In the 10 years since my father was diagnosed with multiple myeloma, he has accumulated thousands of lab results, hundreds of physician progress notes, and dozens of imaging studies. Because his myeloma has been hard to treat, and perhaps because he is a well-regarded physician in his field, he has accessed the best care available, including fantastic doctors and new therapies available at distant research centers.
Despite the fact that all of his physicians use electronic health records (EHRs), nobody actually has his medical record. It does not exist. Rather, his thousands upon thousands of data points are scattered across the country, with no one health system or physician having unified access to all of it, including my dad.
As a clinical informaticist, I spend a lot of time thinking about interoperability—the extent to which systems are able to exchange data and subsequently present those data such that they can be understood by a user—but nothing prepared me for seeing my dad play the role of his own health data aggregator.
Tracking data over time is a key component of multiple myeloma care. Imaging scans looking for bone lesions and the "light chain" blood tests that measure the myeloma cancer protein are done periodically to assess response to treatments. Each result, depending on its direction, either brings a sigh of relief or a rise in stress and fear along with a shift in treatment regimen. To optimize my dad's care, his doctors would need to see the full picture: the imaging, labs, and each historical chemotherapy treatment over time.
You can imagine how this ideal interface would look, with a nice, clean graph showing his light chain results, imaging, medications tried (and failed), and the location of his treatment. But no such graph exists. Worse, it cannot exist in our current system because each health system where my father is treated is only responsible for their portion of his overall medical record.
Knowing the importance of keeping long-term records and the limitations of current interoperability, my dad maintains his own meticulous records. He has an Excel spreadsheet documenting the rises and falls in his light chains over the years, with results culled from at least seven different sources.
The Excel spreadsheet as a health tracker is not a hack unique to my dad. During my years as an endocrinologist, I have seen many people with diabetes leverage this tool. It's a sign that people with chronic disease want to monitor their data, but they need a solution that is universal, easy to access, and easy to share.
Communications are also fragmented. His primary internist, endocrinologist, oncologist, neurologist, transplant oncologist, and other physicians have no easy method of communicating with each other about his care. This isn't for lack of trying. They are all dedicated physicians, frequently picking up the phone to call each other, despite the fact that these phone calls represent free, after-hours care. However, they lack the opportunity for true collaborative team care.
My dad, like many other patients, often serves as the messenger from one physician to another. I consider this part of our nation's interoperability problem because interphysician communication is supposed to be facilitated by the medical record. A truly patient-centered medical record would facilitate team collaboration.
To imagine a future with interoperable healthcare data, we need only look to other tools that we already access in our day-to-day life. Just as Mint.com aggregates and displays your combined finances from many accounts, our medical record could also display aggregated data. A chronological timeline would show the ups and downs of my father's light chains over time, with markings along the way for events like hospitalizations, chemotherapy changes, or other significant events such as a fracture. Hovering over and clicking links would allow a physician to explore deeper to see the details behind any particular point in time.
A team at the University of California, San Francisco, has demonstrated this model by developing MS Bioscreen, an iPad app that pulls together treatment history, lab results, imaging results, and other crucial data in the care of patients with multiple sclerosis. Their app was developed on top of a large research database, but this approach now must progress to real-life clinical data, including data pulled from multiple locations.
Finding a Solution
EHR vendors did not invent this problem and are not solely responsible for solving it. So, what will it take?
First, all of us stakeholders need a shift in mindset away from being fearful of losing patients to other health systems. We all hate being trapped on an email listserv or subscription service that obfuscates the exit path and makes it almost impossible to unsubscribe. Great service from a health system should make you want to stay and use their services, rather than making you feel like you have to stay because your data are held by a health system.
Imagine a billboard from a health system saying, "We make it easy for you to take your data and share it elsewhere." By aligning insurance dollars with delivery systems, accountable care organizations (ACOs) are beginning to encourage this transition, though we will have to be careful that ACOs don't become just another set of silos that trap data within them.
Second, we need a shift toward thinking about the medical record as centered around the patient, not the doctor. For the most part, we have designed medical records that mimic paper charts, which by their nature are intended for local consumption rather than a contribution to a larger whole.
Third, we need cleaner data capture. We frequently use the phrase, "garbage in, garbage out." The data that we can report out are only as good as the data we put into our electronic systems. We can improve our user interfaces and workflows to encourage more capture of discrete data instead of free text. A potential alternative that could preserve more humanism and narrative in medical documentation would be a dramatic improvement in natural language processing (NLP) capability. With advanced NLP—still more dream than reality—we could input free text and let smart electronic systems interpret it and store it as discrete data.
Fourth, we need simplified medical team communication. Tools like Slack are proliferating across the business world, lowering the barriers to team communication, letting teams chat freely with each other, and storing the conversation chains in easily searchable ways. We need this for healthcare so that my dad's primary physician, oncologist, and endocrinologist can discuss together what bone medication he should take, without all of the time wasted with voicemails or returning pages. They could each add a suggestion, question, or comment to the chat window when convenient for them.
If we designed the healthcare system with a very typical patient like my dad in mind, this is what we would have.
Medscape Diabetes © 2016 WebMD, LLC
Any views expressed above are the author's own and do not necessarily reflect the views of WebMD or Medscape.
Cite this: The Case for a Patient-Centered EHR: My Dad - Medscape - Jan 20, 2016.