Negotiating in the Shadow of 'Bad Faith' Refusal to Settle: A Game Theory Model of Medical Malpractice Pre-Trial Settlements and Insurance Limits

Abstract

Recent empirical studies of Texas data by Hyman et al, Zeiler et al, and Silver et al suggest that insurance limits affect settlements of medical malpractice cases. Writing separately, Silver argues that insurance limits act as a de facto cap on malpractice payouts, that plaintiffs are being underpaid as a result, and that therefore legislative caps on damages are unnecessary. But this hypothesis is inconsistent with the data, which indicates that forty-seven percent of cases in which plaintiffs obtain verdicts above policy limits are subsequently settled above policy limits. We propose to reconcile the data by accounting for the effects that third-party causes of action for alleged bad-faith refusal to settle — known in Texas as a Stowers action — have on pretrial settlement negotiations. If an insurer in Texas is presented with a settlement offer within insurance limits, refuses to settle, and the plaintiff wins an award greater than insurance limits, the plaintiff is entitled to sue the insurer for the full damages amount, plus punitive damages, for refusal to settle. In this paper, we explore the game theory of medical malpractice settlement negotiations in the shadow of Stowers.Using a Monte Carlo simulation of the “game,” we find: (1) plaintiffs have an incentive to make, and defendants have an incentive to accept, settlement offers at insurance limits; (2) a settlement at insurance limits may therefore sometimes reflect something other than the quality of the underlying medical malpractice case; (3) the possibility of Stowers awards increases expected returns to plaintiffs and disproportionately increases the settlement value of low-merit cases; (4) plaintiffs with weak cases are systematically overcompensated, while plaintiffs with strong cases are systematically under compensated; and (5) non-economics damages caps have the greatest effect on low-merit cases by reducing overcompensation, without affecting the highest-merit cases.