AP2CD™: The last healthcare acronym you will ever need
Put a freshly grilled steak between two starving dogs and it is inevitable that both canines will fight to their last breath to gain ownership of the morsel. In healthcare, that perfect T-bone steak presents itself as the comprehensive and trusted intersection of quality and administrative data. Unfortunately, we also have two dogs fighting for possession of the healthcare analytics steak; payers and providers!
As veterans of healthcare, we are keenly aware that quality cannot truly be enhanced through claims (payer) data. We are also quick to realize that clinical (provider) data is a poor indicator of cost and access. But what if we could somehow magically combine all of the provider data silos with all of the payer data silos? The All Provider and Payer Care Database™ (AP2CD™) promises to deliver the up until now elusive 360-degree view of the patient/member experience across the continuum of healthcare; fusing quality and administrative data in a single database.
The success of the AP2CD is dependent on being able to access all available data sources, penetrating the siloes they are stored within. The least effort will come by extracting quality data from clinical HIEs and retrieving administrative data from current APCDs. Effectiveness of analytics performed against these sources would have to assume that the HIE and APCD are capturing all data. Knowing this not to be true; we must be prepared to mine information directly out of provider EHR and HIS systems, as well as from claims payment systems. This becomes the “heavy lifting” effort that forms a solid data foundation.
Presuming we can tap into every available data source, our AP2CD is still flawed until such time as we can standardize data. We must be able to take textual information and transform it into structured formats. Maps must be established and maintained to accommodate all of the different local conventions used by payers and providers. In short, every single piece of data needs to be put on common ground and in contextual concept.
Next we need to determine the measures that will be applied against the AP2CD information. Naturally, we all wish to use established clinical quality indicators such as NQF, USPTF, and PCMH, to name a few. We also wish to look at claims indicators such as HEDIS, cost, and access. Then it will become necessary to venture into virgin territory; formulating queries that examine cause and effect across both the quality and administrative data. Only then can we appreciate the 360-view of the healthcare experience for any patient/member, provider, and payer.
We could cite an infinite number of examples to illustrate the efficacy of the AP2CD. For now, let us examine one illustrative scenario. Our cost for the diabetic population in one benefit plan has risen due to a spike in Emergency Department visits. Whether the visit was warranted or not will be excluded from this cursory analysis. Rather, let us ask ourselves why the visit occurred.
Was it a question of access and the patient presented due to severe symptoms and had nowhere else to go for care? Was our benefit plan design flawed and there were not enough copay disincentives to have the member wait until the next day, when they could visit their PCP? Were the additional diabetic patients that visited the ED attributable to one provider or one practice? Were these patients chronically poorly controlled in their A1c measurements? For that matter, had they been given an A1c test in the past year? Were these patients suffering additional comorbidities that contributed to the ED visit? Had the patients been counseled on preventive lifestyle changes that could have lessened the severity of symptoms; allowing them to avoid the ED altogether? For that matter, were each of these patients also diagnosed as depressive, predisposing them to be more likely to seek immediate care; but their health plan had a weak mental wellness benefit, so they were poorly managed?
The above scenario is simplistic in nature. We can all attest to the complexity of any healthcare episode. To understand this complexity requires the ability to examine quality and administrative data in a homogenous data foundation. If we return to the backyard called healthcare, and look at analytics as the sizzling steak; there are still two hungry dogs circling the T-bone. If the dogs cooperate, they can each share in the benefits of the steak. If they fight over the steak, one of them has to lose.
By implementing the AP2CD™ (The All Provider and Payer Care Database™), we assure that all of the dogs are fed. More importantly, we finally arrive at a 360-degree view of healthcare data that assures we can measure cause and effect with respect to quality enhancement and cost reduction efforts. In that scenario, no dog goes hungry!Healthcare, Intelligence