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Decision Making in Health and Medicine: Integrating Evidence and Values

‘Not another book on evidence-based medicine!’ must surely be the reaction that the editors and publishers of this text were trying to avoid. Evidence-based medicine (EBM) has become the new orthodoxy. All true believers (and even agnostics) no doubt possess a copy of the thoughts of sages such as Sackett. However, EBM has its critics, one of whose arguments is the essential need in clinical practice to consider the individual patient in front of you rather than probabilities. Decision Making in Health and Medicine attempts to overcome these difficulties by describing an approach to which the authors give the acronym PROACTIVE (problem-reframe-objectives-alternatives-consequences and chances-trade offs-integrate-value-explore-evaluate). This is an impressively comprehensive approach to clinical decision-making with every angle considered, advantages and disadvantages tabulated. The authors then lead us through chapters on probability, decision trees, utility assessment, Bayes' theorem, decision trees with Bayes' theorem, analysis of tests, analysis of data, cost-effectiveness analysis, state transition models, other advanced models and a final overview. 
 
There is a great deal of knowledge and information in these chapters, presented with masses of detailed mathematical and statistical analysis. The pages of equations and formulae were quite offputting to me, an average clinician, and beyond my grasp of mathematics. I did find the formula for how to calculate mortgage repayments quite fascinating though and the sort of thing to impress your bank manager or accountant with. The method of deriving the solution of an algebraic equation by the use of geometry was again novel and impressive to me though I must confess to not really understanding the proof (QED and all that). 
 
I suppose therein lies my disappointment with this book. The cover states that it is ‘user friendly’, ‘clearly explains’ and is ‘of immense practical value’ to ‘all those charged with decision making in medicine.’ As I soldiered on through hundreds of pages of dense academic prose and intricate equations, the thought that I was gaining a new practical insight into clinical decision-making, albeit only at my rudimentary level of understanding, kept me going. However, on p. 372 the authors state they ‘do not make a decision tree for every patient that consults us. On the contrary; it is more the insights that we have gained from... the PROACTIVE approach that have been helpful.’ It is exactly those sorts of insights from the authors' own experience of analysing and researching medical decision-making that practising clinicians might find of most interest and relevance, rather than detailed mathematical proofs. 
 
The accompanying CD-ROM gives perhaps a truer representation of the readers likely to understand and benefit most from the approach described. The CD contains lists of references, useful websites, two decision analysis programs and a programming language which readers can use to design their own software for decision analysis. We are told that Fellows in Decision Analysis at the New England Medical Center have used these programs. Notes are also available from one of the editors for those involved in teaching others these techniques. 
 
Overall, this text seems of most interest to those studying or teaching medical decision analysis as an academic subject or considering developing software models. Therefore I regard the cover as quite misleading. Of course, some doctors and students may wish to read this sophisticated mathematical treatise simply for the intellectual challenge.