We believe patient-reported and behavior data belongs in an EMR. Here are our thoughts on how that could work – what else would you suggest?
Image: Dashboard overview page
Search “EMR” on Google images, and you’ll get rows of dense layouts featuring prescription data, lab results and symptom lists. It is mostly biometric data that is seen as the standard information needed to treat a patient and get an accurate picture of how things are going. It’s data that is important and useful, but incomplete in that much of it is only as accurate as the options given or the moment in time at which it was taken.
The trend towards adding communication channels to EMRs (the “Post EHR Era”) shows a desire to augment this data with more timely information that connects the patient and the physician. Whether this means incorporating more patient-reported data that defines how a symptom impacts a patient’s life or creating new metrics around behavior data, it will most likely involve a redesign of the traditional EMR to provide a picture of the whole patient, not just a collection of measurable values.
A number of new systems are focused on collecting patient-reported data and/or the behavior data that may one day become a standard way of measuring overall patient well-being. At Ginger.io, our platform uses a smartphone application to collect both patient-reported and behavior data to drive health insights. We see this information — and the health data that systems like ours can create using it — fitting in with an EMR in a few distinct ways:
● Objective and real-time data to supplement static results: We envision future EMRs updating themselves between patient visits when things change measurably for a patient. PRO data and the behavior data we collect will allow physicians and care teams to have a real lens into how their patients are doing day-to-day.
● An alert that can drive action between visits: One of the challenges with bringing real-time data into daily practice is that it can often result in too many numbers. It is unclear what the provider should do with the data, and it often takes valuable, unreimbursable time to parse through it. Our approach is to start by first showing data in an aggregate, easily actionable form.
● Population-level as well as individual-level information: Much of the information collected in EMRs today derives from years of longitudinal research that highlights patterns. By allowing physicians to compare data across a population in an on-going fashion, additional trends in care and conditions can become apparent.
As we continue to think through how our product fits in with established and new EMR systems, we’d welcome ideas and thought partners. How do you think patient-reported and behavioral data could one day exist in an EMR? Send us your thoughts at email@example.com or tweet us at @ginger_io.
Julia Bernstein is part of the team at Ginger.io, where she helps lead the Sales and Marketing effort. Previously, she was a consultant in McKinsey & Co’s Boston office, where she focused on healthcare. She also worked for the e-commerce start-up Citrus Lane. She is a graduate of from Dartmouth College and the Stanford Graduate School of Business.