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Decision analysis in the clinical neurosciences: a systematic review of the literature
Author(s) -
Dippel D.W.J.,
Habbema J.D.F.
Publication year - 1995
Publication title -
european journal of neurology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.881
H-Index - 124
eISSN - 1468-1331
pISSN - 1351-5101
DOI - 10.1111/j.1468-1331.1995.tb00170.x
Subject(s) - context (archaeology) , decision analysis , medicine , management science , decision theory , clinical decision making , intensive care medicine , mathematics , paleontology , statistics , economics , biology
Clinical decision analysis can be a useful scientific tool for individual patient management, for planning of clinical research and for reaching consensus about clinical problems. We systematically reviewed the decision analytic studies in the clinical neurosciences that were published between 1975 and July 1994. All studies were assessed on aspects of clinical applicability: presence of case and context description, completeness of the analysed strategies from a clinical point of view, extendibility of the analyses to different patient profiles, and up‐to‐date‐ness. Fifty‐nine decision analyses of twenty‐eight different clinical problems were identified. Twenty‐eight analyses were based on the theory of subjective expected utility, twelve on cost‐effectiveness analysis. Four studies used ROC analysis, and fifteen were risk‐, or risk‐benefit analyses. At least six studies could have been improved by more elaborately disclosing the context of the clinical problem that was addressed. In eleven studies, the effect of different, yet plausible assumptions was not explored, and in eighteen studies the reader was not informed how to extend the results of the analysis to patients with (slightly) different clinical characterisitics. All studies had, by nature, the potential to promote insight into the clinical problem and focus the discussion on clinically important aspects, and gave clinically useful advice. We conclude that clinical decision analysis, as an explicit, quantitative approach to uncertainty in decision making in the clinical neurosciences will fulfill a growing need in the near future.

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