1,720,991 research outputs found
An Evidence-Hierarchical Decision Aid for Ranking in Evidence-Based Medici
Full text linkThis chapter addresses the problem of ranking available drugs in guideline development to support clinicians in their work. Based on a pragmatic approach to the notion of evidence and a hierarchical view on different kinds of evidence this chapter introduces a decision aid, HiDAD, which draws on the multi criteria decision making literature. This decision aid implements the wide-spread intuition that there are different kinds of evidence with varying degrees of importance by relying on a strict ordinal ordering of kinds of evidence. In order to construct a ranking every pair of drugs is first compared separately on all kinds of evidence. Next, these quantitative comparisons are then aggregated into an overall comparison between drugs based on all the available evidence in a way which avoids that evidence of less importance is trumped by evidence of the higher levels. Finally, these overall comparisons are used to determine the final ranking of drugs which then informs the process of guideline writing. Properties, modifications and applicability of the decision aid HiDAD are discussed and assessed
Uncertainty in Pharmacology
No full textThis volume covers a wide range of topics concerning methodological, epistemological, and regulatory-ethical issues around pharmacology. The book focuses in particular on the diverse sources of uncertainty, the different kinds of uncertainty that there are, and the diverse ways in which these uncertainties are (or could be) addressed. Compared with the more basic sciences, such as chemistry or biology, pharmacology works across diverse observable levels of reality: although the first step in the causal chain leading to the therapeutic outcome takes place at the biochemical level, the end-effect is a clinically observable result—which is influenced not only by biological actions, but also psychological and social phenomena. Issues of causality and evidence must be treated with these specific aspects in mind. In covering these issues, the book opens up a common domain of investigation which intersects the deeply intertwined dimensions of pharmacological research, pharmaceutical regulation and the related economic environment. The book is a collective endeavour with in-depth contributions from experts in pharmacology, philosophy of medicine, statistics, scientific methodology, formal and social epistemology, working in constant dialogue across disciplinary boundaries
Better evaluating mechanisms in medicine. Book review: Evaluating evidence of mechanisms in medicine
No full textEvidence of mechanisms plays an important role in medical decision-making, but this role is less well articulated than that of clinical trial evidence. A new book, Evaluating Evidence of Mechanisms in Medicine: Principles and Procedures, provides a framework and resources for explicitly evaluating evidence of mechanisms when assessing claims of efficacy and external validity. This review outlines the overall approach of the book, the contribution it makes to evidence evaluation in medicine and makes some suggestions for further work that will aid implementation of the framework into clinical decision-making
A problem for achieving informed choice
No full textMost agree that, if all else is equal, patients should be provided with enough information about proposed medical therapies to allow them to make an informed decision about what, if anything, they wish to receive. This is the principle of informed choice; it is closely related to the notion of informed consent. Contemporary clinical trials are analysed according to classical statistics. This paper puts forward the argument that classical statistics does not provide the right sort of information for informing choice. The notion of probability used by classical statistics is complex and difficult to communicate. Therapeutic decisions are best informed by statistical approaches that assign probabilities to hypotheses about the benefits and harms of therapies. Bayesian approaches to statistical inference provide such probabilities
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