Refining MediQuit: an iterative, participatory approach to shared decision-making in deprescribing

Area of Science:

• Digital Health Interventions
• Primary Care Medicine
• Pharmacology

Background:

• Polypharmacy and inappropriate medication use are common in primary care, leading to adverse events.
• Deprescribing is crucial but complex, especially for preference-sensitive decisions involving preventive medications.
• Existing digital tools often lack clear implementation guidance for deprescribing.

Purpose of the Study:

• To iteratively refine arribaMediQuit, a digital deprescribing tool for primary care.
• To enhance the tool's usability, ethical robustness, and potential for implementation.
• To support shared decision-making in deprescribing complex medication regimens.

Main Methods:

• An iterative, participatory development process guided by the MRC framework and IPDAS.
• Involvement of diverse stakeholders: general practitioners, researchers, patients, and ethicists.
• Regular expert meetings for content, design, and logic review, with continuous feedback integration.

Main Results:

• Developed a dynamic medication database with tailored decision processes for symptomatic, intermediate, and preventive medications.
• Introduced a linear decision model for preventive medications addressing value-sensitive trade-offs.
• Revised terminology and visuals for clinical clarity and patient comprehension; explicitly addressed ethical considerations.

Conclusions:

• Iterative refinement operationalized shared decision-making principles in a primary care deprescribing tool.
• The tool integrates technical guidance with value-sensitive deliberation for ethically grounded and feasible deprescribing.
• Future research will assess the tool's feasibility, acceptability, and real-world application.