A User-Centered Designed Anticoagulation Shared Decision-Making Tool for Stroke Prevention in Atrial Fibrillation (Michigan)

Project Details - Ongoing

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Summary:

Atrial fibrillation (AF) is the most common cardiac arrhythmia, with a projected prevalence of 12.1 million by 2030 in the United States. With a two- to five-fold increased risk of stroke in this population, anticoagulation is recommended for most AF patients; however, this therapy brings with it a risk of bleeding. Balancing the risks of stroke versus bleeding requires a personalized approach. The American College of Cardiology and the American Health Association’s clinical performance measures for AF identify shared decision making of anticoagulant therapy as a quality metric, but does not provide a standardized and understandable method to demonstrate the risks versus benefits of anticoagulation therapy in these patients.

In this current research, the investigators will work with patients and providers to create a decision support tool that clarifies the risk tradeoffs for anticoagulation in AF, develop and implement a shared decision making support application based on patient and provider feedback, and determine how the new decision support tool that incorporates patient preferences about the risk tradeoffs compares to standard communication. Value clarification can often help an individual increase awareness of any values that may have a bearing on lifestyle decisions and actions.

The specific aims of this research are as follows:

  • Use user-centered design principles to design a decision support tool that clarifies the relevant risk tradeoffs for anticoagulation in AF for patients and providers. 
  • Develop a shared decision-making support application for the anticoagulation decision in AF. 
  • Demonstrate the comparative efficacy of the decision support tool in increasing patient knowledge of the risk tradeoffs during shared decision making for anticoagulation in AF. 

The investigators will conduct one-on-one semi-structured interviews with patients and providers to explore methods of communicating both outcome probabilities, but also interview patients to understand their experience of different outcomes. Investigators will also develop: 1) the risk software objects to compute algorithms for risk of anticoagulation in AF, 2) the software objects to create visuals from Aim 1 based on the risk algorithms, and 3) the web application that will present the tailored visuals allowing users to add a value clarification. Finally, investigators will conduct a survey with adults 45 years and older. Participants will be randomized to standard written communication, standard information plus a visual representation of relevant probabilities of risk, or to the new decision support tool that combines design-tailored visual displays with value clarification.

Ultimately, the investigators hope that the study will develop patient and provider-centered clinical decision support to improve cardiovascular outcomes. 

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