Is Population Health the Silver Bullet Healthcare Needs?
When it comes to healthcare IT, there are no silver bullets.
In many ways, despite all of the marketing hype, EMRs have yet to materialize as the digital miracle we all thought they would and still hope they will. Also on the list of .45-caliber, silver-plated buzzwords is interoperability, which has yet to materialize as the end-all, be-all tool for 21st-century healthcare.
Similarly, population health has been advertised as the magic solution for healthcare’s woes. Big data will bring consumerism to healthcare, solve price-transparency issues, reduce healthcare costs, and end world hunger! Okay, maybe that’s a little hyperbolic, but it’s hard to overstate the expectations surrounding population health solutions.
Many of those expectations were included in our 2016 Population Health Framework. But a year of measurement since the document’s publication convinced KLAS that we needed to tune up our research. On Oct 24th we gathered together payer, provider, and vendor leaders from across the globe at our Cornerstone Summit to revisit and update our Population Health Framework. As I spoke with some of the summit attendees, I learned that in many ways, population health has followed a path similar to that of its buzzword predecessors.
Take, for example, interoperability, which was originally heralded as a nationwide solution by which records would flow from sea to shining sea. We’ve quickly learned that in order to achieve such a grandiose vision, we need smaller, more localized successes first. State-based HIEs and regional interoperability initiatives now hold the most promise as we move into the future.
During lunch at our Cornerstone Summit, I had the opportunity to chat with Deborah O’Dell, an MD and the VP over business intelligence for Catholic Health Initiatives (CHI). I always enjoy these events as they give me the opportunity to soak in knowledge from leaders in the field. This was one such opportunity.
I was fascinated to hear how the expansive health system of CHI has looked at population health from a large-scale perspective. While they initially wanted to drive an organization-wide plan for population health management (PHM), they learned that the complexities of each region made a more localized approach a necessity.
Granted, there are international financial institutions with interoperable and aggregated data, so localization isn’t a hard-and-fast rule. But when it comes to eating the elephant that is population health, we’d best take small bites.
It’s easy, I think, to look at other industries that lead the conversation around data integration, aggregation, and analysis and wonder why solutions from those industries don’t translate immediately into HIT. Data complexity is a huge factor.
Take the financial sector as an example. Compared to healthcare, they can readily:
- Understand what data is needed for analysis
- Make sure the incoming data is standardized
- Understand/apply the results of aggregated data
Contrast that with HIT. Recently, 60% of providers stated that the data being exchanged was either poorly formatted or contained too much unnecessary “noise.”
Additionally, payers are now incentivized to move PHM forward. Many payers now ask providers for clinical data to plug into payer-purchased PHM tools. When providers ask, “What data do you need?” the response is something like, “I don’t know. Send us what you send everyone else!” This response indicates a problem, since we’ll never be able to unpack population health until all players understand what kinds of data are valuable.
This is not to say that payers are unengaged in healthcare. If their passion in the proceedings at the Cornerstone Summit is any indication, payer groups are fully invested in solving HIT problems. Instead, payers’ vague requests are a symptom of the complex blending of clinical and claims data and the rapid convergence of provider and payer goals.
Because of these complications, comparing data analysis in HIT and other industries is like comparing apples and oranges. This is especially true when patient-entered data, social determinants of health, and behavioral-health information are added to the mix. Once all the relevant factors are included, the result is a data pool that would leave even the savviest of Wall Street analysts wide-eyed.
Thankfully, it seems that big problems attract sharp minds. The mythical silver bullet for healthcare does not exist, but instead, we have driven, intelligent, and hardworking people from all walks of HIT working together to solve problems. Perhaps we’ve been looking for a silver bullet when the real solution is finding the right people to aim the gun.