INFERENCE: An Evidence-Based Approach for Medicolegal Causal Analyses

Int J Environ Res Public Health. 2020 Nov 11;17(22):8353. doi: 10.3390/ijerph17228353.

Abstract

A fundamental purpose of forensic medical, or medicolegal, analysis is to provide legal factfinders with an opinion regarding the causal relationship between an alleged unlawful or negligent action and a medically observed adverse outcome, which is needed to establish legal liability. At present, there are no universally established standards for medicolegal causal analysis, although several different approaches to causation exist, with varying strengths and weaknesses and degrees of practical utility. These approaches can be categorized as intuitive or probabilistic, which are distributed along a spectrum of increasing case complexity. This paper proposes a systematic approach to evidence-based assessment of causation in forensic medicine, called the INtegration of Forensic Epidemiology and the Rigorous EvaluatioN of Causation Elements (INFERENCE) approach. The INFERENCE approach is an evolution of existing causal analysis methods and consists of a stepwise method of increasing complexity. We aimed to develop a probabilistic causal analysis approach that (1) fits the needs of legal factfinders who require an estimate of the probability of causation, and (2) is still sufficiently straightforward to be applied in real-world forensic medical practice. As the INFERENCE approach is most relevant in complex cases, we also propose a process for selecting the most appropriate causal analysis method for any given case. The goal of this approach is to improve the reproducibility and transparency of causal analyses, which will promote evidence-based practice and quality assurance in forensic medicine, resulting in expert opinions that are reliable and objective in legal proceedings.

Keywords: causal analysis; comparative risk; evidence-based practice; forensic medicine; medicolegal analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Causality*
  • Evidence-Based Medicine
  • Expert Testimony*
  • Forensic Medicine* / methods
  • Forensic Medicine* / standards
  • Humans
  • Probability
  • Reproducibility of Results