How AI is reshaping health care and workers’ compensation

One way health care organizations are rapidly embracing AI is by using it to assist health care providers with medical documentation. By converting patient-provider conversations into structured clinical notes, AI can reduce administrative burden and free physicians to spend more time caring for patients rather than completing paperwork.

At the same time, organizations must stay on the lookout for potential documentation errors, omissions and privacy considerations. AI tools, combined with human review, can also help with this effort.

Additionally, AI is helping clinicians make better diagnostic and treatment decisions through analysis of clinical records, laboratory results, medication histories and physiologic trends. AI uses this data to identify patterns that may signal emerging health concerns before they are apparent through traditional review methods.

While health care organizations are embracing AI across a wide range of functions, workers’ compensation may be one of the areas where its impact is most immediate and measurable.

Managing workplace injuries often requires coordinating medical care, pharmacy management, claims administration and return-to-work planning over days, weeks, months or years. And workers’ compensation claims generate substantial amounts of this data throughout the life of a case.

Historically, turning that information into meaningful action required considerable time and review. AI is changing that dynamic by helping identify opportunities for intervention earlier and more consistently.

One of the most promising applications of AI in workers’ compensation is predictive modeling. By analyzing injury characteristics, prescription utilization patterns, medical history and demographic information, machine-learning models can estimate claim costs, duration and risk levels.

These models continuously improve as they process new data, increasing their ability to identify claims that may require closer attention or intervention. The resulting insights help claims and clinical teams pinpoint high-risk cases earlier, support targeted interventions, improve outcomes for injured workers and control claim costs.

As Tron Emptage, Optum Workers’ Comp and Auto No-Fault Chief Clinical Officer, points out, “The use of AI models, such as predictive analytics, enables a more proactive approach in which claim management risks can be identified and addressed earlier in the claim lifecycle. This intervention can reduce the likelihood that an injury will escalate into a long-term, high-cost claim.”

The value of predictive analytics becomes clearer when viewed through the lens of a real-world claim.

Tracy, a 41-year-old manufacturing employee, suffered a back and hip injury while working. Following her injury, our predictive model analyzed her clinical profile, medication history, injury characteristics and demographic information.

Tracy was identified as a high-risk claimant and her case was flagged for additional review.

Despite its current and future benefits, we are careful to note the potential risks of AI. Successful implementation will continue to require thoughtful governance and ongoing oversight by technology, compliance and health care professionals

• Bias and fairness
  AI systems learn from historical data. If that data reflects existing biases, AI-generated recommendations may unintentionally reinforce disparities in treatment, claims handling or resource allocation.
  
  
• Transparency and explainability
  Some AI models can generate highly accurate predictions while providing little visibility into how those conclusions were reached. This lack of explanation can create concerns among injured persons, clinicians, regulators and payers.
  
  
• Privacy and data security
  Health care and claims information contains extremely sensitive personal data. Organizations must ensure that AI applications and systems comply with privacy requirements and maintain strong security protections.

As AI becomes increasingly integrated into health care, policymakers are working to establish guardrails that promote responsible use.

Many health care leaders believe today’s applications represent only the beginning of AI’s potential.

Wearable devices and remote monitoring technologies may enable continuous assessment of patient health, allowing clinicians to identify deterioration earlier and intervene before conditions worsen.

AI is also expected to play a growing role in combining information from multiple sources to support earlier disease detection and more personalized treatment strategies.

Beyond patient care, AI may strengthen occupational health programs by identifying injury trends, monitoring workplace exposures and supporting prevention efforts before injuries occur.

Researchers are also using AI to accelerate drug and therapy development by identifying promising treatment targets and improving research efficiency. In workers’ compensation, this could lead to highly individualized recovery plans and return-to-work strategies tailored to each worker’s unique risk profile.

AI is reshaping health care and workers’ compensation by helping us see risks sooner, uncover insights faster and make more confident decisions. But technology alone isn’t the answer. The real value emerges when we couple AI’s ability to analyze vast amounts of information with the experience, critical thinking and accountability that only people can provide.

Dr. Robert Hall, Chief Medical Officer for Optum Workers’ Comp and Auto No-Fault, sees a powerful opportunity to transform outcomes by combining AI with the knowledge and judgment of experienced professionals: “By pairing advanced technology with compassionate human expertise, we will create smarter, more effective pathways to care and recovery.”