Impatience is said to be the stance of modern technology users, but a doctor sitting with a patient has good reason to be impatient. The afflicted person may be suffering from a condition where lost minutes could mean death, an amputated limb, or severe brain disfunction. Even if the patient’s condition is not so dire, there are probably a half dozen other people with painful complaints twiddling their thumbs in the waiting room while the doctor tries to guess at a course of treatment. And in the US today, guessing is often the only option.
Somewhere in the country, an expert has probably learned all about the medical condition at hand and even presented the solution at a conference. Relatively few medical crises are really new discoveries. But the current system of disseminating information through conferences, journals, and rotations, or even through newer media such as blogs and webinars, cannot reach the beleaguered doctor and patient at the point of care.
I got a glimpse of a solution in the book #SOCIALQI (which has an associate web site) by the multi-disciplinary biomedical researcher Brian McGowan. His first challenge to us is an assertion that the central problem holding back improvements in health care quality is the inadequate dissemination of knowledge. I could match this claim with several other urgent needs in the health care field: inconsistent and distorted recording of patient data, lack of standards for storage and data exchange, and resistance by doctors to patient engagement, to name a few. But McGowan’s first chapter makes a very persuasive argument: if the best practices of each site were instituted throughout the health care system, we’d save thousands of lives and drastically lower costs.
McGowan lays out in excellent, comprehensive strokes the bottlenecks holding back information exchange among three key groups in health care: patients, providers, and researchers. But his most intriguing proposal comes precisely half-way through the book on the first page of Chapter 7. Here he lays out a vision where information comes to the physician through an electronic medical record right at the point of decision making.
The software envisioned by McGowan would note that a doctor entered a symptom such as “shortness of breath” along with other facts about the patient and would immediately return relevant information that could help the doctor make an informed diagnosis and assign a treatment. This is reminiscent of IBM’s Watson (which McGowan touches on but does not compare to his solution) and might well be called “social Watson.” The medical product built on Watson searches the medical literature in real time and returns possible diagnoses based on an evaluation of the research. But McGowan’s system could be even more up-to-date and flexible because it would draw on other practitioners in a live chat fashion.
Naturally, a huge amount of technological development lies between our current situation and the realization of social Watson. McGowan finds promising elements of the solution among patients in organizations such as PatientsLikeMe, among doctors with services like MDchat, and among researchers with organizations such as Sage Bionetworks, which I have written about extensively. His proposals fall into the broad categories of collaboration and crowdsourcing. But there be dragons.
For instance, McGowan asks that systems for searching and filtering information be both “simple” and “flexible,” which the field of human-computer interaction widely recognizes as conflicting goals. I don’t believe it so easy to resolve information overload through filtering and critical thinking, which is the core of McGowan’s solution. I also question how a limited set of experts can answer the particular questions that each doctor has about each case.
Still, I like McGowan’s spirit and I hope he explores the point-of-care solution further. Separating education from practice, as we do now, burdens the doctor. Combining them will someday seem absolutely natural.