Decision analysis in medicine has not been broadly applied to clinical decision making. It seems particularly suited for high-value decision making where it is imperative to assess uncertainty and complexity with a common goal to optimize decision outcome variables. Balancing Costs and Benefits at Different Stages of Medical Innovation: a Systematic Review of Multi-Criteria Decision Analysis (MCDA) exemplifies the process in a clinical setting, an extension from its origins in engineering and technical frameworks. Decision analysis seeks to address ambiguity and convey recommendations, gain consensus, develop and execute single recommendations or simplify disparate understandings of complex disease states..
Executives are often asked to make critical choices based on gut feel. Even an experienced engineer would not attempt to build a sound bridge this way, and the executive, even one with a great education and lots of experience, should not be expected to arrive a sound decisions this way either. Like a sound bridge design, a good decision needs to be properly engineered; it is naive to guess the answers directly.
Click on the interactive map to see how dragging the Decision Intelligence bubble moves the network and focuses the inputs.
I use these advances in decision intelligence and analysis of data systems to explore complex clinical syndromes and diseases. Building an ecosystem that is responsive and reflexive requires collaborative mapping and differentiation of complex networks. These are certainly team-based discussions and models that are not trivial in diffuse clinical conditions like Alzheimer's disease.
Thus, the optimal prevention and treatment of AD and MCI (mild cognitive impairment) may ultimately be informed by the precedents set during development of successful therapeutics for other chronic illnesses such as cardiovascular disease, osteoporosis and cancer. Although the development and optimization of systems of therapeutics would require radical modernization and streamlining of the current complex structure involved with drug development, approval and administration, the increasing gravity of the failure to develop effective therapeutics for Alzheimer’s disease argues that such therapeutic systems should be considered thoughtfully.--Bredesen 2013
An inability to charactize the etiology of Alzheimer's disease hints at the need for an evolving mechanism that explains the multiple mechanisms involved in pathogenesis. Modernization of current perspectives that include prevention and consideration of age-associated chronic diseases should help narrow the funnel and create targeted algorithms that include lifestyle and social determinants of health outcomes.
Put these developments together with tools like the New York Times’ “You Draw it!” visual relationship drawing widget and all the players in the emerging Decision Intelligence ecosystem, and we can see how the pieces fit together to form a new machine. It’s not just automated systems, but humans in the loop solving problems that go beyond sales and marketing.