Merging AI and human intelligence for big recovery results

May 27, 2020 Dan Iantorno
Merging AI and human intelligence for big recovery results

Technology plays a key role in health plans’ transition to more proactive, data-driven payment integrity results. We sat down with Dan Iantorno, Chief Information Officer at Discovery Health Partners, whose team received the FutureEdge 50 award from IDG/CIO magazine for Discovery’s work with machine learning and AI. We discussed how technology is driving a transformation in payment integrity and what Discovery is doing to help clients access new technologies to improve revenue, avoid costs, and enhance their members’ experience. 

Data and analytics are transforming many industries, including healthcare. What are the biggest challenges health plans face when implementing these new technologies? 

We know that health care costs are skyrocketing, driven by administrative complexity, fraud, and abuse. It’s estimated that as much as $935 billion, or nearly 25% of total spending, is wasted in the US healthcare system every year. As a result, providers are under intense pressure to manage costs and ensure payment integrity, while at the same time continuing to provide quality care for their members.

Technologies that leverage artificial intelligence, machine learning, and analytics can enable plans to implement process efficiencies and dramatically increase recovery rates, while reducing member abrasion. But many health plans lack the internal tools and resources to identify and pursue recovery opportunities for high-cost, complex claims. Discovery is partnering with health payers to support data-driven payment integrity solutions and help them identify and pursue the highest-value cases to drive bottom-line results.

What are some of the ways Discovery is innovating to help clients transform their payment integrity approaches?

Since the company’s inception, Discovery has been at the leading edge of analytics-powered technology solutions to help clients address payment integrity challenges. Today, we are using machine learning and predictive analytics to tap into the potential of more than a decade of case outcome data to improve results, drive efficiency, and guide our customers to more proactive payment integrity strategies. Last year, we unveiled our Case Open Logic solution, an initiative that uses machine learning as part of our claims ranking process in our Subrogation practice. 

Rather than relying on human logic to prioritize the 2% of cases that result in 90% of recoveries, our solution uses machine learning to augment human intelligence by selecting the cases with the highest likelihood of success, doing in seconds what would previously have taken hours of manual work. These enhancements help validate subrogation claims faster and more accurately and identify cases that otherwise might be missed. The process also helps health plans reduce member friction because there’s no need to contact members unnecessarily on claims that are not of substance. This solution has delivered immediate results for our clients, and the technology shows great potential to enhance solutions across business lines. We’re very proud that our Case Open Logic solution was honored with IDG/CIO’s FutureEdge 50 award that recognizes cutting-edge applications of emerging technologies to advance business goals. 

What’s in store for the future of payment integrity and how will Discovery support health plans as they evolve their payment integrity strategies?

Discovery’s data science team has a history of blazing new trails in the payment integrity industry. In 2020 and beyond, we will continue to innovate with solutions that drive results for our health plan clients and provide best-in-class models for the industry. For example, our investment in machine learning with our Case Open Logic solution has already helped us boost subrogation recoveries for our customers by 20%. Based on that overwhelming success, we intend to roll out similar machine learning capabilities to other lines of business such as Data Mining, Clinical Audits, and Coordination of Benefits (COB). The application of machine learning based on a decade of data enables Discovery to provide services that are immensely valuable to our health plan clients. Combining technology innovation with our team’s decades of experience in the health payer space is how we will continue to deliver game-changing profound client value.

Find out how Discovery Health Partners can help strengthen your payment integrity initiatives in 2020. Contact us today!

Dan IantornoMerging AI and human intelligence for big recovery results
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Insights and observations on the digital healthcare revolution

November 19, 2019 Wheeler Coleman
Insights and observations on the digital healthcare revolution

At our recent Discovery Client Council meeting, we had the pleasure of hosting Wheeler Coleman, CEO and Executive Partner of EC-United and a member of our Strategic Advisory Board. In this guest blog, Wheeler summarizes the key takeaways of his presentation on the healthcare digital revolution.

Survive or thrive

The digital revolution has been a game changer for all industries, and health payers are not immune. Startup companies are creating new business models and blending existing and emerging technologies to leap-frog and disrupt well-established companies and business protocols. There are also well-established companies in other industries that are entering the healthcare industry to the same end—to change the model and dislocate the existing players.

A few good examples of this are Amazon, Google, and Microsoft. These companies see healthcare as an industry ripe for an operational and administrative transformation that they can deliver through their powerhouse of technological capabilities and expansive digital footprint. To survive, payers must take this threat seriously. They cannot take their leadership position or their iconic name for granted. Resting on their laurels will very likely result in a slow death spiral.

Look at a company like Kodak. They were a market leader with a great brand. Did you know that they created the digital camera? But they were so happy with their position that they refused to make changes and ignored the red flags:

  • Hitting a revenue plateau
  • Competing on price / no differentiation
  • Big on data and short on analysis and actionable information
  • Neglected table stakes
  • Too much pride
  • Too deep in their comfort zone

Healthcare payers need to make sure they don’t fall victim to the same pitfalls. They are enjoying large revenues now, and too many are unwilling to reconsider their business models and leverage technology to maximize efficiency.

