Mark Starinsky, AHFI, CFE, CHC, SE and Product Lead for Shift Technology’s Healthcare Improper Payment Detection solution states that, “One of the most pressing issues is the risk of providers manipulating care complexity to maximize reimbursements. Providers may inflate the perceived value of their services by offering unnecessary amenities or more specialized care, driving up costs and complicating patient care.” Examples include cherry-picking healthier patients or cutting corners to meet targets, leading to fragmented and inefficient care that ultimately increases healthcare costs. To combat these risks, it is essential for payers to adopt advanced fraud detection systems that examine care holistically across the entire spectrum. This includes primary care providers and supporting actors such as therapists, labs, clinicians, and specialists, ensuring that potential fraud is caught early.
The potential for fraud is further heightened as providers may twist outcome measures to present an artificially favorable picture of patient improvement, leading to overpayments for substandard care. Traditional rules-based systems are ill-equipped to handle these complexities. Instead, an AI-driven system that can mimic the instincts of top investigators is necessary to analyze patterns and behaviors across different providers, identifying potential fraud that might slip through conventional methods. Regular monitoring and system edits can help insurers stay ahead of trends, mitigating risks before they escalate and maintaining the integrity of the claims process.
Telehealth: The Double-Edged Sword
Telehealth has emerged as a critical component of healthcare delivery, particularly in the wake of the COVID-19 pandemic. It has increased access to care, improved service quality, and reduced costs. However, the rapid adoption of telehealth has exposed insurers to a range of challenges that require immediate attention.
One major concern is the impending expiration of provisional telehealth codes, which could disrupt the current system and lead to billing inaccuracies. Insurers must ensure that policy changes from the Centers for Medicare & Medicaid Services (CMS) are promptly integrated into front-end edits to prevent discrepancies and ensure accurate claims processing.
The potential for fraud in telehealth is significant, with providers exploiting loosened regulations to prescribe narcotics across state lines or bill for services not rendered. According to Jesse Montgomery, Head of Value Engineering & Customer Success US Healthcare at Shift Technology, “The lack of auditability in virtual visits, compared to in-person care, further complicates insurers' ability to ensure the accuracy and legitimacy of claims.” To address these concerns, implementing pre-pay edits that flag suspicious codes specific to telehealth services is crucial. Additionally, network detection tools can be leveraged to identify kickback schemes and impossible billing scenarios, such as providers claiming to see an unrealistic number of patients in a single day. This proactive approach helps safeguard the integrity of telehealth while maintaining its benefits for patients.
Moreover, the effectiveness of certain services, such as physical therapy, in a telehealth format remains questionable, raising concerns about the quality of care being delivered. The rise of telemarketing in telehealth has also led to the proliferation of unnecessary services, driving up costs and complicating the reimbursement process. Establishing stringent monitoring and validation processes, supported by AI-driven systems, can help payers continuously audit telehealth claims, ensuring that services rendered are both necessary and effective.
Mental health services are inherently more complex and sensitive than physical health services, governed by stringent guidelines around the sharing of Personal Health Information (PHI). This makes FWA detection particularly challenging, as the increased volume of mental health claims correlates directly with a heightened risk of fraud. To address these complexities, payers should implement AI-driven FWA detection systems that can analyze the entire care journey—from initial diagnosis to treatment by various providers, including therapists, labs, and specialists. Pre-pay edits specifically designed to flag suspicious codes related to mental health services are essential to ensure the accuracy and legitimacy of claims.
Stigma remains a significant barrier, particularly for groups like law enforcement officers who fear job loss if they seek mental health care. This stigma often leads to underreporting and the exacerbation of conditions, ultimately increasing costs for insurers. Proactive outreach and education, coupled with rigorous screening processes, can help insurers ensure that members receive high-quality care without facing additional barriers. Insurers must also conduct regular document reviews and audits to maintain the integrity of the claims process, ensuring that members receive the care they need without unnecessary delays or complications.
The varying quality of mental health providers further complicates the landscape, necessitating the use of advanced technology to monitor provider quality and flag discrepancies in care delivery. By integrating AI-driven solutions into their FWA detection processes and maintaining rigorous oversight, insurers can better manage the complexities of mental health care while safeguarding their reputations.