A STATISTICAL-MODEL FOR PREDICTING THE OUTCOME IN BREAST-CANCER MALPRACTICE LAWSUITS

Objective: To analyze specific medical, legal, and cost factors that p redict the probability of successfully defending lawsuits filed becaus e of failure to diagnose breast cancer. Methods: Seventy-six malpracti ce cases handled by the Massachusetts Medical Professional Insurance A ssociation between June 29, 1983 and December 30, 1993 were abstracted and analyzed using univariate analysis, multivariate stepwise logisti c and least-squares regression analysis, and the Cox proportional haza rds model to identify statistically significant associations between c linical factors and medicolegal outcomes. Results: Obstetrician-gyneco logists were defendants in the largest number of cases (38) and incurr ed the highest total indemnity ($7,629,570). The probability of defend ing a suit successfully increased with smaller tumor size and younger patients (less than 40 years of age). The failure to perform a biopsy was associated with a decreased probability of successful defense. Var iables predicting high case cost included younger patient age, an incr eased length of delay in diagnosis, and the failure to perform a biops y. The presence of metastasis at diagnosis was associated with an incr eased interval from diagnosis to the initiation of a suit. Conclusion: Statistical models that use medicolegal and cost factors can predict both the probability of a successful defense and the total cost of a b reast cancer malpractice case.