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Understanding the Value of Predictive Analysis in Bundled Payments

The increasing emphasis on value-based care has likewise increased the need for new reimbursement models. Bundled payments represent one example.

Bundled payments focus on lowering the costs of discrete episodes of care by paying the providers to coordinate services, Jacqueline LaPointe at RevCycleIntelligence writes. The model requires providers to take on more risk, but rewards them if costs are below the preset bundled payment amount while still meeting quality standards.

“Providers now have a greater amount of skin in the game and risk in the outcome,” says James Caillouette, M.D., surgeon in chief at the Hoag Orthopedic Institute.

The increased risk has prompted providers to seek information in order to determine whether bundled payments are appropriate for their practices and budgets. Predictive analytics offer one way for providers to gain the insight they need into bundled payment models within the context of their individual practices.

How Bundled Payments Work

A bundled payment “links multiple provider payments into one care management and payment system during a specific episode of patient care during a defined period of time,” explains Matt Guildin, senior analyst at Chilmark Research.

Bundled payments are increasingly common for medical conditions or procedures that can be grouped into a predictable event and outcome, such as joint replacement surgeries. In the past, for example, a surgeon, anesthesiologist and hospital would have been paid separately for their respective roles in a joint replacement procedure. With bundled payments, one payment is made for the entire procedure and providers are tasked with managing costs. If their costs exceed the payment amount, the providers bear the burden; if costs are lower than the payment amount, providers share the excess.

In late 2017, the Centers for Medicare and Medicaid Services (CMS) announced it would end two compulsory bundled payment programs. Instead, the agency launched a voluntary episode bundled payment model called Bundled Payments for Care Improvement Advanced (BCPI-Advanced). The model tests new versions of bundled payment for 32 different clinical events with the goal of reducing costs while maintaining or improving the quality of care, Tracey Walker at Managed Healthcare Executive writes.

Are Bundled Payments Worthwhile?

Alternative payment models continue to gain ground. According to healthcare journalist Michael D. Dalzell, 34 percent of healthcare payments in 2017 were made through alternative payment models, up 17 percent over 2016 and 50 percent from 2015.

In fact, while alternative payment models are gaining ground, bundled payments may be losing popularity. Research led by Karen E. Joynt Maddox, M.D. shows only 12 percent of US hospitals signed up for CMS’s voluntary Bundled Payments for Care Improvement (BCPI) initiative. Of these, 47 percent had dropped out within two years.

Dropout rates don’t seem to be tied to the success of bundled payments in improving quality of care while controlling costs, as studies of their effect on these two factors remain promising. For instance, one study published in the February 2017 issue of Jama Internal Medicine found that bundled payments for joint replacement saved taxpayers an average of 20.8 percent for each procedure.

“A large portion of savings came from declines in implant prices and usage of high cost postacute services—both changes that may be implemented rapidly without intensive investment in care coordination,” say researchers Amol S. Navathe, M.D., Ph.D. et al., who published the study.

Proponents argue that bundled payments improve the quality of care because they place pressure on providers to address those factors that most affect patient satisfaction and health outcomes. In a piece for JAMA, Rishi K. Wadhera, M.D. and fellow physicians argue that making bundled payments voluntary won’t be sufficient to reach value-based care goals — and it won’t improve providers’ data collection, either.

Predictive Analytics and Bundled Payments

Predictive analytics focuses on predicting future outcomes based on the analysis of data gathered from past events, tech writer John Edwards notes. It leverages tools like artificial intelligence and machine learning to spot patterns in large data sets and draw conclusions from them.

Bundled payments present a risk to healthcare providers, who face losses when care goes over budget, says Andrei Gonzales, M.D., assistant vice president at healthcare technology solutions company, Change Healthcare. Predictive analytics can help providers understand the value of accepting a particular bundled payment arrangement and manage financial risks.

Tracking Costs and Value

Being able to accurately track cost trends is essential to incorporating bundled payments into a practice’s bottom line, since not all procedure costs are completely covered. For instance, a study led by Sean P. Ryan, M.D. found that 29 percent of the 2,084 total joint arthroplasty procedures studied had costs of care that exceeded the bundled payment price.

Bundled payments make the costs of procedures contextual in a way they have not been under previous fee for service models. To determine whether the cost of a procedure exceeding the payment amount threatens a provider’s bottom line, the provider must consider factors including the amounts by which costs come in over or under the payment amount.

While these numbers can be difficult or time-consuming to analyze manually, computer analytics tools can analyze them in a matter of moments, providing not only a view of what has happened but a prediction of how a similar pattern of patients and procedures will affect payment, revenue and profit in the future.

Analyzing Multiple Data Points

Studying the costs of specific procedures and the bundled payments provided for them is just the beginning for predictive analytics, which can handle much larger data sets. Naveen Joshi, founder and CEO of software solutions provider Allerin says businesses are already using predictive analytics to study human behavior as well as quantitative data points like sales and profits.

For healthcare providers, the ability to fine-tune predictive analytics to account for factors like a patient’s age or health history provides better predictions. Providers can see not only whether a bundled payment is likely to cover a particular procedure, but can pinpoint ways to reduce costs for particular patients while still maintaining quality of care.

Making Bundled Payments Work

Predictive analytics can help providers understand the value of these payments and respond accordingly. As with any technological tool, predictive analysis works best when used as a means to achieve a goal. It can be profitably incorporated into a clear vision and plan for success.

“I would say [the] number one important [thing] with any type of alternative payment model is to have strong physician leadership,” says Monica Deadwiler, senior director of payment innovation at Cleveland Clinic. Deadwiler credits the Clinic’s success with bundled payment models to the physicians who led the implementations.

Once leadership is in place, the next step is to choose and adopt the tools necessary to collect and analyze data, explains Shane Wolverton, senior vice president of corporate development at healthcare SaaS applications provider, Quantros. “Accurately comparing the total cost and utilization of medical services against peer groups, national norms and best practices is important as the trend in bundles is to cover post-procedural spend for as long as 90 days,” he writes. Predictive analytics can leverage this data to provide forecasts for similar procedures and patients in the future.

Finally, it’s important to choose a system that makes the data accessible to stakeholders, including providers and patients. “The challenge isn’t in conducting predictive analytics themselves, but in making them accessible, accepted and relevant enough to address challenges and opportunities alike,” says James Platt, CEO of Aon Risk Solutions. When predictive analytics provides accessible insights, providers can improve quality of care while minding the financial health of their practices.

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