Evidence-Based Decision Making

Quantitative research is a means by which one can gain factual knowledge. Today, a number of such study design options are available to the researcher. However, when studying these quantifications, the researcher must still make a judgment on the interpretation of those statistical findings. To others, what may seem like conflicting, confusing, or ambiguous data requires thoughtful interpretation. Information for decision making is said to be almost never complete, and researchers [Page 434]always work with a certain level of uncertainty. The need for making and providing proper interpretation of the data findings requires that error-prone humans acknowledge how a decision is made.

Much of the knowledge gained in what is known as the evidence-based movement comes from those in the medical field. Statisticians are an integral part of this paradigm because they aid in producing the evidence through various and appropriate methodologies, but they have yet to define and use terms encompassing the evidence-based mantra. Research methodology continues to advance, and this advancement contributes to a wider base of information. Because of this, the need continues to develop better approaches to the evaluation and utilization of research information. However, such advancements will continue to require that a decision be rendered.

In the clinical sciences, evidence-based decision making is defined as a type of informal decision-making process that combines a clinician's professional expertise coupled with the patient's concerns and evidence gathered from scientific literature to arrive at a diagnosis and treatment recommendation. Milos Jenicek further clarified that evidence-based decision making is the systematic application of the best available evidence to the evaluation of options and to decision making in clinical, management, and policy settings.

Because there is no mutually agreed-upon definition of evidence-based decision making among statisticians, a novel definition is offered here. In statistical research, evidence-based decision making is defined as using the findings from the statistical measures employed and correctly interpreting the results, thereby making a rational conclusion. The evidence that the researcher compiles is viewed scientifically through the use of a defined methodology that values systematic as well as replicable methods for production.

The value of an evidence-based decision-making process provides a more rational, credible basis for the decisions a researcher and/or clinician makes. In the clinical sciences, the value of an evidence-based decision makes patient care more efficient by valuing the role the patient plays in the decision-making process. In statistical research, the value of an evidence-based approach ensures that the methodology used, as well as the logic of the researcher, to arrive at conclusions are sound.

This entry explores the history of the evidence-based movement and the role of decision analysis in evidence-based decision making. In addition, algorithms and decision trees, and their differences, are examined.