April 24, 2024

Weekly Business Insights 04/24/2024

AI in Healthcare Claims Processing. Hospitals Readying as Health Insurers Embrace AI. Claims Automation AI: The Ticket to Cleaner Claims and a More Efficient Revenue Cycle.

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AI in Healthcare Claims Processing: The Complete Guide

The complexity of healthcare claims processing is staggering. Firstly, the sheer volume of claims processed daily is huge, requiring a level of efficiency and accuracy that manual processing struggles to achieve. Additionally, the healthcare landscape is laden with a myriad of regulations, coding standards (such as ICD-10 and CPT),and payer-specific policies, adding layers of complexity to the process.

The healthcare industry isa prime target for fraudulent claims, whether intentional or unintentional. Fraud and abuse in claims processing can result in financial losses for both healthcare providers and payers. It not only distorts the economic landscape of the healthcare sector but also compromises the trust and integrity of the entire system. Detecting and preventing fraudulent activities is an ongoing challenge that requires robust systems and vigilant oversight.

The potential of AI in healthcare claims processing is vast, offering transformative solutions to longstanding challenges. At the heart of AI's potential in healthcare claims processing lies the ability to automate routine and time-consuming tasks. AI-driven systems can handle data entry, verification, and routine administrative processes with unparalleled speed and accuracy. This automation reduces the burden on human resources and minimizes the risk of errors that often accompany manual data handling. Machine Learning (ML), a subset of AI, empowers systems to learn from patterns and data. In the context of claims processing, ML algorithms can analyze historical claims data to identify trends, recognize anomalies, and predict potential issues. This predictive capability significantly reduces the likelihood of errors, ensuring that claims are processed accurately and in compliance with coding standards.

CPGs have varieties of digital factory software tools at their fingertips. These serve as a big-picture tool that integrates continuous optimization and fosters a connected worker culture of operational excellence. 


Hospitals Readying as Health Insurers Embrace AI

As AI enters the mix, many hospital leaders recognize the pressing need to enhance their technological capabilities to safeguard their financial stability. The inability to identify denial trends and promptly resolve issues can hinder hospitals from receiving the payments they are rightfully owed. Inaccuracies at any point in the service authorization, documentation, or denial review process can result in payment delays or financial losses. Higher denial rates from insurers also increase the likelihood of greater patient financial responsibility and a negative patient experience.

The U.S. healthcare system relies on intricate payment processes that demand timely insights into patients' medical needs for swift coverage decisions. Post-service, health insurers face the task of efficiently reviewing medical claims to ascertain payment amounts aligned with contractual agreements and patient financial obligations.

The use case for ramping up the speed and efficiency of this decision-making with artificial intelligence (AI) is strong and, for better or worse, will soon affect millions of patients. Among its strengths, AI combined with machine learning can analyze similar patient profiles to anticipate therapy hours, predict doctor visits, and estimate hospital discharge dates. This capability aids insurers in making faster approvals of claims and identifying potential signs of fraud or waste.

Hospitals and physician practices acknowledge the urgency of advancing their technology infrastructure. Leaders are prioritizing investments in revenue cycle technology, encompassing systems for insurance eligibility verification, charge capture, denial appeals processes, and payment efforts. Larger organizations are more inclined than others to invest in business process outsourcing and incorporate AI-enhanced features.


Claims Automation AI: The Ticket to Cleaner Claims and a More Efficient Revenue Cycle

The automation of administrative tasks related to claims has saved the industry as a whole an annual total of $122 billion, according to the Council for Affordable Quality Healthcare. However, further opportunities for automation could lead to additional annual savings of $16.3billion by fully automating some common processes.

Claims management has long been a concern for healthcare providers and revenue cycle teams. Denials, prior authorization requirements, and many other factors require staff to dedicate additional time and resources to resolve problems and, ultimately, secure the revenue their hospital or health system deserves. Effective, accurate, and reliable automation can play a pivotal role in empowering an organization to get to payment faster and more consistently. With the right automation solution in place, staff can steer their efforts toward the issues that require uniquely human talents. At the same time, a combination of artificial intelligence (AI), machine learning (ML), and targeted support from revenue cycle experts can address a bulk of tasks related to processing claims and handle them effectively.

A Unified Automation claims solution has the power to not only complete many of these edits without any staff supervision or input, but also to adapt and handle a broader range of edits over time. Everything from modifying fields, reading insurance cards and updating records, sending requests for information to patients, updating codes, and rebilling corrected claims.


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