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TABLE I. Descriptions and Availability for the Reported PEP Metrics.

Activity Name

Per Day

Per Appt

Example EHR Tasks

Chart review

X

X

Review of prior notes and documentation Review of medication and allergies Review of data (labs, imaging, pathology) Review of scanned media from outside referrals Responding to telephone encounters & staff messages Reviewing cc ’ d charts Patient portal communications Responding to noti fi cations for completed orders, eg, surgical pathology, laboratory, and imaging, etc. Progress note composition including typing, voice recognition software, and note writing tools Letter and communication composition Electronically completing orders including medications, labs, referrals, imaging, and billing codes

In basket

X

X

Notes

X

X

Orders

X

X

Other

X

Viewing and interacting with dashboards Creating and managing note templates Reviewing patient lists Reporting functionality (if utilized) Viewing and interacting with any schedule

—

Schedule

X X

—

Visit Navigator

Interaction with the visit navigator, including reason for visit, medical, surgical, and family history activities

—

User activity log time was recorded based on interactions with “ Example EHR Tasks ” shown in rightmost column. Four metrics were available both in “ Time in Activity per Day ” and “ Time in Activity Per Appointment, ” while three metrics were only available on a per day basis as shown in the middle two columns. EHR = electronic health record; PEP = provider ef fi ciency pro fi le; X = reported, — = not reported.

logged into the EHR that month. The denominator for PEP met rics “ time in activity per appointment ” is the number of appoint ments scheduled for the provider during that month. The availability and examples of common activities for each PEP metric are detailed in Table I. Statistical analysis and statistical fi gures were created with rStudio, (Foundation for Statistical Computing, Vienna, Austria). Pearson correlation was used to determination relationships between two continuous variables. ANOVA testing was used to test different continuous variable between categories, and Tukey post hoc analysis was used to determine estimates for mean dif ference between groups.

assistant CMIO, and/or department chair), the physician well being team at the EHR vendor (Epic Systems Corporation) pro vided the data from participating institutions to the research team. In discussions with the EHR vendor, the variables had recently undergone an overhaul in capture and calculation, thus the most reliable and reproducible data was the 6 months from January 1, 2019, to June 30, 2019. De-identi fi ed individual pro vider data were provided to the authors, and at the request of the participating institutions, participating institutions were also de-identi fi ed. Only providers with scheduled visits, physicians, and advance practice providers (APPs), are currently tracked in the PEP data. Thus, values for residents, nurses, medical assis tants, and fellows were not recorded and could not be analyzed. Fellows with their own patient schedules were included, but they were not able to be separated from attending physicians. The quantitative assessment of many of the PEP data vari ables are intuitive (eg, progress note in length in characters, number of visits per day, etc.). The methodology for calculating PEP variables related to time is as follows. Time begins when the activity is selected and continues while the user is actively interacting (clicking, typing, scrolling, etc.) within the activity. Time continues to be tracked until either 5 sec of inactivity or the user logs out. Even if the EHR is still open, any idle time over 5 sec is not counted as part of that metric ’ s value. If another activity is selected, time continues to be recorded but it is attrib uted to that new activity. For a given provider, all time in each activity is summed into one numerator for the month. This numerator includes time spent in the activity during clinic hours but also includes time outside traditional clinic hours such as evenings, early mornings, or weekends — often referred to as “ pajama time. ” At the time of data collection, the PEP metric “ pajama time, ” de fi ned by the vendor in January 2020 as time in the EHR on evenings (5 PM – 7 AM) and weekends, had not been validated and thus could not be separately reported. Metric values are then calculated by dividing the total time in activity numerator by the denominator. In the case of PEP metrics “ time in activity per day, ” the denominator is the number of days

Fig. 1. Histogram depicting the frequency of institution based on the size of the institution measured in number of providers.

Laryngoscope 131: May 2021

Giliberto et al.: National Time Spent in EHR

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