Appl Clin Inform 2018; 09(01): 072-081
DOI: 10.1055/s-0037-1621702
Research Article
Schattauer GmbH Stuttgart

Exploring Data Quality Management within Clinical Trials

Lauren Houston
,
Yasmine Probst
,
Ping Yu
,
Allison Martin
Funding None.
Further Information

Publication History

17 August 2017

06 December 2017

Publication Date:
31 January 2018 (online)

Abstract

Background Clinical trials are an important research method for improving medical knowledge and patient care. Multiple international and national guidelines stipulate the need for data quality and assurance. Many strategies and interventions are developed to reduce error in trials, including standard operating procedures, personnel training, data monitoring, and design of case report forms. However, guidelines are nonspecific in the nature and extent of necessary methods.

Objective This article gathers information about current data quality tools and procedures used within Australian clinical trial sites, with the aim to develop standard data quality monitoring procedures to ensure data integrity.

Methods Relevant information about data quality management methods and procedures, error levels, data monitoring, staff training, and development were collected. Staff members from 142 clinical trials listed on the National Health and Medical Research Council (NHMRC) clinical trials Web site were invited to complete a short self-reported semiquantitative anonymous online survey.

Results Twenty (14%) clinical trials completed the survey. Results from the survey indicate that procedures to ensure data quality varies among clinical trial sites. Centralized monitoring (65%) was the most common procedure to ensure high-quality data. Ten (50%) trials reported having a data management plan in place and two sites utilized an error acceptance level to minimize discrepancy, set at <5% and 5 to 10%, respectively. The quantity of data variables checked (10–100%), the frequency of visits (once-a-month to annually), and types of variables (100%, critical data or critical and noncritical data audits) for data monitoring varied among respondents. The average time spent on staff training per person was 11.58 hours over a 12-month period and the type of training was diverse.

Conclusion Clinical trial sites are implementing ad hoc methods pragmatically to ensure data quality. Findings highlight the necessity for further research into “standard practice” focusing on developing and implementing publicly available data quality monitoring procedures.

Authors' Contributions

L.H. conceptualized and formulated the research question, designed the study, performed the study, evaluated the data, drafted the initial manuscript, revised the manuscript, and approved the final manuscript as submitted. Y.P., P.Y., and A.M. made substantial contributions to the study design, analysis, and interpretation of the data, critically reviewed the manuscript, and approved the final manuscript as submitted.


Protection of Human and Animal Subjects

This study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was approved by the University of Wollongong Human Research Ethics Committee (HE16/131).