Robert Kneschke - stock.adobe.co

Solving the ACO’s Out-of-Network Utilization Problem

Technology is now driving physician referrals at one of the top Next Generation ACOs, reducing out-of-network utilization and driving better patient outcomes even during the pandemic.

Physician networks are key to the success of accountable care organizations. Leaders of these organizations, otherwise known as ACOs, lean on their networks of high-quality, cost-efficient providers to improve patient outcomes, reduce costs of care, and achieve shared savings.

But patients don’t always stay within cultivated high-performing networks, creating quality and cost problems for even the best ACOs.

“Historically, we were seeing only roughly about 42 percent of the services from our population coming in-network,” Tyler Munson, senior vice president of operations at Southwestern Health Resources, recently told RevCycleIntelligence.

Flipping that statistic around, Munson said that means a majority of patients treated by the Texas-based clinically integrated network and its ACO providers were receiving out-of-network care.

SWHR’s ACO is one of the nation’s top-performing Next Generation ACOs. Its Southwestern Health Resources Accountable Care Network saved more than $52 million in 2019, accounting for a fifth of total program savings that year and bringing its individual ACO savings to $120 million since joining the program in 2017.

Leaders at SWHR attribute ACO success to physician-driven strategies. But when they noticed that out-of-network utilization was impacting the organization’s success, and more importantly, care coordination for its patients, they had to act.

“We're arming our providers and patients with the right services to ensure better health outcomes for not just the short term but really the long term, and that is where the power of that network utilization comes in,” Munson explained.

“It's that journey of health needs and that journey of wellness that is not these snippets of episodic care. It's really the management of that patient across the continuum. That's where this really adds a lot of power for us,” the ACO leader continued.

Out-of-network utilization—sometimes referred to as patient leakage—can seriously derail an ACO’s concerted efforts to provide better care at lower costs. A recent study out of the University of Michigan found that costs were higher for ACOs that had a greater percentage of patients who saw a primary care physician outside of the organization’s network, with average total costs up more than $43 for each “leaky” patient.

Additionally, a 2018 survey showed that half of healthcare organizations are losing 10 percent of revenues because of patient leakage. Yet almost a quarter of organizations surveyed did not track one of the main culprits of out-of-network utilization—physician referrals.

“There is just a lack of awareness or a difficulty, if you will, for referring providers to keep up with who is in the network, understanding what insurance they accept, what locations they are in, and so on,” Munson explained. “It can make it difficult for the provider offices to really understand and know how to refer in-network.”

Additionally, providers in ACOs do not always understand the importance of referring patients to other in-network providers, especially when they may already have long-established relationships with certain specialists, Munson added.

“It’s challenging to influence habits of providers. So we embarked on a journey to redesign some of our interactions to support the education, the understanding of how this fits into the overall mission of the organization, and provide that easy support for those providers to engage in their referrals,” Munson stated.

Technology played a major role in redesigning the physician referral process to prevent out-of-network utilization. SWHR leveraged the technology platform HealtheReferrals from Cerner to automate “decision points” to help providers make the most appropriate referral choice. Those decision points include whether a provider is in the ACO’s network, what insurance plans they accept, what languages they speak, and even quality outcomes.

“We've taken some of that administrative headache of trying to figure out where the best place to go is and we've armed them through a technology service to get to our patients and our providers,” Munson said.

Since implementing the new referral process, SWHR has seen in-network utilization jump to over 70 percent of service.

But just as importantly, the process helped the organization and its many providers overcome some of the key challenges of the recent COVID-19 pandemic.

“If you think back to that second quarter of 2020, when it was a little bit chaotic in the healthcare delivery marketplace, it was very difficult to know which providers were open, who had modified work hours, how they were engaging in telehealth, if they were accepting new patients,” Munson explained.

With the help of the new referral process, SWHR was able to compile those data points for its network and mobilize the data to make it accessible to its providers and its patients.

“That was a critical point for us in a conceptual proof that this type of technology can be adapted to support more than just your basic referral from primary care to specialist or post-acute need. It can be used to tackle some of the most complex problems that we've seen in recent times,” Munson stated.

Enabling data-driven decision-making can help ACOs and other providers achieve one of the top goals of value-based care—getting patients the right care, at the right place, at the right time.

“Since we've kicked it off, we're running, if you extrapolate annually, about 650,000 referral transactions through that platform annually. Think about the impact of having sound data behind 650,000 decisions a year that impact point-blank patient experience and patient outcomes but also in our Next Gen contract and some of our governmental work, our fiduciary duty to CMS and taxpayers,” Munson elaborated.

Moving forward, the algorithms SWHR and its technology partners have found for getting patients the “right” care will be used to address more of healthcare’s complex problems, like social determinants of health.

“What we've been looking at is how can we activate AI and machine learning to get to that next level of detail where we can look at specific outcomes based on a patient profile,” Munson said. “So we may look at the specific conditions that a patient has paired with other contributing factors, whether those are social determinants of health or other comorbidity conditions, and leveraging that insight to know very specifically which provider is going to achieve the best outcomes for that specific patient beyond the need that they're being referred for, but the other needs that they have.”

“That is where we see this enabling us to go to, which is just a much higher level of ensuring that we're getting the right patient to the right place at the right time,” Munson concluded.

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