Electronic Data Capture Versus Conventional Data Collection Methods in Clinical Pain Studies: Systematic Review and...

Area of Science:

• Pain research
• Health informatics
• Data science

Background:

• Traditional pain assessment relies on self-reported questionnaires via paper, phone, or in-person methods.
• These conventional methods may compromise the validity and reliability of pain data.
• Electronic data capture offers a promising alternative for collecting pain-related information.

Purpose of the Study:

• To systematically review and meta-analyze studies comparing electronic and conventional pain data collection.
• To assess equivalence in pain scores, data completeness, ease of use, efficiency, and acceptability.
• To determine the feasibility of electronic methods in clinical and research settings.

Main Methods:

• Systematic review and meta-analysis of peer-reviewed studies.
• Searched MEDLINE, EMBASE, and CENTRAL databases up to November 2019.
• Included studies comparing electronic and conventional pain data capture on specific outcomes.

Main Results:

• 82% of studies showed congruent pain scores between electronic and conventional methods (correlation coefficient 0.92).
• Electronic methods were generally equivalent or superior in data completeness, ease of use, and efficiency.
• 83% of patients preferred electronic data collection formats.

Conclusions:

• Electronic pain data capture methods are comparable to conventional approaches.
• Electronic methods demonstrate equivalence or superiority in key data quality and user experience metrics.
• With proper psychometric validation, electronic tools are feasible for pain data collection in diverse settings.