Data analytics can help physician practices’ transition to value- based care models

In a move to grapple with seemingly endless increases in healthcare spending, the U.S. healthcare industry is in the midst of undergoing a fundamental transformation in the way physicians are compensated to provide care to patients – from the current fee-for-service model to one where medical providers are paid a flat fee for servicing a defined group of patients.

This pivot in reimbursement is often discussed as far off. A survey by Numerof & Associates, a St. Louis, Mo.-based healthcare strategy consultancy, finds that most health organizations have been slow to make the shift — 54% receive less than 10% of their revenue from risk-based agreements.

However, as consumers become more sophisticated, and payors and health systems become more emboldened to wring out costs, we expect to see the shift in reimbursement models take off in the coming years. Provider groups that embrace this shift now have an opportunity to gain meaningful first-mover advantages.

Policy changes will further enhance the transition. Annual fee-for service pricing (“FFS”) increases are set by the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) and physicians treating Medicare patients will receive FFS raises of 0.5 percent this year and next. Then, from 2020 through 2024, there will be no automatic payment increases.

That’s not a recipe for growing revenues. But, instead of fearing the transition to a value-based compensation model, physician groups that have the foresight and inclination to harness analytic tools, patient data, and standardized processes will have a leg up on other practices, positioning them to win new contracts with payors and systems, and capture more patient volumes.

A key to a profitable shift away from the traditional FFS reimbursement model, is a practices’ ability to effectively price a procedure based on their understanding of the patient’s medical history and other risk factors, as well as an understanding of what it costs to perform the procedure, including consumables, implants, and the time the physician spends with the patient. Automated, or programmatic data analysis can help.

A good place to begin is an analysis of the top procedures the group performs. Using data from the practices’ electronic medical records system to answer the following questions can help providers determine a competitive price for these procedures.

As an example, an orthopedic group analyzing the pricing for a knee replacement might evaluate:

What is being spent on implants? Are there commonalities or preferences on implants across the group? If a standard implant system could be selected, the group could standardize procedures or timing, allowing it to negotiate for better prices with vendors and better price the time associated with the procedure.

What are the common complications associated with knee replacements? Are there recommendations that can be given to patients to reduce complications and hospital readmissions and improve outcomes?

What are the facility charges?

With this level of data in hand, a group can develop a series of costs for procedures and an appropriate target profit per patient before negotiating a capitated rate with a health system or insurance company.

Physician practices that are making the move to this model now by partnering with or serving a health care system or insurance provider, are significantly growing their businesses. In doing so, they exchange the potential upside of being able to charge for extra services for the ability to gain market share by treating significantly more patients.

Groups that do not have this level sophistication, understanding of their data, or how to deliver care in a cost-effective manner will be at a profound disadvantage, and will likely miss the opportunity to participate in ACOs or narrow provider networks.

All this requires significant analysis of data that the practice can draw from its electronic health records system. Some practices will be able to undertake this analysis with the leadership and guidance of a controller and a billing team, while others may need assistance from a consultant.

Currently, there are numerous data-focused healthcare information service businesses that are helping physician groups sift through their patient data, procedure outcomes, and expenses to effectively price their services.

This approach can deliver better healthcare to patients at a lower price while helping efficient practices grow significantly. By using data and analytics in this way, health-care providers and insurers have the same incentive to lower health-care costs. We’re already seeing this approach work.

Kaiser Permanente, for example, owns both its own insurance and health systems, where 95% of its 11.7 million members are covered on a capitated basis.

All manner of practices can benefit from this approach — from dermatologists, orthopedic surgeons, gastroenterologists and ophthalmologists, to name just a few.

The Harvard Business Review writes that the value-based approach can trim waste from U.S. healthcare spending while also making physicians’ practices significantly more profitable: “Better products at lower costs generate higher value, which helps organizations achieve better market positions. Strategies based on that thinking have transformed other industries. We believe that they will do the same in health care. Population-based payment will play a critical role in helping care delivery groups make that leap.”

Whether physicians’ practices like it or not, this transition is taking place. It may take the next 15 to 20 years to get there, but it’s always good to be ahead of the curve.

Patrick Krause co-leads MHT Partners’ Healthcare Services industry practice and provides advisory and transaction execution services to healthcare service companies, including a wide variety of physician groups. He can be reached at pkrause@mhtpartners.com.

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