The Sucker's Paradox

Honesty is not a winning strategy

Every doctor experiences this multiple times a day. You open your inbox and see a message from a coding specialist asking you to clarify whether a patient’s heart failure was acute, chronic, acute on chronic, with or without organ dysfunction, and whether it was present on admission. The message has nothing to do with how the patient was treated. It exists because the phrasing of that sentence will materially change the hospital’s reimbursement.

Modern healthcare policy has produced a strange equilibrium, one that increasingly reflects our broader regulatory culture. It combines dense rulemaking with means-tested exceptions, discretionary enforcement, and leniency for hardship. Each of those elements is defensible on its own. We want standardized payments so hospitals cannot charge wildly different amounts for similar care. We want adjustments for sicker patients so institutions are not penalized for taking on complex cases. We want compassion in enforcement because real lives are affected. Yet when these components are layered together, they create a predictable outcome: the honest actor is penalized relative to the strategic actor.

Consider a standard hospital admission under Medicare’s prospective payment system. A pneumonia admission is paid a fixed amount under a Diagnosis Related Group, or DRG. The purpose is straightforward: limit variation in pricing and prevent hospitals from billing whatever they choose. But not all pneumonias are alike. An 87-year-old with dementia and heart failure is categorically different from a healthy 34-year-old athlete. To account for this, payment increases when patients appear sicker on paper. Additional diagnoses raise the DRG weight.

Once payment depends on documented severity, documentation becomes economically valuable. Hospitals hire coding teams to comb through charts for additional diagnoses. Physicians receive requests to clarify whether a condition was acute on chronic, whether kidney injury met formal criteria, whether an infection was confirmed, or whether something was present on admission. Insurers respond by hiring audit teams to challenge those classifications. No one in this exchange believes they are committing fraud. Each side insists it is simply applying the rules accurately and protecting its financial position. Yet the economic focus subtly shifts away from clinical care and toward classification strategy.

Insurance companies operate under the same incentive structure. In Medicare Advantage, plans receive a fixed payment per enrollee, adjusted for risk. The sicker the patient appears, the higher the payment. Insurers therefore invest heavily in identifying additional diagnoses through home visits, chart reviews, and increasingly sophisticated software. This activity is described as improving risk adjustment accuracy, and much of it falls within regulatory boundaries. Still, payment flows not only from improving health but from maximizing diagnostic classification within complex rules.

None of these examples necessarily constitute fraud. They are instances of actors operating near the edge of what the rules permit, stretching documentation and interpretation to capture legitimate but aggressively defined reimbursement. Economically, this behavior makes sense. Regulation increases the payoff to classification. Leniency reduces the perceived risk of punishment. Information asymmetry makes perfect verification impossible; an auditor cannot easily determine whether a borderline case truly met every definitional nuance. Policymakers are reluctant to penalize hospitals caring for sicker patients or insurers covering complex beneficiaries, so enforcement tends to be selective and politically constrained. Meanwhile, auditing every case would be logistically infeasible, even with modern AI.

In such an environment, competitive pressures do the rest. If one hospital aggressively optimizes documentation and another does not, the optimizing hospital will generate higher margins. If one insurer captures every possible risk-adjustment code and another leaves money on the table, the latter will underperform financially. Over time, the actor who declines to play the classification game bears opportunity cost. Honesty does not generate a bonus; it generates a disadvantage. The equilibrium stabilizes not around overt fraud, but around aggressive compliance optimization.

This dynamic is not unique to healthcare. Any system that relies on intricate rules, targeted benefits, and discretionary enforcement will tend to reward those who master classification. Tax codes, defense contracts, agricultural subsidies, and other regulatory frameworks generate similar incentives. Economic value increasingly accrues not solely to those who produce goods and services, but to those who navigate complexity most effectively. Industries arise around rule interpretation. Compliance becomes a competitive strategy.

We did not set out to build dishonest institutions. The intent was to design systems that were fair, standardized, and resistant to abuse. Yet when payment depends on ever more granular distinctions, and when enforcement can never be perfect, behavior adapts. The issue is not that people are uniquely unethical. It is that we have constructed institutions in which honesty is not the dominant strategy. Once that equilibrium takes hold, trust erodes quietly. Participants begin to assume that everyone else is optimizing aggressively, and they respond in kind. Rebuilding trust in such a system is far more difficult than drafting another regulation.