Healthcare funders, which are required to protect resources to ensure sufficient funds are available to meet the needs of their members, cannot afford to be too trusting as fraud and abuse are an unfortunate reality confronting the industry. It is therefore fortunate that advanced technology and an artificial intelligence engine have been developed to detect improper claiming practices.
“In our experience, the majority of South African healthcare service providers are truly dedicated to applying their expertise to improving patients’ health and preventing disease progression,” says Wilma Liebenberg, Chief Executive Officer of Knowledge Objects Healthcare (KOH).
“Medical schemes demand no less for their members, and this is why healthcare professionals and schemes work together to ensure that all members receive equitable and appropriate evidence-based care. This being said, human error sometimes arises and, as has unfortunately been seen, human frailty means that schemes need to be on high alert to prevent healthcare fraud.
“In this day and age, there is certainly no need to be practising deception or playing ‘secret agent’ games to get to the bottom of such suspicions in order to safeguard members’ funds,” she adds.
Many medical schemes experienced much higher claims in 2016, which in turn tends to drive membership contribution increases. In order to ensure that medical scheme resources are only used to fund legitimate claims, inappropriate claims must be identified proactively and managed quickly and effectively.
“We recognise that healthcare service providers are not coding specialists. It is therefore not surprising that they might make mistakes from time to time. Regrettably, yet understandably in light of fraud blighting the industry, some medical schemes tend to treat these providers with quasi-criminal suspicion until they are proven innocent without affording healthcare professionals an opportunity to rectify the mistake. Rather, the healthcare funding industry often relies on a small subset of rejection messages on statements that have no definitive meaning.”
KOH’s approach relies on providing the maximum amount of information in order to ensure claims submitted are accurate and factual. Advanced artificial intelligence software known as Health-Power™, which pre-emptively flags inappropriate claims, is used to detect risk patterns while assisting in identifying suspicious activity.
“Our technological solutions mean that incorrect prescription submissions, bundling or unbundling of treatment codes, ‘code farming’ and over-servicing are detected using an embedded rules engine for real-time protocol application to prevent incorrect payments being made,” Liebenberg explains.
Claims auditing identifies potential coding and billing issues, including outpatient coding errors for example, to distinguish inappropriate or potentially fraudulent claims. “Essentially, the system detects and prevents fraudulent or ‘phantom’ claims through communication with members on all transactional line-level records. In addition, claims are adjudicated against comprehensive best practice clinical, fraud and coding rules, which are backed by experts from all medical disciplines,” she notes.
“This means there is no need for spy cameras or private investigators, which we have recently heard allegations of, and no duplication of administrative processes. All rejection messages are a reflection of the actual protocols and clinical rules triggered per line transaction.”
“Complementary insurance products, such as gap cover and hospital cash back daily plans, have also been subjected to increasingly sophisticated abuse, including leveraging medical scheme claims in an attempt to piggyback fraudulent claims for these types of insurance. As Knowledge Objects Healthcare (KOH) provides technology solutions across these product classes, it is able to cross reference rule firings for further algorithm enhancements.”
Liebenberg explains that KOH’s approach is an important deviation from the industry norm, where data trawling and auditing of outliers is traditionally performed retrospectively and in many instances even manually. “In contrast the focus of KOH is proactive management, with 90% of our analysis being conducted at this level. In addition, we make use of retrospective algorithmic rules to continuously analyse big data and detect trends.
“These complementary systems further enhance the real-time rules engine, and engagement with healthcare service providers and members enhances the medical care provided. The purpose is not only to deter or detect mistakes or fraud, but more importantly to confirm quality care is being provided to further support the health of patients.”
Sechaba Medical Solutions, Administrator and Managed Care organisation for Sizwe Medical Fund, implemented KOH technology less than a year ago and has experienced an initial reduction in inappropriate claims of around 6%. “In our experience, this generally settles down for schemes making use of the fully integrated NEO™ administration and managed care system, as claiming healthcare service providers acclimatise to the rigorous real-time checks and balances and the “halo effect” kicks in,” Liebenberg observes.
“When we consider that the private healthcare industry funded in excess of R100 billion in claims in 2016, a potential 6-8% saving on fraud and abuse is therefore considerable. Fortunately, the solution is not costly human capital-intensive lengthy investigations, but virtually instantaneous technological claims review and industry-leading decision-making software. This powerful and proactive risk management system assists in containing annual increases on medical schemes’ annual membership contributions.
“When it comes to managing fraud and abuse risk for health-related expenses, there are elegant and technologically-advanced solutions available. Where patient outcomes and risk management are concerned, spy cameras and private investigators trying to trip up doctors have little to offer in comparison with our sophisticated software solutions,” Liebenberg concludes.