The fundamental goals of healthcare are to improve people’s lives and to prevent and treat disease. We may think of technology and artificial intelligence as tools for diagnostic and medical advancements like robotic surgery, “smart” prosthetics, or vaccine rollout. But the industry is discovering how the use of AI prevents healthcare fraud, waste and abuse (FWA), advanced data security and cybersecurity solutions prevent security breaches, and biometrics and machine learning protect patient information.
Hospital directors are grappling with national losses of $300 billion to FWA each year and the constant threat of ransomware attacks, privacy breaches and identity theft. The massive scale of pandemic-related healthcare digitization increased these risks, causing healthcare leaders to seek better solutions. Many are beginning to use artificial intelligence (AI) and advanced technologies to address these constant threats to the healthcare industry and those connected with it.
Many technology solutions developed by Mastercard® to make its payments systems operate more efficiently and securely can also provide benefits to healthcare organizations. They can be applied to solve everything from seamless security and patient registration to fraud prevention and improved, secure workflows for payments.
Cybersecurity is a growing risk for healthcare data
The COVID-19 pandemic accelerated a digital-first economy as consumers and vendors seek touchless payments, social distancing and telemedicine appointments. As a result, cybersecurity is an increasing risk for the healthcare sector, exposing patients, payers and providers to myriad ways patient data can be used against them.
Fraudsters are in business for themselves and, like any business owner, looking to optimize their revenue based on current trends. An exponential increase in digital patient profiles is a business opportunity for these unscrupulous dealers. Cybercriminals breached 642 accounts of 500 or more patient profiles in 2020. That’s a rate of more than 1.76 per day, reports HIPAA Journal, totalling 29 million breached healthcare records in the U.S. By the end of 2020, security breaches cost healthcare companies $6 trillion.
Stolen patient profiles are used for healthcare FWA and other financial crimes, but their biggest value may be when they’re sold multiple times on the dark web.
Healthcare data security breaches net fraudsters up to $1,000 per record
Research in April 2021 revealed that “the value of healthcare credentials varies on the web, depending on which source you ask. According to the Dark Web Price Index 2020, credit card details generally sell for US$12-20, whereas a Gmail account can fetch US$156. One reason may be that users often sign into many accounts using their Google login, so that opens the door to many profitable opportunities.”
A medical record is 50 times more valuable than a credit card, says Chris Bowen, ClearDATA Chief Privacy and Security Officer and Founder. Fraudsters can build an entire persona to seek or bill for medical services, obtain prescriptions and abuse or sell drugs. These crimes can be repeated numerous times without detection by many legacy and manual fraud solutions.
Advanced AI provides risk analysis and security for healthcare data
Complex cybersecurity challenges in healthcare can only be addressed through integration of the many data sources and functions. Imagine if one technology solution could provide a risk analysis at every touchpoint, bundle disparate solutions across an organization and ensure a frictionless end-to-end user experience.
Mastercard’s next-level Connected Intelligence does exactly this. Mastercard’s holistic, integrated network bundles proprietary and acquired solutions to deliver security across the ecosystem. The overarching benefit is the inherent risk analysis provided through bridging the gap between technology solutions.
Armed with advanced tools like predictive data analytics, artificial intelligence, state‑of‑the‑art cybersecurity threat detection, digital identity tools and flexible billing solutions, Mastercard helps payers and providers improve business results by tackling critical challenges.
Mastercard is improving the patient and member experience by helping payers and providers improve outcomes, improve the digital experience, and simplify and enhance the billing and payment process. Valuable healthcare data is protected by the same cybersecurity and digital identity solutions used to protect billions of credit card transactions. With proven technology and deep industry experience, Mastercard helps the healthcare system become more convenient, secure and cost‑effective.
Healthcare risk analysis includes insightful onboarding
Sixty-two percent of Medicaid fraud cases were attributable to providers, according to a 2016 Government Accountability Office (GAO) report, with beneficiaries complicit in 14 percent of the cases. Recent reports show that fraudulent billing, kickbacks and medical identity theft continue to dominate this area. Healthcare payers can’t ignore proper onboarding protocols, an integral part of healthcare risk analysis.
