Pandemic Profiteering at a time of Crisis: Using Python to Detect Fraud in COVID-19 Testing and Treatment Payments

Abstract Background During the pandemic, the Centre for Medicare and Medicaid Services (CMS) introduced waivers and rule flexibilities to address rising COVID-19 cases. This included expanding telehealth services to urban areas, along with various testing options like surveillance testing, school and workplace testing, self-tests, and more in-patient settings like nursing homes. The federal and State Government also covered for Covid-19 testing, vaccination and treatment for the uninsured population, creating opportunities for fraud and unnecessary testing, double billing, kickbacks, and deceased billing, mainly for monetary gain, by unscrupulous healthcare providers. Aim The aim of the study is to employ a mixed-method approach and data mining techniques to detect instances of healthcare fraud, waste, and abuse in COVID-19 claims reimbursement data for services provided to the uninsured population. This aims to safeguard the integrity of public health resources as well as government preparedness in the wakeup future unforeseen crisis. Methodology: The study adopted an unsupervised learning approach. Using Python programming, the study employed the use Isolation Forest to detect healthcare providers who were anomalies in the payment of covid-19 testing, treatment and vaccination by HRSA. The study also adopted an official search enquiry into Official U.S Government websites such as the FBI, USDOJ, and the HHS-OIG, for schemes relating to covid testing and treatment. Results The Isolation Forest algorithm, set at a 5% contamination level, identified 1,890 healthcare providers (7.64% of total claims) as anomalies. These providers had an average total claims amount of approximately 7.5 million. The highest anomaly claim amounted to 646 million, primarily attributed to “Claims Paid for Testing”. These results support the recommendations given to HRSA by the Office of Inspector General of the Department of Health and Human Services (HHS-OIG), emphasizing the need for identifying and addressing improper payments. Conclusion/Recommendation: Protecting public health resources requires preventing fraud in the healthcare industry. Strong education programs for healthcare workers are crucial, as are vigilant oversight and collaboration between federal and state agencies. Additionally, this study emphasizes how crucial it is to use official government resources—like the FBI, HHS-OIG, USDOJ, and the CDC—in order to efficiently detect and prevent fraudulent activities. By putting these suggestions into practice, healthcare programs such as COVID-19 testing can be made more reliable and public health resources won't be misused.