bill for patient‐initiated digital communications, including MyChart and secure email.…”

Section: Discussionmentioning

confidence: 99%

A retrospective cohort study of clinical factors, visit patterns, and demographic factors associated with use of remote communications in patients with headache

et al. 2021

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Objective To identify the characteristics associated with high utilization of remote communications (RCs) in patients with headache. Background Patients with headache frequently communicate with their providers using secure portal messaging and telephone calls. However, clinical and demographic factors as well as visit patterns associated with RC utilization remain poorly characterized. Methods We retrospectively analyzed data from patients with headache who were evaluated in the ambulatory neurology faculty practice at the Icahn School of Medicine at Mount Sinai in New York between January 1 and June 30, 2019. We extracted clinical and demographic characteristics, total office visits, secure MyChart portal messages, and telephone encounters from our institutional data warehouse. We defined high RC and MyChart utilization as the top tertile of RC and MyChart message volume, respectively, and assessed the relationship between patient characteristics and high RC (primary outcome), as well as high MyChart utilization (secondary outcome). We characterized the relationship between clinicodemographic characteristics and the ratio of MyChart messages to total RCs (secondary outcome). Results We identified 1390 patients, of whom 477 (34.3%) were high RC utilizers and 321 (23.1%) were high MyChart utilizers. High RC utilizers generated 3306/3921 (84.3%) RCs. The presence of chronic headache (aOR 2.31, 95% CI 1.75–3.03, p < 0.0001), cluster headache (aOR 18.3, 95% CI 5.0–71.7, p = 0.001), and migraine (aOR 3.82, 95% CI 1.93–9.3, p = 0.011) was associated with high RC utilization. Patients ≥65 years of age were less likely to engage in MyChart messaging as a proportion of RC (191/680, 28.1%) compared with patients 18–30 years of age (243/620, 39.2%, p = 0.049) and 30–64 years of age (1172/2721, 43.1%, p < 0.0001). Conclusions A minority of patients with headache (477/1390; 34.3%) generated the majority (3306/3921; 84.3%) of RCs. Our findings should be validated in external patient cohorts with the objective of developing strategies to optimize RC utilization.

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Physicians’ electronic inbox work patterns and factors associated with high inbox work duration

Cited by 35 publications

References 27 publications

Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis

Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis

Physician Stress During Electronic Health Record Inbox Work: In Situ Measurement With Wearable Sensors

A retrospective cohort study of clinical factors, visit patterns, and demographic factors associated with use of remote communications in patients with headache

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