Causal inference in perioperative medicine observational research: part 2, advanced methods

Br J Anaesth. 2020 Sep;125(3):398-405. doi: 10.1016/j.bja.2020.03.032. Epub 2020 May 3.

Abstract

Although RCTs represent the gold standard in clinical research, most clinical questions cannot be answered using this technique, because of ethical considerations, time, and cost. The goal of observational research in clinical medicine is to gain insight into the relationship between a clinical exposure and patient outcome, in the absence of evidence from RCTs. Observational research offers additional benefit when compared with data from RCTs: the conclusions are often more generalisable to a heterogenous population, which may be of greater value to everyday clinical practice. In Part 2 of this methods series, we will introduce the reader to several advanced methods for supporting the case for causality between an exposure and outcome, including: mediation analysis, natural experiments, and joint effects methods.

Keywords: causal inference; confounding; epidemiology; joint effects; mediation analysis; natural experiment; observational research.

Publication types

  • Review

MeSH terms

  • Biomedical Research / methods*
  • Humans
  • Observational Studies as Topic / methods*
  • Perioperative Medicine / methods*