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Of positivity, negativity, and f-bombs: EHR language as an indicator of physician burnout

Article

Study finds inbasket messages may offer more clues about improving patient experience than doctors’ feelings on the job.

Of positivity, negativity, and f-bombs: EHR language as an indicator of physician burnout

Although physicians may dread large numbers of new messages in their inbaskets, quantity of messages may not be an indicator of burnout.

But quality of messages – positive or negative – may show areas where the patient experience needs improvement.

The findings were part of a study of words contained in messages sent to 609 physicians through electronic health records (EHR) at University of California San Diego Health. The study, “Association of Electronic Health Record Inbasket Message Characteristics With Physician Burnout,” was published in JAMA Network Open.

Words count

Researchers analyzed word counts and other factors, such as use of all capital letters or degree modifiers such as “very,” in more than 1.45 million inbasket messages sent from April to September 2020.

Physicians were surveyed on their feelings of burnout and those who reported more burnout received more messages overall and from patients, than doctors who were not feeling burnout. But those differences were not significant, the study said.

For both groups, the messages overall and from patients were far more positive than negative. Patient messages to physicians with burnout had the highest positive ratings at 69%.

“We did not find significant associations between burnout and message sentiment,” the study said.

Cussing out the doctor

But the list “of high-frequency words included many expletives, demonstrating the animosity of some messages arriving at physicians’ inbaskets,” the study said. High-frequency words that reflect violence or hatred are concerning, especially in light of recent patient-inflicted violence against physicians, the study said.

“Some of these messages expressed negativity specifically directed toward physicians, while others expressed frustrations at the challenges of navigating complex health care systems or laments regarding clinical conditions,” the study said. “These messages could still be stressful for physicians, particularly if the patients’ frustration is related to factors beyond the individual physician’s control. However, these messages highlight the need for health systems to examine root causes of patient frustrations and improve patient engagement in their care.”

The study included examples of patient messages to physicians using expletives or profanity. The f-word landed ninth on the top 10 list of most-used words in patient messages “with overall negative sentiment score.”

The other top nine negative words: cancel, pain, no, risk, cancer, problem, stop, low, and lower. The top 10 positive words: thank, haha, help, care, good, well, best, sure, OK, and hope.

Civility solutions

The researchers proposed potential solutions for improving communication and civility in EHR messaging:

  • Health systems should ensure the inbasket is not a venue for physician abuse and cyberbullying.
  • EHR portals could have reminders to use kind language when sending messages.
  • Electronic filters could block expletives or threatening words.
  • EHR programs could use frameworks to identify patients who frequently send negative messages.

“There may also be opportunities for educating physicians how to handle electronic communications, as training on electronic communication if fairly lacking,” the study said.

Health systems also can analyze message language “to identify systems issues associated with patient negativity,” and make efforts to improve those patient experiences and outcomes.

Limitations

The researchers noted the study dealt with one health system and the physician survey may have underestimated burnout at the start of the COVID-19 pandemic. They also used a general layperson lexicon, not a medical one, so clinical terms may be undercounted.

“Additionally, this was an observational study which is inherently limited in its ability to establish causality,” the study said.

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