As Walter Cronkite once said, “America’s healthcare system is neither healthy, caring, nor a system.” A bit harsh? Probably. Yet, as our healthcare system continues to march toward value-based care amidst political uncertainties around it, it’s a pretty easy to see there are opportunities for improvement.

Many healthcare systems and providers have payment models that are still dependent on fee-for-service (FFS) revenues, and making the transition has not been easy. According to a survey conducted by analytics vendor Health Catalyst, only 23 percent of healthcare systems said they would meet HHS’ goal to tie 30 percent of traditional FFS Medicare payments to quality through alternative payments models such as Accountable Care Organizations (ACOs).

Many believe this shift, despite what happens with national healthcare policy, is inevitable. With the U.S. spending nearly 18 percent of its gross domestic product (GDP) on healthcare and fee-for-service being a major driver for it, it’s hard to argue that a different model isn’t needed.

As the focus continues to be on reducing volume and increasing value, data will remain at the heart of this process. While there are many forms of data that play a role in value-based care, we believe that these three are the most critical forms of data and the linchpin for success:

• Clinical Data
• Claims Data
• Demographic Data

The Two Major Players: Providers & Payers

According to healthcare leader Emad Rizk, M.D., the shift from fee-for-service to value-based care can’t be administered by providers alone. A huge player and administrator of it must be payers, he said in a recent Healthcare Informatics article, adding that payers do not yet have the systems in place to be able to pay for a bundled payment.

With providers as the keepers of the clinical data and payers as the keepers of the claims data, it only seems logical that these two entities will need to work closely together in value-based care.

Providers and Risk-Based Contracts

For providers working in environments with value-based care models where payment is dependent on outcomes and quality, claims data will offer a much more complete picture, when combined with clinical data, of a patient’s health. While claims data has a lag time, taking weeks or more to process, it can effectively be used for predictive modeling for future care and cost management. Combined with clinical data, success or failure can be better demonstrated.

System Redundancies

Redundancies within healthcare are notorious. Claims data can reveal redundant, misused and overused tests and services. Adding clinical data to the mix can help to inform care plans and create greater efficiencies within a healthcare system, with the goal to avoid waste and redundancies.

Interoperability

In the early days of health IT, the goal was to get healthcare data from paper to an electronic format. We’ve sure come a long way. Now, interoperability has replaced electronification of healthcare data as the next big step. Unfortunately, the healthcare system offers little incentive to commercial electronic medical record (EMR) vendors to be interoperable with one another. At minimum within a system, marrying a system’s clinical data with claims data can provide a more holistic picture for care, strategy and risk management.

Our Clients

At Intellimed, a healthcare data analytics company, we don’t pretend to have all the answers to success in value-based healthcare. However, in working with our clients, we see that the ones leading the way and doing it with the least amount of pain are marrying clinical, claims and demographic data to inform their value-based strategies.