A Multidimensional Data Set for Obsessive-Compulsive Disorder to Strengthen Research and Care: A Cross-Sectional...

Area of Science:

• Psychiatry and Mental Health
• Health Informatics
• Epidemiology

Background:

• Obsessive-compulsive disorder (OCD) significantly impacts quality of life, yet diagnosis and data collection are often fragmented.
• Existing assessment tools for OCD primarily focus on symptom severity, neglecting crucial demographic, environmental, and service utilization data.

Purpose of the Study:

• To develop a standardized, multidimensional minimum data set (MDS) for obsessive-compulsive disorder (OCD).
• To enhance clinical decision-making and facilitate robust epidemiological research in OCD.

Main Methods:

• A modified Delphi technique involving 20 experts from diverse fields was employed over two consensus rounds.
• An initial 94 data elements were evaluated, leading to the refinement and categorization of the final MDS into seven domains.

Main Results:

• The Delphi process resulted in a consensus on a final MDS comprising 66 essential data elements.
• Experts initially approved 39 items and rejected 4, with 51 items requiring further evaluation in the first round. The second round finalized 27 additional items.

Conclusions:

• The developed MDS addresses limitations of current OCD assessment tools by incorporating multidimensional data.
• Implementation of this MDS is expected to improve personalized patient care, inform public health policies, and potentially reduce health disparities.
• Further validation studies are recommended to confirm the MDS's impact on patient outcomes and its global applicability.