Error Rates of Data Processing Methods in Clinical Research: A Systematic Review and Meta-Analysis of Manuscripts Identified Through PubMed.

Autor:	Garza MY; Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, Arkansas., Williams T; Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, Arkansas., Ounpraseuth S; Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas., Hu Z; Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas., Lee J; Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas., Snowden J; Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas.; Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas., Walden AC; University of Colorado Denver, Anschutz Medical Campus, Denver, Colorado., Simon AE; Environmental influences on Child Health Outcomes (ECHO) Program, National Institutes of Health (NIH), Rockville, Maryland., Devlin LA; Department of Pediatrics, University of Louisville, Louisville, Kentucky., Young LW; Department of Pediatrics, The Larner College of Medicine at the University of Vermont, Burlington, Vermont., Zozus MN; University of Texas Health Science Center at San Antonio, Joe R. & Teresa Lozano Long School of Medicine, San Antonio, Texas.
Jazyk:	angličtina
Zdroj:	Research square [Res Sq] 2023 Dec 21. Date of Electronic Publication: 2023 Dec 21.
DOI:	10.21203/rs.3.rs-2386986/v2
Abstrakt:	Background: In clinical research, prevention of systematic and random errors of data collected is paramount to ensuring reproducibility of trial results and the safety and efficacy of the resulting interventions. Over the last 40 years, empirical assessments of data accuracy in clinical research have been reported in the literature. Although there have been reports of data error and discrepancy rates in clinical studies, there has been little systematic synthesis of these results. Further, although notable exceptions exist, little evidence exists regarding the relative accuracy of different data processing methods. We aim to address this gap by evaluating error rates for 4 data processing methods. Methods: A systematic review of the literature identified through PubMed was performed to identify studies that evaluated the quality of data obtained through data processing methods typically used in clinical trials: medical record abstraction (MRA), optical scanning, single-data entry, and double-data entry. Quantitative information on data accuracy was abstracted from the manuscripts and pooled. Meta-analysis of single proportions based on the Freeman-Tukey transformation method and the generalized linear mixed model approach were used to derive an overall estimate of error rates across data processing methods used in each study for comparison. Results: A total of 93 papers (published from 1978 to 2008) meeting our inclusion criteria were categorized according to their data processing methods. The accuracy associated with data processing methods varied widely, with error rates ranging from 2 errors per 10,000 fields to 2,784 errors per 10,000 fields. MRA was associated with both high and highly variable error rates, having a pooled error rate of 6.57% (95% CI: 5.51, 7.72). In comparison, the pooled error rates for optical scanning, single-data entry, and double-data entry methods were 0.74% (0.21, 1.60), 0.29% (0.24, 0.35) and 0.14% (0.08, 0.20), respectively. Conclusions: Data processing and cleaning methods may explain a significant amount of the variability in data accuracy. MRA error rates, for example, were high enough to impact decisions made using the data and could necessitate increases in sample sizes to preserve statistical power. Thus, the choice of data processing methods can likely impact process capability and, ultimately, the validity of trial results. Competing Interests: Competing Interests The authors declare that they have no competing interests.
Databáze:	MEDLINE
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