For 20 years, I’ve been writing about clinical data management, analytics and what has now come to be known as Big Data. Like everyone else who follows this sector, I’ve been exposed to many examples of brilliant thinking about leveraging health data, and of late, a growing number of examples where data analytics has improved care and saved lives.
I’ve also reported on dozens of notable case studies in which combing EMRs for telltale signs of disease has resulted in finding dangerous or even life-threatening conditions, including heart disease, diabetes and to a more limited degree cancer. What’s even more remarkable is that we’re likely to see the list of conditions detectable by data analytics expand greatly, particularly if we make smart use of the growing flood of mobile health data.
The problem is, we’re still extremely far from achieving universal health data interoperability, and no amount of inspiring speeches by HIT thought leaders or Congressional bellyachers will achieve this goal on their own. We need a shift comparable to cultural transformation that fueled the astonishing progress of our space efforts. (Maybe someone should claim that the Russians are ahead of us in the interoperability race — we can’t let them Russkys achieve national health data interoperability before we do, durn it!)
And none of this will help me get the last few years of my life back.
You see, while the diagnosis hasn’t been all-out finalized, it appears that I have a case of early-onset Parkinson’s Disease. I won’t bore any clinicians with a detailed description of the illness, but suffice it to say that it’s neurological in origin, potentially disabling and at present, uncurable and unstoppable. I can probably still live a good life, particularly if I respond well to standard drugs, but all told, this thing is a major buzz kill.
I’ve had signs and symptoms that fit the diagnosis for at least a couple of years, and I dutifully reported them to the caregivers I saw. That included several encounters with doctors associated with the large, high-quality health system which serves the region where I live. The health system providers entered the symptoms into their jet-fueled Epic EMR, but it seems that despite that, they never put two and two together. (And as is still the norm, the data gathered at PCP visits has been in no way connected to the data living in the hospital Epic system.)
Fortunately, picking up on the earlier signs of Parkinson’s — if that is indeed my condition — wouldn’t have done anything to slow the progression of the illness. (If I had a malignant cancer, of course, this would be a different story.) But heaven knows I would have had the clarity I needed to make good self-care choices.
For example, I could have seen physical therapists to help with growing muscle weakness, occupational therapists to help me adjust my work style, joined patient groups to gather support and volunteered for clinical trials. (I live in the DC metro, not too far from NIH, so that may well have been an option.) And most importantly, as I see it, I wouldn’t have had to live with the vague but growing dread that something was Just Not Right for years.
Because I’m not a clinician, I’ll never know how likely it is that I could have been diagnosed earlier if all my caregivers had all of my health data. But I’m confident that interoperability and the accumulation of population data will help with earlier diagnosis and treatment of many unpleasant, disabling or even fatal conditions.
So when you go about the business of improving data analytics tools and interoperability, mining population health databases for trends and leveraging mHealth to improve chronic disease management, I invite you to think of me — not a tragic figure by any means, but someone who’s counting on you to keep connecting the dots. Never doubt that the human value of what you do is extraordinary, but never forget that real people are waiting in the wings for you to supply insights that can give them their life back.