Promoting Quality Face-to-Face Communication during Ophthalmology Encounters in the Electronic Health Record Era

Abstract

Objective To evaluate informatics-enabled quality improvement (QI) strategies for promoting time spent on face-to-face communication between ophthalmologists and patients. Methods This prospective study involved deploying QI strategies during implementation of an enterprise-wide vendor electronic health record (EHR) in an outpatient academic ophthalmology department. Strategies included developing single sign-on capabilities, activating mobile- and tablet-based applications, EHR personalization training, creating novel workflows for team-based orders, and promoting problem-based charting to reduce documentation burden. Timing data were collected during 648 outpatient encounters. Outcomes included total time spent by the attending ophthalmologist on the patient, time spent on documentation, time spent on examination, and time spent talking with the patient. Metrics related to documentation efficiency, use of personalization features, use of team-based orders, and note length were also measured from the EHR efficiency portal and compared with averages for ophthalmologists nationwide using the same EHR. Results Time spent on exclusive face-to-face communication with patients initially decreased with EHR implementation (2.9 to 2.3 minutes, p = 0.005) but returned to the paper baseline by 6 months (2.8 minutes, p = 0.99). Observed participants outperformed national averages of ophthalmologists using the same vendor system on documentation time per appointment, number of customized note templates, number of customized order lists, utilization of team-based orders, note length, and time spent after-hours on EHR use. Conclusion Informatics-enabled QI interventions can promote patient-centeredness and face-to-face communication in high-volume outpatient ophthalmology encounters. By employing an array of interventions, time spent exclusively talking with the patient returned to levels equivalent to paper charts by 6 months after EHR implementation. This was achieved without requiring EHR redesign, use of scribes, or excessive after-hours work. Documentation efficiency can be achieved using interventions promoting personalization and team-based workflows. Given their efficacy in preserving face-to-face physician–patient interactions, these strategies may help alleviate risk of physician burnout.

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

“…Looking at specific measures of EHR use reported in each study reveals additional differences, particularly regarding durations of EHR use ( Figure 4 ). Reported time-based measures included total time in the EHR (49 articles), 3 , 4 , 19 , 24–33 , 35–49 , 51–59 , 61 , 66 , 69–73 , 77 , 79 , 95 , 98 time in notes (32 articles), 3 , 4 , 7 , 19 , 24–32 , 35–38 , 40–46 , 48 , 51 , 55–58 , 79 , 109 time in inbox (23 articles), 2–4 , 19 , 24 , 25 , 27–29 , 35–38 , 42 , 43 , 45 , 47 , 48 , 51 , 61 , 62 , 70 , 71 time in chart review (23 articles), 3 , 4 , 24–27 , 29 , 31 , 32 , 35 , 36 , 40 , 42 , …”

“…Twenty-two studies reported a measure based on a set time period, of which 7 unique periods were used (5:30 pm –8:30 am and 12:30 pm –1:30 pm , 5:30 pm –7 am , 6 pm –6 am , 6 pm –7 am , 7 pm –7 am , 7 pm –8 am , and 7:30 pm –7:30 am ). 4 , 6 , 19 , 25 , 27 , 29 , 32 , 34 , 36 , 39 , 40 , 42 , 48 , 49 , 51 , 53 , 55 , 66 , 69–71 An overlapping set of 22 articles, including 9 that also reported time period-based measures, reported at least 1 measure based on clinician schedules. 4 , 6 , 19 , 27 , 28 , 30 , 34 , 37 , 38 , 40 , 41 , 43 , 44 , 47–50 , 67 , 69 , 72 , 77 , 119 These included time outside scheduled hours on days with appointments, time on days without appointments, and time after the patient checked out.…”

“… 4 , 6 , 19 , 25 , 27 , 29 , 32 , 34 , 36 , 39 , 40 , 42 , 48 , 49 , 51 , 53 , 55 , 66 , 69–71 An overlapping set of 22 articles, including 9 that also reported time period-based measures, reported at least 1 measure based on clinician schedules. 4 , 6 , 19 , 27 , 28 , 30 , 34 , 37 , 38 , 40 , 41 , 43 , 44 , 47–50 , 67 , 69 , 72 , 77 , 119 These included time outside scheduled hours on days with appointments, time on days without appointments, and time after the patient checked out. These schedule-based measures differed in whether they (1) measured active EHR use or all time logged into the EHR, (2) included mid-day meetings or breaks in scheduled hours, or (3) included the 30 or 60 min before and after the first and last appointment of the day in scheduled hours.…”

Social Determinants of Health Data Availability for Patients with Eye Conditions

“… 37 However, EHR tools and predictive models can be used to optimize documentation and practice efficiency. 38 Prior studies have shown that although predictive modeling of EHRs has advanced rapidly, research describing actual implementation of these predictive models in clinical settings is lacking. 39 Finally, administrators may improve data collection by modifying the existing payment system (e.g., offering new incentives or developing new CMS evaluation and management coding guidelines) to reimburse providers for SDoH documentation.…”

Electronic Health Record Transition

“…Researchers assumed that it may take time to assimilate new practices and therefore we may see a change in perception early on but a return to baseline at 6 months as did other researchers. 19…”