Related Experiment Video
Updated: Jun 5, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
The democratic fallacy in matters of clinical opinion: implications for analysing cause-of-death data
1Umeå Centre for Global Health Research, Department of Public Health and Clinical Medicine, Umeå University, Umeå 90185, Sweden. peter.byass@epiph.umu.se.
Abstract:
Arriving at a consensus between multiple clinical opinions concerning a particular case is a complex issue - and may give rise to manifestations of the democratic fallacy, whereby a majority opinion is misconstrued to represent some kind of "truth" and minority opinions are somehow "wrong". Procedures for handling multiple clinical opinions in epidemiological research are not well established, and care is needed to avoid logical errors. How to handle physicians' opinions on cause of death is one important domain of concern in this respect. Whether multiple opinions are a legal requirement, for example ahead of cremating a body, or used for supposedly greater rigour, for example in verbal autopsy interpretation, it is important to have a clear understanding of what unanimity or disagreement in findings might imply, and of how to aggregate case data accordingly.In many settings where multiple physicians have interpreted verbal autopsy material, an over-riding goal of arriving at a single cause of death per case has been applied. In many instances this desire to constrain findings to a single cause per case has led to methodologically awkward devices such as "TB/AIDS" as a single cause. This has also usually meant that no sense of disagreements or uncertainties at the case level is taken forward into aggregated data analyses, and in many cases an "indeterminate" cause may be recorded which actually reflects a lack of agreement rather than a lack of data on possible cause(s).In preparing verbal autopsy material for epidemiological analyses and public health interpretations, the possibility of multiple causes of death per case, and some sense of any disagreement or uncertainty encountered in interpretation at the case level, need to be captured and incorporated into overall findings, if evidence is not to be lost along the way. Similar considerations may apply in other epidemiological domains.
Related Concept Videos
Bias in Epidemiological Studies
Causality in Epidemiology
Confounding in Epidemiological Studies
Assumptions of Survival Analysis
Criteria for Causality: Bradford Hill Criteria - II
Statistical Methods for Analyzing Epidemiological Data
