Clinical judgement in the interpretation of evidence: a Bayesian approach


  • Jean Harbison MPhil, RGN, SCM, RNT, RCNT

    1. Senior Lecturer, Department of Nursing, School of Health Sciences, Queen Margaret University College, Clerwood Terrace, Edinburgh, UK
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Jean Harbison
Senior Lecturer
Department of Nursing
School of Health Sciences
Queen Margaret University College
Clerwood Terrace
EH12 8TS
Telephone: 0131 317 3561


Aim.  This paper presents an argument for the use of Bayesian reasoning in considering the value of evidence in making nursing judgements.

Background.  Nursing has taken on board the drive towards evidence-based practice. There has been little discussion, however, of how evidence should be interpreted. There is a growing interest in health care in the use of Bayesian reasoning for evidence interpretation, both in research and in clinical practice; as yet, there is a limited discussion in the literature of relevance to nursing.

Objectives.  To provide a short tutorial in the application of Bayes rule to a clinical judgement. To discuss the implications for practice of adopting a Bayesian perspective.

Discussion.  The relationship between evidence and clinical judgement is outlined. The need to accept uncertainty, and be equipped to deal adequately with this, is discussed: some basic ideas of probability are rehearsed. An outline of Bayesian reasoning is offered and a demonstration of the application of Bayes rule to a nursing judgement is presented.

Relevance to practice.  A rationale for adopting a Bayesian perspective on evidence interpretation is offered: namely the changing context of practice, with the blurring of professional boundaries and the need to articulate judgements, the avoidance of error and the opportunity to identify the appropriate areas for investigation in nursing.