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Uptick in Patient Messages May Increase Physician Burnout
In an Oct. 12 Research Letter from JAMA Network Open entitled, “Trends in Electronic Health Record Inbox Messaging During the COVID-19 Pandemic in an Ambulatory Practice Network in New England,” the authors address COVID-19 related disruptions regarding how patients access routine care. They explain that anecdotal evidence indicates that ambulatory physicians saw an increase in patient medical advice requests (PMARs) and they compared patient message volume during the pandemic with levels pre-pandemic.
The letter states that “This cross-sectional study analyzed deidentified electronic health record metadata (Signal, Epic Systems) from March 2018 to June 2021 in a large ambulatory practice network in New England. This study was deemed exempt for review and informed consent by Yale University’s institutional review board because it involves secondary research of deidentified electronic health record metadata that did not include any patient identifier or private health information. This study follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.”
That said, “Trends in inbox message volume (categorized by message type and source), time in the inbox, visit volume and type (in-person vs telehealth), patient volume, and patient use of the patient portal were examined using descriptive statistics. Physician specialties were grouped into primary care, medical, and surgical specialties. Variables were compared before (March 2018 to February 2020) and during (March 2020 to June 2021) the COVID-19 pandemic. To assess whether the onset of the pandemic was an inflection point in PMARs, message volume per physician per day was modeled by piecewise linear regression using a spline for month with a single knot at March 2020 and Huber-White SEs. Three months of inbox message data were missing (3 of 40 months [7.5 percent]) and excluded from the analysis. To test for significance (P < .05), we used a 2-sided Wald test for equivalence of the coefficients. We used Stata statistical software version 16 (StataCorp) for data analyses.”
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