Evaluation of a Teleform-based data collection system: a multi-center obesity research case study

Area of Science:

• Clinical data management
• Health informatics
• Data quality assurance

Background:

• Electronic data capture (EDC) systems automate data validation, identifying and correcting errors.
• Traditional paper-based methods pose challenges for real-time data error detection.
• Optimizing data collection tools is crucial for multi-center prospective studies.

Purpose of the Study:

• To evaluate the accuracy of TeleForm, a paper-based data capture software, in a multi-center prospective study.
• To compare the error rates of TeleForm against established data quality benchmarks.
• To identify specific data field types contributing to data entry errors.

Main Methods:

• A prospective, multi-center study utilizing TeleForm for data collection.
• Data accuracy was assessed via a data audit of case report forms (CRFs) and the study database.
• Audits included examination of critical variables for all subjects and all variables for a subset of subjects.

Main Results:

• The TeleForm system demonstrated an overall error rate of 6.7 errors per 10,000 fields.
• Error rates for critical (6.9/10,000) and non-critical (6.5/10,000) variables were below the acceptable threshold of 50 errors per 10,000.
• Error rates varied significantly by data field type, with open text fields exhibiting the highest error frequency.

Conclusions:

• TeleForm, when optimized with custom scripts, offers a viable alternative to EDC systems for accurate clinical data collection.
• The system's performance meets rigorous data quality standards set by the Society for Clinical Data Management.
• Future data collection efforts should focus on strategies to mitigate errors in open text fields.