Overcoming challenges to data quality in the ASPREE clinical trial.

BACKGROUND: Large-scale studies risk generating inaccurate and missing data due to the complexity of data collection. Technology has the potential to improve data quality by providing operational support to data collectors. However, this potential is under-explored in community-based trials. The Aspirin in reducing events in the elderly (ASPREE) trial developed a data suite that was specifically designed to support data collectors: the ASPREE Web Accessible Relational Database (AWARD). This paper describes AWARD and the impact of system design on data quality. METHODS: AWARD's operational requirements, conceptual design, key challenges and design solutions for data quality are presented. Impact of design features is assessed through comparison of baseline data collected prior to implementation of key functionality (n = 1000) with data collected post implementation (n = 18,114). Overall data quality is assessed according to data category. RESULTS: At baseline, implementation of user-driven functionality reduced staff error (from 0.3% to 0.01%), out-of-range data entry (from 0.14% to 0.04%) and protocol deviations (from 0.4% to 0.08%). In the longitudinal data set, which contained more than 39 million data values collected within AWARD, 96.6% of data values were entered within specified query range or found to be accurate upon querying. The remaining data were missing (3.4%). Participant non-attendance at scheduled study activity was the most common cause of missing data. Costs associated with cleaning data in ASPREE were lower than expected compared with reports from other trials. CONCLUSIONS: Clinical trials undertake complex operational activity in order to collect data, but technology rarely provides sufficient support. We find the AWARD suite provides proof of principle that designing technology to support data collectors can mitigate known causes of poor data quality and produce higher-quality data. Health information technology (IT) products that support the conduct of scheduled activity in addition to traditional data entry will enhance community-based clinical trials. A standardised framework for reporting data quality would aid comparisons across clinical trials. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number Register, ISRCTN83772183. Registered on 3 March 2005.

Stakeholder Satisfaction with the Australian Rheumatology Association Database (ARAD).

BACKGROUND: The Australian Rheumatology Association Database (ARAD) is a voluntary national registry for monitoring the long-term benefits and safety of biological disease-modifying anti-rheumatic drugs (bDMARDs) for inflammatory arthritis. Both rheumatologists and patients contribute data to the ARAD. OBJECTIVE: To evaluate the satisfaction of patients and rheumatologists with the ARAD. METHODS: Cross-sectional surveys were distributed to a random sample of 100 community-dwelling ARAD patients in 2007 and to rheumatologists attending the 2007 Australian Rheumatology Association (ARA) annual scientific meeting.Survey questions included items about the usefulness of the ARAD, workload for participants, frequency of questionnaires, and experience of contact with ARAD staff. RESULTS: A total of 92.5% of patients perceived the ARAD as very important (scoring 9-10 on a numeric rating scale). Patients reported minimal difficulty in completing questionnaires, and 95.0% indicated that a 6-month interval between questionnaires was reasonable. Of responding rheumatologists, 32.3%, 62.1%, and 53.8% indicated that the ARAD was very important (scoring 8-10) with respect to clinical information, research, and the profession, respectively, while 68% of those participating in the ARAD reported that the workload required to enroll patients was manageable and 30% found it difficult or onerous. CONCLUSION: Key stakeholders in the ARAD view it as an important resource and are satisfied with its operations. Efforts will be directed towards assisting those rheumatologists who find the associated workload difficult and to improving the perceived clinical value of information available from the ARAD.