Part One: Introduction
As evidenced by StrataRx, as well as our Hype and Hope white paper, expectations run high regarding data’s potential to transform healthcare: lower costs, fewer errors, and better patient outcomes. So high, indeed, as to suggest we are nearing the peak of a hype cycle, with inevitable disenchantment ahead.
Don’t get me wrong, real advances in data management and analytics have already enabled:
- Promising new lines of medical research: genomics, proteomics, metabolomics and others.
- More efficient drug development: high-throughput screening, more statistically astute clinical trial design and interpretation, the re-engineering of old, failed or off-patent pharmaceuticals.
- More powerful medical devices: capturing data and sending it to the cloud for storage and analysis, using the app revolution to enable faster, cheaper, user-friendlier devices.
- Mobile health apps: would be impossible without the platform technologies of the Internet, cloud, smart devices and the cellular infrastructure.
But, as is always true at the leading edge, enthusiasm and hustle sail over significant real-world obstacles.
In his StrataRx talk, Stephen Friend had many non-obvious insights, but I’ll only address two here:
- He likened today’s “Iron Triangle” of research, development and academia to Eisenhower’s well known warning about the “military-industrial complex”. Less well known is that in a later paragraph of the same Farewell Address, Eisenhower also warned against a similar Iron Triangle:
“The prospect of domination of the nation’s scholars by Federal employment, project allocations, and the power of money … is gravely to be regarded…. Yet, in holding scientific research and discovery in respect, as we should, we must also be alert to the equal and opposite danger that public policy could itself become the captive of a scientific-technological elite.”
I think we’ve seen more than a little of both in the past 50 years.
- More to my immediate point, Dr. Friend mentioned the “corruption of denial”: if you are not aware of a problem, you cannot address it.Thus, in the interest of drawing attention to some of the (usually unspoken) obstacles to realizing the potential of data in healthcare (so as to better enable us to change, overcome or work around them), here is my view. I’m coming from a 20+year career in life science communications (with an early exposure to bioinformatics), 10 years as officer of a small business, plus a ring-side seat (thanks to my husband) to 40 years of enterprise IT infrastructure, including healthcare.
Most of these obstacles are not technical, but systemic, organizational and cultural (I’ll write about a few technical issues in a later post).
- The next will outline some of the systemic obstacles,
- Number 3 will discuss the regulatory maze,
- Number 4 will discuss more IT-specific barriers,
- My fifth post will list some attractive opportunities, despite existing obstacles, for healthcare data.
