AI Solutions for Healthcare

Managing Healthcare Costs Through Digitization

– Musheer Ahmed, CEO, CTO & Founder of Codoxo

As healthcare costs continue to rise, health plans face increasing pressure to control systemic fraud, waste and abuse in order to provide affordable patient care. Codoxo CEO, CTO and Founder Dr. Musheer Ahmed shares his thoughts on the positive impacts that digitization can have on the efforts to control healthcare costs.

America spends more money on healthcare than any other nation in the world today. According to the Centers for Medicare & Medicaid Service, (CMS) the cost of healthcare in 2018 was $3.6 trillion and rising, or more than $11,000 for every person in the United States.  Despite the trillions spent, health plans struggle to keep premiums and cost of care down while still providing quality patient care, because a significant portion is lost to fraud, waste, and abuse in the healthcare system.

According to the National Health Care Anti-Fraud Association (NHCAA) fraud, waste and abuse accounts for as much as 10%, or $360 billion of our healthcare spend. And since it is calculated as a percentage of healthcare expenditures, these costs are projected to go up significantly over the next few years as healthcare spending rises.

What is healthcare fraud, waste and abuse?
Fraud, waste and abuse takes many forms in our healthcare system. It can include intentional misdiagnosis, bill padding, upcoding, unbundling, performing unnecessary services, wasteful expenditures, or even simple human error. Today, there’s a rise in COVID-related scams fueled by changing treatment protocols and loosening of regulations to expand the use of telehealth.

Although fraud can come from any corner of the healthcare ecosystem, incidents stemming from providers typically have the largest financial impact. For example, last year a fraud ring in Florida used stolen patient information to file $42 million in medical claims from phantom clinics. Another egregious example involved a scheme to intentionally misdiagnose patients with cancer, so providers could prescribe chemotherapy and charge the insurance company for the treatment. And of course, the U.S. Department of Justice recently executed a $6 billion healthcare fraud takedown, which included 100 medical professionals.

Identifying fraud in healthcare payments is challenging
Healthcare payments are incredibly complex. Our intricate, highly-regulated, and fragmented healthcare system includes a staggering number of touchpoints and variables that impact payments. Decisions sometimes need to be made in short order without having access to all data points that could influence the payment.

Non-standardized contracts, where payments can vary by provider, make it hard to identify anomalies in cost data that would help uncover fraud. Ultimately, the industry is challenged with legacy technology systems, inaccessible data, and a resistance to adopting new technology.

Health plans have mostly relied on traditional techniques such as rule-based systems and human expertise to combat FWA. Some plans and service providers have started exploring the use of supervised machine learning in this space. However, such techniques focus on known and predicted schemes and aren’t able to keep up with the emerging FWA schemes in a timely manner.

This causes health plans to lose money to these schemes until they can be established and identified. These methods also tend to produce a high number of false positives that drain a health plans’ limited resources to chase down non-existent schemes. And the impact of a false positive is magnified in healthcare where it could lead to costly court cases.

An AI-based platform defies the traditional rules-based logic by being completely agnostic to the data and any preconceived known or suspected FWA schemes. The AI can identify trends and patterns not known to exist and surface these to a health plan in a proactive manner, rather than surfacing the issue months or even years later.

Digitization can help health plans get back to providing affordable care
Health plans can overcome many of these obstacles to digitization by partnering with third-party platforms like Codoxo. Using artificial intelligence and machine learning, combined with predictive analytics, these platforms analyze significantly larger volumes of data, including medical, pharmacy and lab claims, provider history, member history, and other types of data, in real time to augment rule-based techniques.  In a rapid and efficient manner, the AI can look for combinations of patterns using various data sources that otherwise would be overlooked by a rules-based engine or human review.

With the power of AI, they can quickly detect practices that intentionally or unintentionally increase costs, and build connections across the data to provide actionable insights.  With automated workflows, they can help health plans identify providers, facilities, pharmacies and members that are engaged in fraud schemes, even detecting emerging schemes earlier in the cycle. Identifying these cases before claims are paid enables health systems to investigate and address fraud before it impacts their bottom line.

Taking it one step further, these platforms can integrate results into health plans’ existing internal analytics to prioritize cases that will yield the highest savings. They can even help users expedite the investigation process by automating data analysis tasks around location analysis, relationships, and code utilization. There are also opportunities to bring AI into case workflow management, to help health plans manage numerous cases that may be open at the same time and efficiently bring them to resolution quickly.

Typically this AI technology can be rapidly implemented and deployed, unlike traditionally available platforms on the market today. Some health plans have been able to identify millions of dollars in suspicious claims activity in a matter of weeks. However, that success is dependent on how quickly health plans provide access to their claims data, as well as the completeness and accuracy of the data provided. AI platforms can assist by providing mechanisms to clean data, and coach health plans on best data practices, so users can maximize the value they get from digitization.

As healthcare costs continue to rise, health plans need to take a more proactive approach to identifying fraud, waste and abuse in the system. Health plans that adopt innovations like digitization and AI are detecting fraud much earlier in the payment process, before overpayments are made. As a result, they are able to manage costs to stay competitive, optimize their networks and provide affordable quality care.

Ahmed recently joined other healthcare experts to discuss consumerization and digitization in the healthcare payments industry. You can watch the video conference on demand.

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