Journal article
Overcoming challenges to data quality in the ASPREE clinical trial
Trials, Vol.20(1), pp.686-686
12/09/2019
DOI: 10.1186/s13063-019-3789-2
PMCID: PMC6902598
PMID: 31815652
Abstract
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-ofrange 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.
Details
- Title: Subtitle
- Overcoming challenges to data quality in the ASPREE clinical trial
- Creators
- Jessica E. Lockery - Monash UniversityTaya A. Collyer - Monash UniversityChristopher M. Reid - Monash UniversityMichael E. Ernst - Roy J. and Lucille A. Carver College of MedicineDavid Gilbertson - Orthopaedic Research FoundationNino Hay - Monash UniversityBrenda Kirpach - Berman Center for Outcomes and Clinical ResearchJohn J. McNeil - Monash UniversityMark R. Nelson - Monash UniversitySuzanne G. Orchard - Monash UniversityKunnapoj Pruksawongsin - Monash UniversityRaj C. Shah - Rush University Medical CenterRory Wolfe - Monash UniversityRobyn L. Woods - Monash UniversityASPREE Investigator Group
- Resource Type
- Journal article
- Publication Details
- Trials, Vol.20(1), pp.686-686
- DOI
- 10.1186/s13063-019-3789-2
- PMID
- 31815652
- PMCID
- PMC6902598
- NLM abbreviation
- Trials
- ISSN
- 1745-6215
- eISSN
- 1745-6215
- Publisher
- Springer Nature
- Number of pages
- 11
- Grant note
- U01AG029824 / National Cancer Institute at the National Institutes of Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI) U19AG062682; U01AG029824 / NATIONAL INSTITUTE ON AGING; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute on Aging (NIA) Monash University (Australia); Monash University National Institute on Aging; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute on Aging (NIA) Victorian Cancer Agency (Australia) 334047; 1127060 / National Health and Medical Research Council of Australia; National Health and Medical Research Council (NHMRC) of Australia
- Language
- English
- Date published
- 12/09/2019
- Academic Unit
- Family and Community Medicine; Pharmacy Practice and Science
- Record Identifier
- 9984297335502771
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