The fundamentals.
Before applying the method, start with the mindset. A credible causation analysis requires more than a conclusion — it requires evidence, disciplined reasoning, and awareness of the limits of what the facts can support. This section introduces four foundational ideas that separate a scientifically credible analysis from assumption, advocacy, or unsupported opinion.
Why causation demands science.
Few questions in medicine carry as much consequence for an individual, an employer, an insurer, and society. The answer may determine who pays, who is held responsible, what care is authorized, and whether the result is fair. A question of that weight deserves a disciplined, transparent, and reproducible method. It deserves science.
Causation analysis is not a matter of intuition, sympathy, or professional reputation. It is a structured inquiry grounded in objective facts, published scientific literature, and sound clinical reasoning. Performed well, it produces conclusions that another qualified evaluator, reviewing the same records and the same science, could independently understand and test. Performed poorly, it produces opinions that vary from one examiner to the next — untethered from evidence and vulnerable to bias.
Diagnosis asks what is wrong. Causation asks what is responsible. They are not the same question.
Determining causation is fundamentally different from diagnosing an individual, planning treatment, estimating prognosis, or rating impairment. A fracture may be treated the same way whether it occurred at work or at home. Causation, by contrast, is a forensic question that asks whether a condition should be attributed to a claimed exposure under the applicable legal or administrative standard.
Because the question is forensic, disputed causation analysis should be conducted with independence. Treating clinicians provide essential observations about history, examination, diagnosis, treatment, and clinical course, but they may face practical, therapeutic, financial, or social pressures when asked to render causation opinions for individuals they are treating. The therapeutic role and the forensic role have different purposes. When causation is disputed, the analysis is best performed as an independent, evidence-based assessment.
The single most important distinction.
Science is a systematic method of searching for, testing, and verifying facts. It values reproducible, evidence-based observation over individual belief. A scientific finding does not depend on who first reported it; if it can be independently verified, the identity or credentials of the person who introduced it should not determine its value.
Legal and administrative systems often operate differently. They rely heavily on expert opinion, which can sometimes elevate confidence, credentials, convenience, or presentation above independently verifiable fact. A clinician trained in the scientific tradition can be drawn, almost without noticing, into offering opinions based on personal experience rather than evidence-based method. A structured causation method is one of the best protections against that drift.
It helps the evaluator approach the analysis as a disciplined medical and scientific inquiry, rather than as unsupported opinion or advocacy.
This is not a criticism of clinical judgment, which remains essential. It is a discipline placed around that judgment, so the conclusion rests on something more durable than the confidence of the person stating it.
Reasonable medical probability.
In most workers' compensation and disability settings, causation is commonly judged by whether the relationship is more likely than not — often described medically as a reasonable degree of medical probability. Terminology varies by jurisdiction, including preponderance of the evidence, reasonable medical probability, reasonable medical certainty, or more probable than not. The practical threshold is usually whether the causal relationship is more probable than its absence.
This standard requires the evaluator to distinguish carefully between what is probable and what is merely possible. A factor may be biologically plausible, temporally associated, or statistically linked at a low level without satisfying the standard of reasonable medical probability. The fact that a causal relationship cannot be excluded does not mean it has been established. Confusing possibility with probability is one of the most common and consequential errors in causation analysis.
Four common patterns that lead to flawed causation opinions.
Most flawed causation opinions fail in recognizable ways. Naming the pattern makes it easier to avoid the error.
{{ t.title }}
{{ t.desc }}
Adapted from The Science of Causation: Principles and Best Practices for Determining Injury and Disease Relatedness and The Science of Causation: An Introduction to Biostatistics — foundational educational source documents for OpenCausation.orgSM — by J. Mark Melhorn, MD.