Decision Support in Shared Decision-Making for Patient-Centered Care

Healthcare decisions should be evidence-based and patient-centered. Patient-centered care is about providing quality care with the patient as the focus. The provider has to incorporate the patient’s values, preferences, and objectives into the clinical decision. Traditionally, clinical decisions were made by the provider alone. Healthcare decisions are complex, due to the multiple objectives and potential serious outcomes, making it difficult for the provider to facilitate shared decision-making with the patient. Decision support software can assist with decision-making, by letting the patient incorporate their preferences and perform the decision analysis. Annalisa is a decision support software that has been developed for this purpose. The objective of this thesis is to analyze Annalisa, from a multi-criteria decision analysis (MCDA) perspective and to discuss the tool’s ability to assist with healthcare decisions in a patient-centered care setting. Annalisa’s elements and method were reviewed, using information from the developers. The input data and results from two healthcare studies using Annalisa were used to analyze the tool from a MCDA and patient-centered care perspective and discuss the tool’s ability to provide aid in healthcare decisions. The tool’s method of simple additive weighting (SAW) was compared to the expected utility function using a decision tree. The developers of Annalisa focused on the simplicity and ease of use, rather than creating a new kind of decision support tool. The two example studies indicated problems with the tool’s ability to incorporate the patient’s preferences and values. However, considering that one of the goals with using a decision aid software in healthcare is to assist with decision analysis after the patient has been presented with the information in the traditional healthcare decision guide, Annalisa makes an interesting attempt to provide aid in that next step of the decision-making process