The Impact of AI on Workers’ Compensation Claims

Navigating workers' compensation claims is often challenging due to several factors. The industry is prone to fraud, impacted by escalating medical costs and challenged by the long-term nature of claims, which complicates financial planning and liability estimation. Additionally, the sector operates under stringent regulations that vary widely between regions, adding another layer of complexity. However, the adoption of AI in insurance is transforming the workers’ comp landscape, offering promising solutions to longstanding issues. 

Reducing Workers’ Compensation Costs with AI

Rising medical costs and increasingly costly litigation continue to challenge workers’ compensation carriers. Fortunately for carriers, AI can help reduce workers’ comp claims costs in several ways:

• Rapidly review claims. AI’s ability to rapidly process and summarize medical records, surfacing critical information so that no detail goes unnoticed can dramatically reduce workers’ comp costs. With this advancement, claims professionals can quickly find comorbidities and identify the primary diagnosis for each claim. AI can also isolate and track conditions for a longitudinal view of how claimants are progressing. 
• Increase efficiency. Many workers’ compensation claims are simple. Yet they take up the majority of claims professionals' time. With AI, claims professionals can efficiently sift through thousands of pages of medical records, deduplicate records, and flag cases which require further review. 
• Quickly intervene on catastrophic claims. With AI, carriers can swiftly identify cases that have high litigation potential and assign them to senior claims professionals. By ensuring claims professionals are focused on complex cases that demand their expertise, rather than getting bogged down with simple claims, carriers can improve resource allocation and reduce the risk of legal action.
• Identify irregularities in procedures and treatments. AI excels at detecting anomalies like unusually expensive drugs or procedures, alerting professionals promptly. With this information, carriers can easily highlight outliers for further review. 

Using AI in Insurance to Address Talent Shortages and Burnout

The U.S. insurance industry is facing significant challenges caused by talent shortages. Projections from the U.S. The Bureau of Labor Statistics suggests the industry could lose around 400,000 workers through attrition by 2026. This issue is augmented by an aging workforce, with many experienced insurance professionals nearing retirement. 

Additionally, burnout is high among insurance professionals. In fact, a 2023 survey by business communication organization Ringover found that 82.5% of workers in the finance and insurance sector reported burnout. This is significantly above the U.S. average and can have significant consequences. Burnout can cause employees to make mistakes, lose focus and decrease efficiency, ultimately impacting a carrier’s bottom line.  

AI can reduce employees’ workload by tackling tedious and time-consuming tasks, such as summarizing medical records and fetching key case details. It can also reduce processing times and decrease the risk of human error. According to a 2023 workers’ compensation survey by Risk & Insurance, 61% of respondents reported that their organizations have benefited from newly implemented claims processing and operational efficiency initiatives, such as the adoption of AI and machine learning tools. 

Insurers can also use AI to help train, and develop new claims professionals to be proficient in their roles. AI can accurately capture what current employees are doing and create comprehensive training materials and guides to get new workers up to speed. Additionally, AI solutions like DigitalOwl's are instrumental in guiding new employees through the medical record review process by flagging critical details in medical records, helping claims professionals understand what to focus on and providing valuable educational support. This can help reduce the administrative burden of onboarding and training new employees. 

Using AI to Reduce Claims Litigation

Managing litigation for workers’ comp claims is a costly drain on resources. Furthermore, the potential consequences of losing are substantial, including high legal fees and the opportunity cost of diverted time that could otherwise be allocated to more productive endeavors. Therefore, it’s not surprising that nearly 50% of workers’ compensation stakeholders listed litigation as a primary industry concern in the Risk & Insurance survey. 

Workers' comp litigation often stems from delays in disability payments or treatment authorization. With AI, workers’ comp carriers can prioritize speed and efficiency to improve communication between medical providers and employers as well as improve claim and medical outcomes. Carriers can also use AI to quickly and efficiently identify claims that have high litigation potential (for example, by flagging pre-defined data from a bulk of cases). This information allows carriers to quickly involve senior claims professionals, reducing the likelihood of legal action. 

Navigating Complex Claims with AI

Complex claims were also listed as a major concern by 45% of respondents. Many factors can contribute to a complex claim including comorbid conditions, mental illness and other biopsychosocial factors. Cases involving complex claims often take longer to resolve, which can result in underpayment, overpayments, administrative burden and compliance issues.

With AI, P&C insurers can efficiently triage cases, automatically filtering for cases that need further review to improve resource allocation, surface critical details and provide them with the information they need to make evidence-based decisions. 

Using AI to Combat Fraud in P&C Insurance

Workers' comp insurance fraud costs $6 billion to $7 billion dollars each year, according to estimates by the Coalition Against Insurance Fraud and the National Insurance Crime Bureau. 

Addressing fraud within the workers' compensation system is a time-consuming process, leading to substantial delays for both illegitimate and legitimate claims alike. Furthermore, heightened scrutiny of all claims as a result of suspected fraud can significantly slow down the claims process or lead to improper decisions. Ultimately, these delays and uncertainties can diminish the injured worker’s satisfaction and impact their return to work.

Consider the following ways new technology is being used to identify workers’ compensation fraud:

• Digital twins are being used to create virtual replicas of workplace accidents. This allows insurers to identify claims that couldn’t have happened the way the claimant described.
• Machine learning is helping carriers sift through massive datasets to recognize patterns in claims and flag characteristics that may point toward fraud, enabling further investigation. 

Unlocking the Potential in Medical Data with AI

Medical data is crucial to make accurate, evidence-based decisions. However, carriers have historically struggled to unleash the full potential of medical data. One of the main obstacles has been that medical data is typically unstructured, meaning it comes in various data formats that are difficult for humans to succinctly analyze and comprehend. This includes APSs, EHRs, lab results, handwritten notes and much more. 

Fortunately, with the adoption of AI, carriers are finally able to efficiently structure and analyze large datasets. For example, DigitalOwl’s platform normalizes data from diverse sources such as, EHRs, APSs, handwritten notes and more, consolidating them into a single coherent source that eliminates the need for separate rules engines and streamlines decision-making processes. 

How Can AI Streamline Workers’ Compensation Claims?

With DigitalOwl’s AI platform, you can unlock prompt and thorough evaluations for efficient claims processing with a complete view of all treatment and injuries, a consolidation of available medical records and the ability to filter for pre-existing conditions. The following are just some of the benefits:

• Dramatically reduce the time it takes for manual reviews, improving resource allocation.
• Access clear insights to more easily determine severity and complexity.
• Empower accurate and change in exposure assessments. 
• Align treatment to guidelines to enhance Utilization Review.
• Enhance decision-making with a concise, comprehensive view of medical records.
• Efficiently perform return to work evaluations.
• Filter by specific body parts and isolate key injury-related conditions.
• Track changes to better understand how injuries and recovery are developing.
• Gain a comprehensive understanding of all treatments and permanency.

Conclusion

By preparing for talent shortages, improving evaluations prior to litigation, bolstering fraud detection efforts, and unlocking the potential of medical data, AI technologies are reshaping the landscape of workers’ compensation. Moreover, by unlocking the potential of medical data, AI offers unprecedented opportunities for enhancing decision-making, ultimately improving outcomes. As P&C insurers continue to embrace these innovations, there will be a significant advancement of the workers’ compensation claims strategy.

‍