Freeing Up Time

As electronic medical records begin incorporating AI, Manisha J. Loss, associate chief medical information officer for Johns Hopkins Medicine, envisions a health care future with fewer administrative hassles, better patient experiences and more time for patient-centered care.

Already, pilot programs are underway at Johns Hopkins to use AI to draft notes based on clinical conversations, generate responses to patient queries in MyChart and categorize MyChart messages for triage based on clinical versus administrative concerns from patients.

But while AI technology can write notes, letters and MyChart responses, it doesn’t discern if the information is accurate or if its message would devastate a recipient. “We need to make sure we have transparency in understanding how these models generate their responses,” Loss says. “And even when we have that transparency, this is clinical care — we still need a clinician to lay eyes on it to make sure it’s appropriate.”

Yet in its own way, AI can be remarkably empathetic, able to explain difficult health news without the all-too-human burdens of emotion, exhaustion or distraction. “The patient gets a [written] response that’s thorough and kind and grammatically correct,” says Loss. It’s then up to clinicians to review those computer-generated words and use them as a starting point for their conversation. 

Freeing clinicians from clerical duties to prevent burnout and increase time with patients is the ideal. But: “We need to be wary of policies where we say, ‘This tool makes you more effective, and so we are going to ask you to do even more.’” 

Mark Dredze

Computer scientist Mark Dredze and colleagues made headlines last spring with a study, published in JAMA Internal Medicine, that looked at whether ChatGPT can respond accurately to the types of questions patients send to their doctors. Comparing written responses from human physicians and those from ChatGPT, a panel of licensed health care professionals preferred ChatGPT’s answers 79% of the time. The panel perceived ChatGPT’s responses to be more empathetic.

While physicians are under punishing time pressure, notes Dredze, “Sometimes all that is needed is to stop and say, ‘I’m sorry you’re going through this.’ It’s such a simple thing, and computers are easily able to remember to do that — especially in writing. Computers have all the time in the world to make empathetic statements.”

“There should be prompt and proper disclosure that the doctor is using AI to write the notes in order to maintain trust with the patient: ‘This was generated by ChatGPT but reviewed by a doctor.’”

Tinglong Dai

Manisha J. Loss

Manisha J. Loss, associate chief medical information officer for Johns Hopkins Medicine and associate professor of dermatology, is working to bring AI technologies to electronic medical records.
A portrait of Manisha J. Loss wearing her white coat

Mark Dredze

Computer scientist Mark Dredze is director of research for the Johns Hopkins AI-X Foundry, which drives AI research and its applications in health, scientific discovery and safety.
A photo of Mark Dredze smiling and wearing a collared shirt

Tinglong Dai

Tinglong Dai, a professor of operations management and business analytics at Johns Hopkins Carey Business School, leads research on human–AI interaction.
A portrait of Tinglong Dai wearing a striped suit.