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. 2019 Aug 22;12(1):537.
doi: 10.1186/s13104-019-4574-8.

Analysis of erroneous data entries in paper based and electronic data collection

Benedikt Ley  1 , Komal Raj Rijal  2 , Jutta Marfurt  3 , Naba Raj Adhikari  2 , Megha Raj Banjara  2 , Upendra Thapa Shrestha  2 , Kamala Thriemer  3 , Ric N Price  3   4   5 , Prakash Ghimire  2
Affiliations

Analysis of erroneous data entries in paper based and electronic data collection

Benedikt Ley et al. BMC Res Notes. .

Abstract

Objective: Electronic data collection (EDC) has become a suitable alternative to paper based data collection (PBDC) in biomedical research even in resource poor settings. During a survey in Nepal, data were collected using both systems and data entry errors compared between both methods. Collected data were checked for completeness, values outside of realistic ranges, internal logic and date variables for reasonable time frames. Variables were grouped into 5 categories and the number of discordant entries were compared between both systems, overall and per variable category.

Results: Data from 52 variables collected from 358 participants were available. Discrepancies between both data sets were found in 12.6% of all entries (2352/18,616). Differences between data points were identified in 18.0% (643/3580) of continuous variables, 15.8% of time variables (113/716), 13.0% of date variables (140/1074), 12.0% of text variables (86/716), and 10.9% of categorical variables (1370/12,530). Overall 64% (1499/2352) of all discrepancies were due to data omissions, 76.6% (1148/1499) of missing entries were among categorical data. Omissions in PBDC (n = 1002) were twice as frequent as in EDC (n = 497, p < 0.001). Data omissions, specifically among categorical variables were identified as the greatest source of error. If designed accordingly, EDC can address this short fall effectively.

Keywords: AKVO; Electronic data entry; Epidata; Paper based data entry.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Proportion of discrepant results per variable and variable category. Red highlighted variables are excluded from analysis
Fig. 2
Fig. 2
Proportion of discrepant results per variable sorted in sequence of data collection. Variables left of the dotted line are collected with the patient, variables right of the dotted line are collected in the laboratory. Red highlighted variables are excluded from analysis
See this image and copyright information in PMC

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