Recent increases in health care costs are not expected to reverse course for several decades. In search of a solution, Adun Akanni and TJ Ademiluyi co-founded Alaffia Health in 2020, one of the startups participating in the TechCrunch Disrupt Battlefield 200. The health technology company uses machine learning to try to identify fraud, waste and abuse in claims for healthcare.
“In founding Alaffia, we used key insights from our family’s medical billing company,” Ademilui said in an interview with TechCrunch. “We found that most of the waste in the system is the result of natural human error, a lack of transparency in claims processing, and misaligned incentives between health care providers and payers.” We founded Alaffia to address these issues by leveraging nascent machine learning and AI, built on deep expertise in healthcare.”
Alaffia sells services primarily to health insurance payers and businesses that provide health coverage to their employees. Using AI to extract and standardize data from hospital bills, including various medical billing procedure codes and dates of service, the platform aims to reduce payer costs by finding errors and overcharges in bills sent by healthcare providers.
The causes of medical billing errors are myriad, but often arise from double billing, missing payer submission deadlines, and failure to capture patient information. Non-specific diagnostic codes are another common problem leading to overcoding and undercoding cases. Upcoding is when a coder reports a service at a higher level than what patients received or never performed, while undercoding is when billing codes do not capture the full scope of work performed by a physician.
Medical costs are expected to grow an average of 5.1% from 2021 to 2030, reaching $6.8 trillion, according to the Centers for Medicare and Medicaid Services — and a significant portion of those costs stem from errors in health care claims. insurance. It is estimated that about 80% of claims in the US contain at least one medical billing error, and that every year about $300 billion is lost to provider fraud, waste, and abuse.
“This is quite a difficult technical problem due to the lack of data standardization in the healthcare system, so we rigorously trained machine learning models using training data generated by our in-house annotation team,” Ademilui said.
Alaffia reviews the facility’s accounts for errors such as “separation” – ie. using multiple codes for separate parts of a procedure – while verifying the accuracy of more complex claims such as implants and surgeries. The company says it taps registered nurses, certified coders and certified billers to cross-reference AI findings, as well as a clinical review team that examines each claim and the corresponding medical record.
When asked about competitors, Ademiluyi says he sees “legacy industry players” who manually process and review claims as Alaffia’s main competitors. But Alaffia isn’t the only startup trying to tackle the problem of medical billing errors with AI. Anomaly, which works with insurance companies and providers, offers an AI-driven platform designed to detect irregularities in medical bills. There’s also Nym, whose technology automatically converts medical charts and electronic medical records from physician consultations into verifiable billing codes.
However, Alaffia was able to gain traction in the space — and funding. Ademiluyi claims that the company’s services currently cover a total of over 300,000 health plan members. And to date, Alaffia has raised $6.6 million in venture capital from backers including Anthemis, 1984 Ventures, Aperture Ventures Capital, Tau Ventures, Twine Ventures, Plug and Play Ventures and ERA’s Remarkable Ventures Fund.
Ademiluyi says 2022 revenue is on track to more than double in a year. The short-term plan is to expand Alaffia’s commercial footprint and product offerings, he added, starting with direct-to-patient hospital bill review services. The company currently employs “just over” 20 people and expects to hire five more by the end of the year.
“Fortunately, we operate in a recession-proof industry. Regardless of pandemics, macro trends or the outlook for interest rates, people will still go to the doctor to get care,” Ademilui said. “When patients receive care, it leads to additional healthcare costs, which benefits our business as we review the generated hospital bills for errors. As we move toward a market slowdown, large businesses — both the health insurance institutions and the employers we support — are actually looking for ways to reduce their costs, which we directly support by reducing health care costs. As such, we believe the pandemic and the current economic slowdown is a net positive for the business.”