Developing a minimum dataset for a national patient registry on Long COVID in Canada: a Delphi consensus-based study

Area of Science:

• Public Health
• Health Services Research
• Patient Registries

Background:

• Long COVID presents a complex, multi-systemic health challenge.
• There is a need for standardized data collection for Long COVID patients.
• A national patient registry is crucial for understanding and managing Long COVID.

Purpose of the Study:

• To develop a comprehensive minimum dataset for a national Long COVID patient registry in Canada.
• To establish consensus on essential survey items for Long COVID data collection.

Main Methods:

• A modified Delphi process involving three rounds of online surveys was employed.
• A diverse panel of 52 experts, including patients, caregivers, clinicians, and researchers, participated.
• An environmental scan of existing literature informed the initial survey item development.

Main Results:

• An initial 243 survey elements were narrowed down through consensus-building rounds.
• 33 core survey elements achieved consensus.
• The final Long COVID minimum dataset comprises 48 items.

Conclusions:

• Broad consensus exists on collecting data for key Long COVID symptoms, including fatigue, post-exertional malaise, cardiovascular, respiratory, and cognitive issues.
• The dataset emphasizes the importance of quality-of-life indicators.
• There is a clear need to capture data on care utilization, quality, and access for Long COVID patients.