We’ve seen how this plays out in other industries. The following well-known companies were able to leap-frog the competition and disrupt well-established businesses by creating new models and leveraging existing and emerging technology.

Uber disrupted the taxi and limousine business models and, in many markets, expanded the demand for service by leveraging GPS, e-commerce, and mobile technology.

Netflix disrupted the cable and movie industries and recently their stock increased 20 percent due to increased subscriptions. This happened when 4G was introduced and movies could be streamed to individual homes. They quickly pivoted from shipping DVDs to digitally streaming movies. The outcome has been the end of the video rental business and a cable industry trying to play catch-up.

Airbnb disrupted the hospitality market and transformed how people approach travel accommodations worldwide by allowing people to lease their homes electronically.

These three different companies in three different industries each changed the playing field and caused disruption by using new and emerging technologies, redesigning how services were delivered, and lobbying for new rules and regulations. So, the question for us is not if, but when will this happen to healthcare payers? Those who are reluctant and slow to adopt emerging technology or work with new technology partners could soon find themselves like the Kodaks of the world.

How does this apply in healthcare?

The companies we’ve already mentioned, and so many more, have reset consumer expectations across the board. In healthcare, we must keep up with the evolving demands of the new “digital patient” by harvesting actionable information from all the data that is being generated by the internet of things. To do this, our options must be instant, seamless, and insightful:

Instant—Information is now in all our pockets and consumers demand information in real time. Historically, our industry has taken advantage of batch processing, but we need to change our processes and our information systems to allow for real-time processing.

Seamless—The relationship between payer, provider, and member needs to become real-time. Payers and providers must be able to exchange information in real time without impacting the member experience. The member does not want to know what’s happening behind the scenes.

Insightful—Consumerism and social networks are generating an unprecedented amount of data that we need to be able to harvest and transform into actions. The new generation of analytics (advanced analytics, ML, AI, robotic technology) will allow us to discover noncompliance and fraud more easily than ever before, but only if data is converted to information that triggers action by the payer, provider, or member.

The digital revolution is upon us!

To catch up and better serve consumer demands and stay ahead of competition, companies will need:

Strategic partnerships—Companies must seek non-traditional employees and partners.

Operational excellence—Companies must reduce costs and increase efficiencies.

Emerging technology—Companies must rapidly adopt and embrace new technology.

Healthcare has historically been a slow mover in this regard, but some progressive healthcare organizations have already begun differentiating themselves by providing a more customer-friendly, tech-enabled experience. Still, it’s not too late for those companies contemplating their next moves. The companies that make this a priority and quickly adapt to this inevitable change can survive and rise to the top of their sectors. But the clock is ticking, and for those organizations that continue with business as usual, time is running out.

To learn how Discovery Health Partners can help you advance into the future of payment integrity, contact us today.

Wheeler ColemanInsights and observations on the digital healthcare revolution
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5 Key roles your company needs for data analytics success

September 26, 2017 Discovery Health Partners
5 Key roles your company needs for data analytics success

What roles are necessary in your healthcare organization for successful application of your data analytics? Whatever the size, culture and maturity level of your company, there are five key functions your organization needs to develop models that can help drive solutions to real-world problems.

5 key roles necessary for creating analytics that will drive value for your organization

  1. Data Liaison
    The person in this critical role is someone who really understands your business goals—and can straddle the discussion between business and data. They participate in discussions with your business around your real-world problems and understand enough of the data to realize when a particular problem might be something that can be addressed with the data you can access. In fact, this person is so familiar with your business they might even be able to generate their own list of real-world problems you face that could be addressed with available data knowledge.
  2. Data Architect
    This key technical leadership position understands your big picture—they know what data you have, where it is, and how it fits together. They are current in their understanding of data technologies and can apply that knowledge to your organization’s plans on how it will leverage data.  They help create the blueprint for the environment(s) you need for data science and analytics.
  3. Platform Architect
    Many organizations don’t have data set up in a way that’s really conducive to analytics or big queries. In this IT role, your platform architect will work closely with the analytics team to create the infrastructure needed for effective analytics. They are the person who makes sure your organization has enough “horsepower” for the job at hand.
  4. Data Analyst
    As the extractor of data, this is the person you’re most likely to already have in your organization. The data analyst is often your go-to person for analyzing data sets and reporting results. The data analyst understands SQL, SAS statistical software, and your business goals to manipulate healthcare databases and produce analytic findings.
  5. Data Scientist
    For more advanced analytics against your data sets, the data scientist works to understand real-world problems and writes the models. They work with big data, using various technologies to develop models that convert data into actionable insights. They may also help identify new data sources and work with the data and platform architects to fuse them with other enterprise data sources. This role collaborates with the data analyst to get access to usable data and works with the data liaison to understand what the real-world problem is and build the models that ultimately help drive your value.

You don’t necessarily need five people to fulfill these functions since some of these data analytics roles can be combined. You may have an organization where your data analyst and data liaison roles are filled by the same person, or one person may serve as both data and platform architect. The key is to understand that you’re checking each of these boxes so your company is able to take a singular real-world problem and help turn it into the model that’s going to help drive value.

 

Discovery Health Partners5 Key roles your company needs for data analytics success
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