How data and analytics will boost MACRA success

To succeed under new reimbursement programs, healthcare organizations face many challenges to finding and eclipsing peer performance benchmarks.

Peer pressure is a powerful force, and it helps explain why so many healthcare providers are deploying new technologies that help them measure themselves against their peers.

Peer group performance benchmarking is at the heart of the Medicare Access and CHIP Reauthorization Act (MACRA, a complex law rolled out in two separate tracks with several different categories of provider performance metrics.

While healthcare professionals may struggle to understand the detailed impact of this legislation, the central goal is to move healthcare to a payment model based on providing the highest quality care while considering the lowest possible cost. To do that, provider performance will be measured against national peer performance to establish goals, incentives, and payment structure.

Organizations that perform well against the quality benchmarks while controlling costs will be financially rewarded. Those who miss the mark may see their Medicare reimbursements shrink. High performance, and the financial rewards that follow, will seemingly be tied to the ability to consistently improve outcomes while reducing cost.

While the broad intent of the MACRA initiative can be interpreted as incentivizing healthcare providers – primary care doctors, specialists, nurses, physical therapists and others – to work together to improve quality and coordination of care, it also puts a great deal of pressure on those providers to immerse themselves in performance metrics. To even hope to thrive in this environment, it seems imperative that providers be able to quickly assess where they currently stand relative to others and continuously evaluate how modifying their processes impact overall performance.

It’s not an easy task, but some pioneering hospitals, health systems, and physicians’ networks have forged an early path to successful deployment of the technology to address the MACRA challenge.

The old saying that you can’t manage what you can’t measure could become a mantra for providers as they transition to value-based payment models. Initially, the majority of providers are expected to choose the Merit-Based Incentive Payment System (MIPS) track. This is the gateway to true value-based payment models, whereby providers will see their 2019 Medicare Part B reimbursement adjusted up or down based on their performance in 2017.

Penalties or bonuses will be determined by how well providers perform versus national peer benchmarks on six quality measures. But providers are able to choose these six measures themselves from a list of 271 different metrics. It goes without saying that providers will want to select the measures where they already excel to ensure the highest degree of success.

As an additional component of MIPS, providers will also have to engage in a range of practice improvement activities, such as proactive management of chronic conditions and assigning responsibility for individual patients to care teams. Here again, the ability to tap data analytics to accurately attribute patients to provider-led care teams, flag high-risk patients who need care management, and align treatment protocols for those with chronic conditions is a key step in implementing patient-centered medical home models.

But how does an organization select the appropriate measures? One option is developing an integrated quality dashboard that provides detailed insights into an organization’s performance on specific quality measures, individual provider performance, and the care gaps that need to be addressed for individual patients. Intuitively, it follows that by developing this type of scorecard, providers and quality managers can compare performance across the organization relative to targets and benchmarks to determine the current state of play.

This need to systematically track quality measures throughout the organization may be amplified for providers that are further along in their transition to value-based payment models and are pursuing the second track of MACRA’s Quality Payment Program, which is called Advanced Alternative Payment Models (AAPMs). Under this payment path, providers will earn 5 percent annual performance bonuses for up to five years starting in 2019 if they agree to accept 25 percent of all Medicare Part B payments through one of a few, specific value-based payment models. The requirement eventually increases to 75 percent of all Medicare Part B payments by 2021.

With this approach, providers will really be banking on being able to consistently hit quality thresholds. Now, these early adopters should be beyond basic clinical data integration and starting to incorporate unstructured social and behavioral health data which can add texture and nuance to providers’ understanding of the full patient experience.

Of course, before any meaningful conclusions can be drawn from data, the data itself must be usable. It is not uncommon for even small to mid-sized health networks to have dozens of different electronic medical records systems implemented across their different hospitals and outpatient centers. To analyze data in a useful way, these systems must be able to talk to one another.

Organizations must also incorporate both claims data and clinical data to provide a holistic view of each patient’s complete healthcare experience. Imagine the possibilities if we had comprehensive programs which incorporate social determinants of health, such as food insecurity and housing instability, not typically included in traditional electronic health records, but contain vital information that may influence outcomes.

Ultimately, whether motivated by a sense of competition, pressure from the top, or a pure desire to change the status quo, providers adopting a value-based approach to healthcare will only be as good as their ability to balance, manage and measure the cost and quality of care. The ability to accurately benchmark performance against nationwide norms and stratify patients across geographic and demographic groups will be critical. Orchestrating the people, processes, and technology is a complex task, but the lofty goal of improving health for a population while controlling costs makes the hard work worthwhile.

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