As Senior Director of Coordination of Benefits, Ron is responsible for directing Discovery's Coordination of Benefits (COB) organization while driving growth, new solutions, and process improvements to deliver best-in-class results for our clients. Ron has over 20 years of experience in claims payment, data mining, coordination of benefits, payment optimization/accuracy solutions, and analytics throughout the entire claim payment continuum.
As many as 15% of your health plan members have other insurance coverage, creating a multi-million dollar impact on your health plan’s time, resources, and, ultimately, bottom line. In instances of overlapping coverage, health plans shoulder the burden of accurate claim payments. The arduous process of identifying other insurance, validating coverage status, and recovering incorrectly paid claims all generate substantial administrative costs and greatly affect provider and member relationships.
There are several trends that contribute to the issue of incorrectly coordinated claims. First are continual changes in membership. Take, for example, the nation’s aging population. Increasing numbers of baby boomers are reaching age 65 and becoming eligible for Medicare. At the same time, the percentage of retirement-age Americans who continue to work has doubled since 1985, surpassing the 20% mark in February 2019. Many of these older workers are covered by both their employers’ plans and by Medicare. In addition, health plans’ current claims processing environments entail highly manual, error-prone methods for verifying eligibility and insurance information. As many as a third of claims are paid incorrectly each year, contributing to approximately $1 trillion in annual waste.
These trends create a need for a new, modern approach to coordination of benefits (COB). In today’s competitive marketplace, the old tried and true approach to coordination of benefits—sending lots of member surveys (that cause member abrasion) and doing routine data mining (which produces lots of false positives)—isn’t enough anymore.
Bringing COB into the 21st century, Discovery blends the right people, processes, and technology to allow our team and our clients to work smarter rather than harder, effectively integrates data sources, looks at member eligibility holistically, and determines the most successful indicators or combination of indicators of other coverage.
A.I., meet H.I.
Our “modern” approach to COB does not mean that we’ve completely automated the process. To the contrary, Discovery believes that machines (A.I.) are only part of the coordination of benefits equation. It is the human intelligence (H.I.) component of our coordination of benefits solution that makes it very effective—and really special. A.I., meet H.I.
Sure, Discovery has built custom technology that is really awesome and supports intelligent coordination of benefits workflow and accurate findings. But it is the human factor that is Discovery’s secret sauce—the irreplaceable factor that brings things like critical thinking and an awareness of member sensitivity to the equation. It is this nexus of cutting-edge technology and amazing people that modernizes our approach to COB.
The human component of our Coordination of Benefits solution is comprised of subject matter experts with extensive experience working directly for both payers and providers. This combination creates a unique perspective in not only how to identify COB value for health plans, but also how to implement and operationalize a process that will be the least intrusive for the provider community. Everyone, including our COB leadership, has actually been in the payment integrity space on the front lines (as analysts) at one time or another. We know what it takes to bring maximum value.
Intelligent platform + data sources + matching capabilities
We pair our COB human intelligence with an intelligent, custom-built platform that supports the entire COB lifecycle. Going way beyond routine data matching, our process includes intelligent matching, workflow management, and machine learning algorithms.
Discovery uses many data sources in our algorithms. There are thousands of data sources available—some of which present a high return, while others provide minimal value. Based on our experience, Discovery focuses on the more intelligent sources that historically have a high yield. Our program consists of both traditional data and nontraditional data sources, and we’re continually evaluating new sources with high potential.
Discovery uses several matching processes to ensure the most comprehensive and accurate results possible. We supplement the demographic matching points (e.g., member name, member date of birth) by identifying and updating missing or incorrect information that is preventing a correct match. For example, our process seeks to verify inconsistent address information (“123 South West Main Street” vs. “One Two Three SW Main St.”), name normalization, and partial matches when most but not all key elements match. Additionally, we review case explosion opportunities such as when a member lives in the same household as dependent-aged children.
A modern, intelligent blend for coordination of benefits success
Discovery blends our rock-star COB human intelligence with advanced technology capabilities to deliver great results for our clients. It’s a modern COB solution that we’re proud to bring to health plans across the country now and into the future.
Ron JonesWANTED: new answer to growing COB problem
When health plans think of Coordination of Benefits (COB), the hassles of managing spreadsheets, letters, and phone calls come to mind. These painstaking manual and error-prone methods for identifying other insurance, validating coverage status, and recovering incorrectly paid claims can negatively affect your internal efficiencies, your provider and member relationships, and ultimately, your bottom line.
