Conversations With Kohli | Patient-Generated Health Data – A Physician's Friend or Foe?

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It was a typical morning in cardiology clinic. I was over 25 minutes behind schedule for my appointments. I needed to tighten up the rest of my morning visits to have any hope of staying on time in order to get a better score on my patient-satisfaction survey, which our practice routinely uses to assess us.

My next patient was a 65-year-old man with atrial fibrillation (AFib) in for routine follow-up. His AFib had always been asymptomatic so I anticipated a quick look at his vital signs and an “easy” visit that would help get my schedule back on track.

As I entered the room, I saw him eagerly waiting, seated on the exam table with his shirt off. But my heart sank when I looked down to see a binder in his hand. As he handed it to me, I reluctantly forged a smile and opened it. I stared at a stack of papers with a collage of color-coded tables, graphs and charts – one for each day for three months. With his smartwatch, he’d tracked his heart rate every hour of every day since our last visit three months ago. He’d correlated his heart rate with his exercise, sleep patterns, nutrition and stress levels.

I was simultaneously awed and dumbfounded. The marvels of modern technology have allowed us to systematically deconstruct human behavior in a manner for patterns to emerge that may guide treatment decisions.

I was also hesitant. The accuracy of this patient-generated data – from data collection by a smartwatch to the patient’s input on behavior and reporting the data – was unvalidated. As an evidence-based physician, I’m accustomed to making decisions based only on validated high-quality data. I floundered in my decision making and not knowing whether to rely on this patient’s intricate graphs and charts to titrate his medication doses.

His binder raises so many questions relevant to the practice of medicine in this era. How much information is too much for the physician to process? In the era of exploding health technology startups, which tout everything from tracking mindfulness to symptoms for chronic disease management and vital signs like blood pressure and oxygenation, how do we limit how rapidly this information grows? When does it become too much?

Does this form of data collection need to be validated before it is used? Does tracking patient health information so closely affect the information we’re collecting and alter patient behavior negatively? For my AFib patient the pattern was clear: every time his heart rate went above 100 beats a minute, there was a spike in his “stress level” graph a few minutes later and then his blood pressure.

Should we incorporate these types of data formally into the medical record as we do with office vital signs? And, are these so-called incremental medical technology advancements helping or hurting progress in the way we practice?

The visit took longer than expected. Not just because of the sheer number of pages I had to process and document in my note. But because it left me baffled about the best way to care for my patients in a world where technology has so fundamentally changed the way we live.

I told him we’d need old-fashioned Holter monitoring to track his heart rate and correlate it with his smartwatch before changing his medications.

As I left the office, I saw his furrowed brows, unsatisfied that his data collection had not been more carefully incorporated into his treatment plan.

I also furrowed my brows, asking myself whether those 40 minutes looking over his graphs was the best use of our time together.

How do you handle patient-generated data in your practice? Join the conversation on Twitter. To answer Dr. Kohli’s question, tag @ACCinTouch.

Clinical Topics: Arrhythmias and Clinical EP, SCD/Ventricular Arrhythmias, Atrial Fibrillation/Supraventricular Arrhythmias

Keywords: ACC Publications, Cardiology Magazine, ACC18, ACC Annual Scientific Session, Electrocardiography, Ambulatory, Heart Rate, Blood Pressure, Patient Satisfaction, Atrial Fibrillation, Mindfulness, Follow-Up Studies, Blood Pressure Determination, Biomedical Technology, Decision Making, Disease Management

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