The Merging Point of Provider and Payer Data

June 16, 2016 Joe Yelanich, Sales Director

Since it’s now possible to collect, process, and make sense of the foundational data precision medicine (PM) demands, it’s begun to gain traction as the key catalyst in driving better health outcomes, healthier populations, and manageable costs for healthcare delivery.

But to fully embrace PM, the healthcare community must take truly proactive measures in the collection of that data, or else the benefits of PM will never be realized. Untold numbers of patients will have to settle for an antiquated, increasingly obsolete system in which the talent of our medical professionals and their resources will be unnecessarily spread too thin. We’ll never achieve the “promise of precision medicine—delivering the right treatments, at the right time, every time to the right person” that President Obama described in January 2015.

So let’s take a quick look at what we need to do to support the president’s charter and find the point at which provider and payer data might merge.

Recognize what year it is

It’s 2016.

Data capture and storage technologies have advanced exponentially in the last decade, and because of that, PM can capitalize on an abundance of new data and data collectors that used to be far too difficult to obtain or didn’t even exist, respectively, like: 

  • Detailed family histories
  • Personal health-audit data 
  • Genomic data
  • Exogenous information (e.g., social media usage, environmental factors)
  • Consumer devices (e.g., Fitbit)

These exciting new variables will make effective healthcare analytics possible—what some are calling “the antibiotics of our time"—and dramatically enhance our caregivers’ ability to deliver precise care.

We haven’t arrived yet, though

Despite the potential for this emerging technology, participation levels aren’t quite where they need to be.

Why?

First, let’s recognize the two types of data at play here:

  1. Provider data. This is the data most readily available today—traditional, encounter-based clinical information extracted from EMRs and lab systems. Providers utilize the established real-time HL7 2.x message standard and the commercial integration engines that broker the disparate information. These clinical data spaces detail results, medications ordered, problems, allergies, and procedures. 
  1. Payer data. Information captured by health insurance companies (i.e., payers) is provided in the established X12 transaction sets. Also known as HIPAA data, this data is usually batch-oriented and rich in comprehensive content that goes far beyond the typical one-time encounter. These payer data spaces include diagnoses, dispensed medications, procedures, and the complete history of a paid, processed encounter. 

The health IT holy grail

Next, let’s recognize what the merging of provider and payer data is: nothing less than the health IT holy grail. It bridges the gap between two things: (1) what’s been captured in the provider record and (2) all relevant patient activity gathered by the insurance company. 

Seizing this prize in a free market is difficult thanks to the nature of the competitive—and all-too-often adversarial—relationship between providers and payers.

You can quickly recognize the implications of this lack of harmony in the simple story of a patient, Nancy, and her unplanned visit to the emergency department (ED).

  • Upon Nancy’s admittance, the clinician on duty, Dr. Smith, has very limited insight into Nancy’s recent history with her primary care provider. Dr. Smith has little to no information about Nancy’s healthcare—he doesn’t know about Nancy’s well-woman’s checkups, and he doesn’t know about her treatment for chronic, congenital conditions. Dr. Smith has no way of knowing that Nancy recently visited a rheumatologist and received specific medications to treat a flare-up. 
  • Nancy’s recent health history, it turns out, is stored in separate silos of databases, such as Dr. Smith’s EMR, Nancy’s rheumatologist’s EMR, and her insurance company’s claims system. It’s not consolidated and made available at the time it’s really needed, when Nancy’s actually in the ED. 
  • Smith prescribes pain medication for Nancy that he would’ve never even considered had he known about the medications recently prescribed by her rheumatologist. In an effort to improve Nancy’s health, Dr. Smith actually puts her at risk.

The future

This all-too-common story is about to come to an end.

Health information exchange, value-based care, and government incentive programs for adopting common technologies are slowly driving us toward a world with better synergy between participants. 

But today, most of the healthcare industry simply inventories and acknowledges whatever information is available at its disposal. It doesn’t make sense of it, correlate it, or tie it together. For that to happen, it’s going to take a lot of time and a lot of work. 

The success of that work hinges on the answer to one big question: How do you marry together all the available patient health information while factoring in all the additional data types that just so happen to not be captured in any provider or payer system today? 

It’s definitely a quandary. In my next post, I’ll investigate the ideas surrounding it and their broad implications, and see how we might prevent Dr. Smith from further missteps.

***

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