Leveraging Healthcare Quality and Value in an Information Economy

High-value performance is hard to find in the US healthcare system. This is well-known. What is not clear is how to improve our performance. Logic suggests that measurement of current performance may provide clues to future improvement. The tie between rich measurement and optimal performance is, in fact, quite deep.  

We know from almost 200 years of classical economics that optimal performance—or, as economists call it, the “efficient frontier”—is when market-set prices balance the marginal utility of “consumers” (in healthcare terms, quality and value) with the marginal cost of “producers” (in healthcare terms, budgets of providers and payers).

One could immediately say we don’t have free-market prices in healthcare so there is little to be learned here. But the truly deep insight is that market prices are an expression of each participant’s information horizon—each participant’s optimization of resource use based on everything that participant knows.

As Friedrich Hayek pointed out in his Nobel-prize winning work, efficient economic markets are so because they are maximally efficient in incorporating information. In other words, the more information the better.

How can we get information efficiency into the purchase of healthcare? Over the last 20 or so years, our initial foray into information capture has often been through focused quality measures and related “pay-for-value” programs such as the Centers for Medicare & Medicaid Services (CMS’s) Merit-Based Incentive Payment System (MIPS) reimbursement incentives. These programs have had narrow targets that do not reflect the full spectrum of what it takes to keep us healthy today or maximize our health for tomorrow. These targeted measures are narrow not due to lack of appreciation for how a rich picture of each patient can improve care, but due to the high expense of capturing that data manually, one data field at a time. Current quality program compliance costs are difficult to measure through dollars per year because these narrow measures often require lots of manual effort by each doctor or nurse.

Today, major forces are at play on both the demand and supply sides of quality value measurement data. First, the demand for measurement is rising as healthcare expenses rise. MedPAC, which oversees CMS for Congress, recently stated it simply cannot measure quality in Medicare Advantage, the fastest growing part of Medicare. CMS and the Office of the Inspector General have cited serious concerns with care coverage in Medicare Advantage programs. Pushes for performance transparency are also seen in increased enforcement of CMS price transparency rules. Each of these policy considerations is fundamentally about measuring what we pay for and what we get in healthcare. And each of these policy initiatives is accompanied by new data needs.

On the supply side of information, widespread electronic health records and HIPAA requirements for electronic data interchange in payments are opening large stores of machine-readable data. We are in position to harvest our national investment in electronic health records. The Office of the National Coordinator for Health Information Technology (ONC) and CMS rules coming from the 21st Century Cures Act are making much of this information available in the standardized FHIR format, which enables intelligent computing about both clinical care and the related claims data.

Simultaneously, cloud computing and big data analytic tools are providing stunning tools to match the increasing needs for analysis of performance information with the newly widespread availability of that information.

So, what does that mean for quality and value measurement? It seems inevitable that healthcare performance measurement will start utilizing these modern approaches to identify not just individual features of care but overall patterns of care and move us closer to computationally seeing what works and what does not work. One can anticipate that this data will not just be used for measurement, but will be used alongside real-time cloud computing and rich FHIR APIs to drive decision-making and real-time communications with providers and patients.

We are seeing this rich data world, which has transformed the rest of our lives, sprouting in many key places in healthcare. CMS’s Center for Clinical Standards and Quality has started exploring these new possibilities with a variety of projects on digital quality measurement. The National Committee for Quality Assurance is formally exploring the paths to enable FHIR-based performance measurement with their Digital Quality Solutions pilot program. Major cloud platforms are enabling fully connected approaches to using FHIR-enabled data to communicate with patients, providers, and payers, and do so on the same platform supporting the underlying modern analytic tools that drive the APIs out to the patients, providers, and payers.

These are exciting times for the industry. As an informaticist and doctor who has been working toward this since medical school, I believe that improving care with modern data will be amazing.

Don Rucker is the chief strategy officer for 1upHealth.