A comparison of error detection rates between the reading aloud method and the double data entry method

Miyuki Kawado, Shiro Hinotsu, Yutaka Matsuyama, Takuhiro Yamaguchi, Shuji Hashimoto, Yasuo Ohashi

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

Data entry and its verification are important steps in the process of data management in clinical studies. In Japan, a kind of visual comparison called the reading aloud (RA) method is often used as an alternative to or in addition to the double data entry (DDE) method. In a typical RA method, one operator reads previously keyed data aloud while looking at a printed sheet or computer screen, and another operator compares the voice with the corresponding data recorded on case report forms (CRFs) to confirm whether the data are the same. We compared the efficiency of the RA method with that of the DDE method in the data management system of the Japanese Registry of Renal Transplantation. Efficiency was evaluated in terms of error detection rate and expended time. Five hundred sixty CRFs were randomly allocated to two operators for single data entry. Two types of DDE and RA methods were performed. Single data entry errors were detected in 358 of 104,720 fields (per-field error rate = 0.34%). Error detection rates were 88.3% for the DDE method performed by a different operator, 69.0% for the DDE method performed by the same operator, 59.5% for the RA method performed by a different operator, and 39.9% for the RA method performed by the same operator. The differences in these rates were significant (p<0.001) between the two verification methods as well as between the types of operator (same or different). The total expended times were 74.8 hours for the DDE method and 57.9 hours for the RA method. These results suggest that in detecting errors of single data entry, the RA method is inferior to the DDE method, while its time cost is lower.

Original languageEnglish
Pages (from-to)560-569
Number of pages10
JournalControlled Clinical Trials
Volume24
Issue number5
DOIs
Publication statusPublished - Oct 2003

Keywords

  • Data management
  • Data verification
  • Double data entry
  • Error detection rates
  • Quality control

ASJC Scopus subject areas

  • Pharmacology

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