According to new research, waste accounts for about 25% of U.S. healthcare spending or $760 billion to $935 billion per year –with administrative complexity cited as the greatest source of waste.1 In addition, as many as 15% of all health plan members may hold other insurance coverage.2 Compounding these challenges are continual changes in membership, such as an aging workforce that is eligible for both employer plans and Medicare, and outdated claims processing environments that are ill-equipped to support growing and siloed data.
The convergence of these trends calls for a modern approach to managing your COB program. In today’s competitive marketplace, plans must have the right people, processes, and technology in place to effectively integrate data sources, look at member eligibility holistically, and determine the most successful indicators or combination of indicators of other coverage.
Here are three ways you can improve your COB program and cut down time, money, and paper:
#1: Increase recoveries with technology
There is great manual effort in traditional approaches to COB. Typical COB efforts involve tedious, time-consuming research and member questionnaires and calls—all of which are often ineffective and create member dissatisfaction. New technologies, such as machine learning, predictive analytics, and rules-based analytics, help identify members who have other forms of insurance and other factors that might mitigate inaccurate payments.
#2: Improve cost avoidance
One of the most important keys to success in the modern approach to COB is avoiding inaccurate payments in the first place. Proactive approaches to COB leverage sophisticated data integration, data mining, and data analytics. With technologies that quickly and accurately identify claims that are not the plan’s responsibility, a health plan can resolve claims before paying a dime.
#3: Focus on member and provider satisfaction
Traditional approaches to COB put members and providers in the middle, causing abrasion and dissatisfaction. The modern approach to COB requires that plans and their vendors look to new ways to get the information they need while communicating with providers and members on their terms. This may include using a combination of traditional communication channels, as well as member portals and automation to exchange information in more productive, cost-effective ways.
Core elements of a successful COB program begin with data sources, driven by sophisticated machine learning algorithms to create leads, and matching capabilities which all stand on the foundation of human talent. Without the right team, the technology does not yield the same results.
Discovery’s COB program encompasses all these components and offers both cost avoidance and post-payment, delivering considerable incremental recovery opportunities with minimal disruption to operations. Our COB program uses machine learning-based data mining and modeling to:
Identify additional instances of other insurance coverage
Validate coverage status
Recover any claims paid in error without any disruption to existing claims adjudication processes or existing internal COB validation and recovery efforts
1 JAMA, “Waste in the US Health Care System: Estimated Costs and potential for Savings,” October 7, 2019
2 Discovery Health Partners’ experience.
Ron JonesThree ways to modernize your COB approach
Primacy and eligibility errors can lead to serious losses and expenses. By some estimates, a third of paid health claims contain errors, and as many as 15% of members have other insurance—representing a staggering $1 trillion in annual waste1. Paying for claims due to incomplete or inaccurate member eligibility not only costs your plan millions in higher payouts and administrative costs, these errors can also generate substantial downstream administrative costs and greatly impact your provider and member relationships.
While Coordination of Benefits (COB) is a common occurrence (the process of determining which plan pays for what portions of a claim), the challenges associated with addressing other insurance retrospectively lead to increased administrative costs and payouts. Plans must go beyond the traditional process of post-payment recovery to an expansion of prospective processes that identify potential primacy conflicts while still in the pre-payment stage.
Things to ask as you evaluate your COB processes:
How can we identify more instances of other coverage and maximize our savings from cost avoidance and recovery of overpaid claims?
Do we have the data mining technology and expertise to identify Medicare or other commercial coverage?
How do our COB processes compare to industry best practices?
How do we transition our COB program from recovery to cost avoidance?
How can we minimize member and provider abrasion while coordinating benefits?
Data mining, business intelligence, and analytics are at the core of today’s most successful payment integrity strategies, including COB. As part of our connected payment integrity approach, Discovery’s COB solution automates data integration across multiple sources, bringing it all together in a single database that allows for quick and accurate identification of claims and provider responsibility. This means frequently refreshed data with up-to-date information. In addition, predictive analytics and machine-learning technologies analyze and prioritize data, allowing us to flag and take a closer look at members with a high probability of having other coverage. Our goal is to identify and address primacy issues at the earliest possible stage—improving claims payment accuracy, building stronger relationships with providers, and reducing administrative expenses.
To learn how Discovery Health Partners has helped health plans drive cost savings and millions of dollars in recoveries, download our COB case study or visit our Coordination of Benefits solution page.
1 The Office of the Actuary in the Centers for Medicare & Medicaid Services (July 2015)
Ron JonesMaximizing your COB processes with integrated technology