Healthcare is notoriously slow when it comes to implementing health IT, and one stakeholder claims AI in healthcare won’t be the force for change it has the potential to be until providers are no longer so connected to their computers.

That sounds a bit counterintuitive, but what Harjinder Sandhu, CEO of Saykara, maker of a voice-activated, AI-driven physician’s assistant, means is that for too long providers have been kept connected to their computers at the expense of interacting with their patients.  And the net outcome has too often been less than satisfactory patient experiences as well as less than thorough appointment notes.

In a commentary at MedCityNews, Sandhu recounts the technological “fixes” that were supposed to revolutionize healthcare but haven’t fully lived up to expectations.

For example, he notes, “(t)he promise of EHRs was that they would create a wealth of actionable data that could be leveraged for better patient care. Unfortunately, this promise never fully materialized. Most of the interesting information that can be captured in the course of patient care either is not or is captured minimally or inconsistently. Often, just enough information is recorded in the EHR to support billing and is in plain text (not actionable) form. Worse, documentation requirements have had a serious impact on physicians, to whom it ultimately fell to input much of that data. Burnout and job dissatisfaction among physicians have become endemic.”

One response to that dilemma – at least for those practices with adequate means – has been the hiring of “human scribes” who do the note-taking while provider focuses on the patient. The problem there, he says, is that “the inherent cost of both training and then employing a scribe has led to many efforts to build digital counterparts, AI-based scribes that can replicate the work of a human scribe.”

But building an AI scribe, at least an effective one, is not an easy task.

“It requires a substantially more sophisticated system than the current generation of speech recognition systems,” Sandu explains. “Interpreting natural language conversation is one of the next major frontiers for AI in any domain. The current generation of virtual assistants, like Alexa and Siri, simplify the challenge by putting boundaries on speech . . .  In contrast, an AI system that is listening to doctor-patient conversations must deal with the complexity of human speech and narrative. A patient visit could last five minutes or an hour, the speech involves at least two parties (the doctor and the patient), and a patient’s visit can meander to irrelevant details and branches that don’t necessarily contribute to a physician making their diagnosis.”

Still, change is in fact coming, he says, and while it’s still early for fully autonomous AI scribes, “AI systems augmented by human power are filling in the gaps of AI competency and allowing these systems to succeed while incrementally chipping away at the goal of making these systems fully autonomous.”