The process provides insights to help verify provider credentials, past claims volumes, typical procedures and other business practices. Pre-screening, identify validation, history checks, compliance with National Correct Coding Initiative (NCCI) codes and payment networks, and a credit risk assessment should all be completed before granting payment accounts. These insights contribute to a baseline for future behavioral changes that may indicate financial difficulties, fraud or collusion.
In a 2020 pilot, Mastercard® Healthcare Solutions partnered with a payment integrity vendor and audited a regional health plan’s claims to determine if there were additional overpayments to be found. The AI model, built with both supervised and unsupervised learning methodologies, identified 2,700 high-risk providers and $240 million in potential savings. The model also proved its ability to identify healthcare fraud before providers were paid, offering opportunities for intervention before fraudulent claims are paid.
Healthcare FWA costs escalate annually
Erroneous billings and FWA cost the healthcare industry over $300 billion annually. That’s about 10 percent of all money paid out for healthcare services. It’s easy to imagine that in the overwhelming emergency of a global pandemic, staff will make billing errors. Another likely scenario payers will face is increased claims for fraudulent telemedicine appointments, up charges and bogus treatments by unscrupulous practitioners.
As healthcare fraud becomes increasingly complex, many schemes can’t be detected by payers’ current payment integrity solutions. Human experts may take weeks or even months to sift through volumes of claims data. Rules-based solutions fall out of date and require major modifications to include new fraud trends, additional illnesses and modalities, and recently added NCCI codes.
In contrast, Mastercard AI for FWA detection and prevention uses the same advanced fraud prevention technologies it uses for the financial services industry. Mastercard helps payers detect erroneous or fraudulent healthcare claims before reimbursing providers.
By creating models that continuously adapt and update claims data, the solution improves results by recognizing patterns of complex fraud. Each transaction enables real-time decision making while contributing to accurate predictions for future events.
The advanced AI model evolves at scale with its data, increasing detection rates and decreasing operational costs and false positives.
AI improves efficiencies across organizations
In the payments realm, Mastercard® Healthcare Solutions optimizes the workflow for payers and providers by automating repetitive and error-prone operations, such as billing and claims processing. According to CIO magazine, many hospitals are now using AI to automate mundane tasks, reduce workloads, eliminate errors and speed up the revenue cycle.
The author notes AI’s effectiveness for reducing incorrect payments for erroneous billings, and for preventing the labor-intensive process of pulling files, resubmitting to payers and eventual payment negotiations.
Cost savings, accuracy and scalability: the case for AI in healthcare
The successful use of AI for FWA prevention is increasing in popularity. A recent study by PMYNTS revealed that approximately 12 percent of the 100 sector executives surveyed use AI in healthcare payments, three times the number using AI in 2019. Nearly three-quarters of the 100 execs plan to implement AI by 2023.
Almost every respondent (97 percent) told PYMNTS their most important expectation of AI is the ability to adapt to changing behaviors, followed by a high degree of accuracy (95 percent) and ability to scale (93 percent).
These are all important factors when building an AI model and show the need to demonstrate return on investment (ROI) through a proof of concept.
AI Express, Mastercard’s proprietary process, builds custom AI models in just 6-8 weeks. Working with each customer’s subject matter experts, the AI Express team develops a deep understanding of the organization’s business challenge, helps with data collection and enrichment, then collaborates on desired outcomes. Mastercard seamlessly combines advanced AI tools, delivering personalized decisions in milliseconds.
Once the model is fine-tuned and tested, the team provides a working proof of concept and business plan to substantiate the ROI. These important tools help healthcare leaders sell the concept internally.
Advanced technologies and AI for healthcare bridge the technology gap
While healthcare is very much a people business, it is largely supported by technology. From diagnostics and clinical trials to onboarding new providers and processing payments for services and supplies, technology touches every step of the healthcare process.
AI provides effective risk analysis and tools that protect patient information unlike any other solution. The greatest benefit of using AI in healthcare is its ability to integrate every connection point, ensuring cybersecurity and fraud protection across the entire ecosystem.
Read our Ebook Bridging the healthcare technology gap for case studies and to learn more about how Connected Intelligence integrates technologies in healthcare.