The "for-profit" research side of health care and the academics have always had a strained relationship. The Population Health Blog witnessed it first-hand when it recruited volunteer participants for an protocol that was sponsored by a pharmaceutical company. It was a good experience, but the company made it abundantly clear who was in charge of the data.
As "big data" research grows, will large pieces of it be likewise run by self-serving and deep-pocketed healthcare corporations?
That's the question explored in this JAMA "online first" piece by Sachin Jain et al. Huge electronic health record and insurance claims data sets involving tens of thousands of patients can provide academically (publishable) as well as commercially (profitable) insights on treatment safety and effectiveness in the real world. The JAMA authors use Indiana School of Medicine's Regenstrief Institute's collaboration with pharma giant Merck as an example of how the relationship doesn't have to be anything but collaborative.
Their 5 year agreement centers on mining a statewide information exchange involving over 11 million patients. Scientists from both companies with similar interests - such as melanoma, heart disease in persons with diabetes, medication adherence, the progression of heart failure, treatment of osteoporosis, natural language processing and vaccinations - are encouraged to jointly present ideas to a steering committee that ultimately okays and funds projects.
What are some of the lessons learned?
1. Academics prefer funding that lasts 12 to 18 months, while pharma wants an answer ASAP. The fix was to create sustainable funding "cycles."
2. Protection of individually identifiable data is a priority; Merck has "arms length" access only to de-identified data, and that's just for starters.
3. Both institutions have to agree on the release of any research findings into the public domain. Any disagreements are handled by the steering committee.
4. A separate operations committee keeps track of all the projects and their timelines.
5. Some research questions on the natural progression of chronic disease can only be answered over the course of years. One big data project beats a gold-standard randomized clinical trial.
The PHB's take:
This may be a template for population health vendors to follow.
Because they're interested in the association of multiple risk factors with multiple outcomes, the vendors likewise have a lot to gain from mining big data. The good news is that many already have contracts with health care systems and other entities that are sitting on terrabytes of clinical and claims data. Smart vendors should be asking how to move past their for-profit reputation, leverage these relationships and take big data - with their academic colleagues - to the next level.
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