The Use of Photoplethysmography to Study Emergency Physicians During Shifts
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CitationPeters, Gregory. 2020. The Use of Photoplethysmography to Study Emergency Physicians During Shifts. Doctoral dissertation, Harvard Medical School.
AbstractBackground: The high prevalence of physician burnout, particularly in emergency medicine, has garnered national attention in recent years. Objective means of measuring stress while at work can facilitate research into stress reduction interventions, and
wearable photoplethysmography (PPG) technology has been proposed as a potential solution. However, the use of low-burden wearable biosensors to study training and clinical practice among emergency physicians (EP) remains untested.
Objective: This pilot study aimed to (1) determine the feasibility of recording on-shift photoplethysmographic data from EP, (2) assess the quality of these data, and (3) calculate standard pulse rate variability (PRV) metrics from the acquired dataset and examine patterns in these variables over the course of an academic year.
Methods: A total of 21 EP wore PPG biosensors on their wrists during clinical work in the emergency department during a 9-hour shift. Recordings were collected during the first quarter of the academic year, then again during the fourth quarter of the
same year for comparison. The overall rate of usable data collection per time was computed. Standard pulse rate (PR) and PRV metrics from these two time points were calculated and entered into Student t tests.
Results: More than 400 hours of data were entered into these analyses. Interpretable data were captured during 8.54% of the total recording time overall. In the fourth quarter of the academic year compared with the first quarter, there was no significant
difference in median PR (75.8 vs 76.8; P=.57), mean R-R interval (0.81 vs 0.80; P=.32), SD of R-R interval (0.11 vs 0.11; P=.93), root mean square of successive difference of R-R interval (0.81 vs 0.80; P=.96), low-frequency power (3.5×103 vs 3.4×103;
P=.79), high-frequency power (8.5×103 vs 8.3×103; P=.91), or low-frequency to high-frequency ratio (0.42 vs 0.41; P=.43), respectively. Power estimates for each of these tests exceeded .90. A secondary analysis of the resident-only subgroup similarly showed no significant differences over time, despite power estimates greater than .80.
Conclusions: Although the use of PPG biosensors to record real-time physiological data from EP while providing clinical care seems operationally feasible, this study fails to support the notion that such an approach can efficiently provide reliable estimates
of metrics of interest. No significant differences in PR or PRV metrics were found at the end of the year compared with the beginning. Although these methods may offer useful applications to other domains, it may currently have limited utility in the contexts of physician training and wellness.
Citable link to this pagehttps://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37364986