Public Authorities as Defendants: Using Bayesian Networks to determine the Likelihood of Success for Negligence claims in the wake of Oakden
This addresses the challenge for citizens and legal practitioners in assessing litigation risks against public authorities in aged care, but it is incremental as it applies an existing method to a new legal domain.
The paper tackles the problem of predicting the likelihood of success for negligence claims against public authorities in aged care, using a Bayesian network trained on case audit data, and finds that plaintiffs succeed in only about one-fifth of cases even when all legal requirements are met.
Several countries are currently investigating issues of neglect, poor quality care and abuse in the aged care sector. In most cases it is the State who license and monitor aged care providers, which frequently introduces a serious conflict of interest because the State also operate many of the facilities where our most vulnerable peoples are cared for. Where issues are raised with the standard of care being provided, the State are seen by many as a deep-pockets defendant and become the target of high-value lawsuits. This paper draws on cases and circumstances from one jurisdiction based on the English legal tradition, Australia, and proposes a Bayesian solution capable of determining probability for success for citizen plaintiffs who bring negligence claims against a public authority defendant. Use of a Bayesian network trained on case audit data shows that even when the plaintiff case meets all requirements for a successful negligence litigation, success is not often assured. Only in around one-fifth of these cases does the plaintiff succeed against a public authority as defendant.