Game Theory and Worker’s Comp: Understanding Stakeholder Frictional Maps

In the complicated and highly regulated world of workers’ compensation, predicting the trajectory and resolution of a claim can be an intricate challenge.

The interactions among injured workers, employers, insurance adjusters and treating physicians significantly influence how quickly a claim is resolved and how contentious the process might become—the value of the claim is always subject to change. Each of these stakeholders brings their own motivations, risk profile and influences to the table, creating a dynamic environment where outcomes can be unpredictable.

However, by applying game theory, we can develop a more scientific approach to forecasting these interactions, thereby better understanding the potential friction points and using that knowledge to reduce settlement timelines.

The Prisoner’s Dilemma

Understanding the basics of game theory starts with the “Prisoner’s Dilemma,” a classic scenario illustrating how individuals make decisions based on their self-interest, even when cooperation might lead to a better outcome.

In this situation, two prisoners are separately offered a deal: If one betrays the other while the other remains silent, the betrayer goes free, and the silent one receives a harsh sentence. If both betray, they both get moderate sentences, but if both remain silent, they receive the lightest sentences. The dilemma shows how rational individuals might not cooperate, even when it seems to be in their best interest, highlighting the complexity of strategic decision-making at the most basic level.

Stakeholders and Motivations

The four principal entry level stakeholders in workers’ comp—injured workers, employers, insurance adjusters and treating physicians—each have distinct motivations that drive their actions:

These motivations, influenced by external factors such as the severity of the injury, cost of treatment and access to medical provider networks (MPNs), lead to a variety of potential actions by each stakeholder, which in turn affect the claim’s “game” progression.

An Uneven Playing Surface: Asymmetric Knowledge

These individuals aren’t playing on a level playing field. A vast “asymmetric knowledge” gulf exists between insurers and workers. The latter consistently make standardized, informed and risk-neutral decisions based on thousands of previous cases. By contrast, injured workers are often encountering the workers’ comp system for the first time. Risk-averse and hesitant to prolong the process, they may elect not to undergo surgery, for example, even if those actions might ultimately be in their best interest.

Workers are prone to make “hot” decisions based on emotion in response to perceived slights or delays. This emotional response is akin to grocery shopping while hungry—when hunger drives the decision-making process, people are more likely to make impulsive purchases, often selecting options that offer immediate satisfaction rather than good value. In contrast, insurance companies are rational, detached “cold” decision makers and are more likely to make strategic choices, much like someone shopping with a list who is focused on value rather than immediate cravings.

Game Theory in Workers’ Comp

Game theory provides a framework for analyzing the strategic interactions between these stakeholders. By modeling these interactions, we can identify potential “friction points” —predictable areas of anticipated “stress” at junctures where delays or conflicts are likely to occur—and predict how long a claim might take to settle.

At its core, game theory is about understanding how players make decisions based on a) the anticipated actions of others and b) the result of a prior outcome.

In addition to the core primary “players,” secondary stakeholders, such as attorneys, the judicial system, nurse case managers and even family members of the individual, introduce “side games.” Each player must make decisions that will affect the others, often without full knowledge of the other players’ intentions, actions, or claim data knowledge.

To apply game theory to workers’ comp, we can create “frictional maps” that identify potential points of delay in a claim’s progression by analyzing key factors: 1) the length of the claim at the time of a treatment request, 2) the type of request—such as therapy, medication, imaging or consultation—and 3) the historical behavior of the approval system. These maps also consider each stakeholder’s motivations and the external factors that influence their decisions.

For example:

• A strained employer-employee relationship might prompt the injured worker to hire a lawyer, adding several months and significant costs to the settlement process.
• A worker may seek a different doctor that is viewed as more “patient friendly” or an “advocate” for recovery.
• An employee with a positive performance history and a diagnosis requiring minimal rehabilitation may experience a quick and harmonious resolution.
• An insurance adjuster with a track record of calling for extensive testing and examination before settling a claim might prolong the process.
• A qualified medical evaluator (QME) who has previously received significant business from the employer might, consciously or unconsciously, factor this into their diagnosis and treatment plan in the form of additional testing and rigid demands of compliance with recommendations.
• Alternatively, the QME may provide a summary rating for settlement while the report clearly states the injured individual is not at maximal medical improvement (MMI), adding another layer of complexity, cost of clarification and confusion.

Dynamic Cooperation and Friction

The early stages of a workers’ comp claim are often characterized by high cooperation and low friction. Insurance companies are generally willing to authorize treatments and tests as they gather information about the case. However, as the claim progresses, authorizations may become less frequent, particularly if utilization review or evidence-based medicine does not support continued treatment.

At this point, friction between the primary stakeholders may increase, players can polarize or have partial alliance relationships leading to delays and potential disputes. For example, an insurer may deny further treatment if it believes that the injured worker has reached MMI, even if the worker and their physician disagree. This is a common “on-ramp” for litigation, immediately escalating costs and timelines.

Advanced Models and Predictive Scenarios

Certainly, game theory can help identify potential points of contention and develop strategies to mitigate them—and technology is aiding this quest. By analyzing thousands of similar cases using generative AI engines, insurance companies can determine the likely outcome trajectories using advanced databases, and ultimately determine settlement expectation conditions based on how claims have been resolved in the past.

In this model, the insurer begins by approving authorizations for diagnostic tests, medications, therapy and consultations during the relatively harmonious early stages of a claim. As more information becomes available, the insurer reduces friction with this knowledge of past claim history. These advanced models can analyze vast amounts of data to predict how individual claims will progress based on factors such as the insurance company, zip code, comorbidities, and the background and experience of the treating physician. In some data models, the outcomes of specific doctors can calculate multipliers on the standardized rating model, creating an “over/under” Vegas-style odds ratio of predictability.

For instance, consider a scenario where an injured worker’s biometric injury profile is analyzed and compared across hundreds of similar cases within a comprehensive high-accuracy database. This analysis factors in the insurance company’s past behavior, the worker’s medical and claim history and the expected decisions of the treating physician, among other variables. This approach could enable precise predictions for setting claim reserves and estimating the date of MMI right from the initial emergency room note on the date of injury.

The permutations of these scenarios are nearly infinite, allowing for highly customized and accurate models that can predict the likely outcome of a claim. This level of precision will revolutionize the workers’ compensation system, providing stakeholders with unprecedented insights into the likely trajectory of cases.

A New Workers’ Comp Claim Game

The application of game theory to workers’ comp offers a powerful tool for understanding the strategic interactions between stakeholders and predicting the likely outcome of a claim. By developing frictional maps and applying advanced data models, we can identify potential points of delay, develop strategies to minimize friction and expedite settlements.

Ultimately, this approach has the potential to transform the workers’ comp system, making it more efficient and predictable for all stakeholders. As AI and data analytics continue to evolve, the insights gained from these models will become increasingly valuable, providing a roadmap for navigating the complex landscape of workers’ comp claims.

Alchemy is founder and CEO of Rate-Fast. He is a diplomate of the American Board of Family Practice. He also has certificates of education from the American Board of Independent Medical Examiners and the American Association of Medical Review Officers.