Development of a Cocreated Decision Aid for Patients With Depression-Combining Data-Driven Prediction With Patients'...

Area of Science:

• Mental Health Research
• Clinical Decision Support Systems
• Patient-Centered Care

Background:

• Major depressive disorders (MDD) have varied treatment responses, necessitating personalized care.
• Shared decision-making (SDM) is crucial for patient-centered treatment but lacks adequate instruments for depression.
• Existing tools often fail to integrate personalized data and patient co-creation.

Purpose of the Study:

• To develop an instrument for SDM in depression treatment.
• To provide patients and clinicians with systematic, personalized information via a digital report.
• To guide treatment decisions using objective, evidence-based data.

Main Methods:

• Co-led by researchers and patient representatives using a mixed-methods approach (2017-2021).
• Qualitative research explored end-user needs; a scoping review identified treatment response predictors.
• K-means cluster analysis identified patient clusters for tailored treatment suggestions.

Main Results:

• The Instrument for Shared Decision-making in Depression (I-SHARED) was developed.
• Four categories of treatment response predictors and five patient clusters were identified.
• The I-SHARED report integrated findings and was prepared for piloting within electronic health records.

Conclusions:

• The collaboratively developed I-SHARED tool enhances informed, patient-centered treatment decisions for MDD.
• It represents a significant advancement in personalized treatment and SDM for depression.
• The tool facilitates shared decision-making by combining individual data with objective treatment information.