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Table 1. Common Sources of Error and Primary Detection Methods
DETECTION METHODS | |||||
|---|---|---|---|---|---|
SOURCES OF ERROR | Programmatic Data Checks | Source Data V erification | Data | Aggregate Statistics | CRF-to-Database Inspection |
Subject completes questionnaire incorrectly or provides incorrect or incomplete answers to questions (lack of tool validation or bad form design) | X | ||||
Subject does not follow trial conduct instructions | X | ||||
Inadequate instructions given to the subject | X | ||||
Site personnel trial conduct error (protocol violation) | X | X | |||
Data captured incorrectly on the source | X | X | |||
Site personnel transcription error | X | X | X | ||
Site equipment error | X | ||||
Human error in reading equipment or print out or inter-rater-reliability | X | ||||
Data entry error | X | X | X | X | |
Electronic data acquisition error (power glitch, back up that didn’t run, lead not attached securely) | X | X | |||
Data linked to the wrong subject | X | X | X | ||
Database updated incorrectly from data clarification form or query | X | ||||
Missing data | X | X | |||
Outliers | X | ||||
Data inconsistencies | X | X | |||
Programming error in user interface or database or data manipulations | X | ||||
Lost data | X | X | |||
Fraud | X | X | |||
Errors caused by fraud and protocol violations can be difficult to detect without the use of special programming and the use of aggregate statistics.3, 5, 6, 7, 8, 9 Throughout a trial, aggregate statistics should be available to monitors to facilitate detection of misunderstandings, misconduct and fraud. Data management is the first point in many processes where the data are available for viewing in aggregate across sites. It is at this earliest point that aggregate statistics should be provided to monitors and other study personnel to quickly identify sites that are behaving differently from the rest. Aggregate data reports may be designed to summarize the performance of individual centers in the areas of recruitment, extent of follow-up, compliance to treatment, completion of procedures, late visits, or data queries.2
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