The Imperative to Improve in Payment Accuracy
In the labyrinthine world of healthcare finance, few issues resonate as profoundly with health plan managers as the challenge of payment accuracy. As McKinsey's alarming statistics suggest, administrative costs within healthcare are staggering, consuming nearly a quarter of total healthcare spending. If we take the latest projections to total healthcare costs into account, waste along with projected to reach an astronomical $1.75 trillion by 2031.
Such figures underscore a relentless pressure on health plans to enhance accuracy, streamline processes, and fortify their bottom lines against unnecessary losses.
The Pillars of Payment Accuracy
Payment accuracy isn't just about reducing expenditures—it's about building a reliable healthcare system that is efficient and equitable. Here are the core objectives for necessary accuracy, in this area, which every health plan needs to address:
Payment Responsibility: Ensuring that claims are adjudicated according to who is financially responsible.
Service Accuracy: Ensuring that billing corresponds with rendered services according to plan-specific and industry-wide rules and policies.
Clinical Coding Accuracy: Maintaining precision in diagnostic and procedural data to prevent coding errors.
Compliance: Adhering strictly to the terms set out in plan-provider contracts.
Fraud and Abuse Detection: Employing robust measures to identify and prevent practices that are wasteful, in deceptive or non-deceptive intent.
Failure to enhance within these pillars doesn't just result in unnecessary claim payments and increased fraud, it can also lead to provider dissatisfaction and decreased patient trust. Decreasing provider abrasion, for instance, not only enhances cost-effectiveness but also helps maintain healthy provider relationships by streamlining the claims payment process and making best practices in service rendering and billing more transparent.
Leveraging AI in Payment Integrity
Carolyn Wukitch, COO of Lyric, notes the shift towards integrating advanced automated processes like AI in payment integrity. AI's role in healthcare is rapidly evolving from a back-office tool to a front-line necessity, improving not just cost efficiency but also the accuracy and personalization of patient care.
AI applications in payment integrity include:
Automated pre-pay claim editing: This capability reduces the need for costly post-payment corrections and supports accurate, real-time decision-making.
Fraud detection: AI can identify patterns that human auditors might miss, thus preventing losses due to fraud.
Regulatory compliance: AI tools can be updated to reflect new regulations almost instantaneously, ensuring compliance and reducing the risk of penalties.
Strategies for the Next Era of Payment Integrity
To navigate the complex terrain of healthcare payment systems effectively, health plans must adopt comprehensive and nuanced strategies that leverage technological advances while ensuring regulatory compliance and maintaining essential human oversight.
Centralize Payment Accuracy Strategies: Fragmentation in payment accuracy efforts often leads to inefficiencies and inaccuracies. By centralizing these efforts, health plans can ensure a unified approach to managing pre-pay editing, post-pay auditing, and coordination of benefits. This centralization allows for seamless communication across departments, reducing redundancies and ensuring that all parts of the payment process are aligned with the overall strategic goals of the organization.
Embrace AI and Machine Learning: The application of AI and machine learning in payment integrity is transforming the landscape. These technologies can process vast amounts of data quickly and with high precision, identifying patterns that may indicate errors or fraudulent activity that would be difficult for human auditors to detect. Moreover, AI can adapt to new information much faster than traditional systems, keeping up with the rapid changes in healthcare regulations and practices.
Innovate Clinical Content: As medical technology advances, the complexity of clinical content in billing increases. Health plans need to continuously innovate their claim editing processes to accommodate new treatments and technologies, such as genetic testing and specialty drugs, which often involve complex billing codes and regulations. By leveraging AI to update and refine clinical content libraries, payers can ensure that claims are reviewed against the most current and relevant medical information, thereby improving payment accuracy, and reducing the need for costly post-payment corrections.
Maintain Fundamentals: Despite the advantages offered by AI, the human element remains irreplaceable, especially in making nuanced decisions that require ethical considerations and deep domain expertise. It's crucial for health plans to maintain a balance between automated processes and human oversight. This involves regular training for staff to stay updated on the latest technologies and industry practices, as well as ensuring that AI systems are monitored and managed by knowledgeable professionals.
Adapt to New Regulations: The healthcare industry is subject to frequent regulatory changes that can significantly impact payment processes. Health plans must have flexible systems in place that can quickly adapt to new laws and guidelines to maintain compliance and avoid penalties. This agility is facilitated by AI systems that can be updated in real-time, but it also requires a proactive approach to regulatory monitoring and a strong collaboration with legal and compliance teams to ensure that all payment practices adhere to current requirements.
Conclusion: Trust as the Guiding Principle
The strategies outlined above represent a holistic approach to enhancing payment accuracy in healthcare. By focusing on innovation, centralization, and maintaining a balance between technology and human expertise, health plans can tackle the challenges of today's complex healthcare environment. This approach not only improves operational efficiency and seeks to slow down rising waste and administrative costs, but also builds a foundation of trust and reliability, which are essential for successful interactions among providers, payers, and patients.
By prioritizing these strategic elements, and driving greater levels of stakeholder transparency, the healthcare industry can move towards a more efficient, transparent, equitable, and accurate system.
About Lyric
Lyric, formerly ClaimsXten, is a leading AI healthcare technology company, committed to simplifying the business of care. Over 30 years of experience, dedicated, expert teams, and top technologies help deliver up to $14 billion of annual savings to our many loyal and valued customers—including 9 of the top 10 payers across the country. Lyric’s solutions leverage the power of machine learning, AI, and predictive analytics to empower health plan payers with pathways to increased accuracy and efficiency, while maximizing value and savings. Lyric is investing in AI driven technology to ease implementation and speed to value for customer savings, while offering enhanced and newly available solutions through internal product development and strategic partnerships, including recently announced partnerships with Concert Genetics, Autonomize AI, and now, Codoxo. Discover more at Lyric.ai.
