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

Benedikt Ley, Komal Raj Rijal, Jutta Marfurt, Naba Raj Adhikari, Megha Raj Banjara, Upendra Thapa Shrestha, Kamala Thriemer, Ric N. Price, Prakash Ghimire

Research output: Contribution to journalArticleResearchpeer-review

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.

Original languageEnglish
Article number537
Pages (from-to)1-6
Number of pages6
JournalBMC Research Notes
Volume12
Issue number1
DOIs
Publication statusPublished - 22 Aug 2019

Fingerprint

Data acquisition
Nepal
Information Systems
Biomedical Research
Research Design

Cite this

Ley, B., Rijal, K. R., Marfurt, J., Adhikari, N. R., Banjara, M. R., Shrestha, U. T., ... Ghimire, P. (2019). Analysis of erroneous data entries in paper based and electronic data collection. BMC Research Notes, 12(1), 1-6. [537]. https://doi.org/10.1186/s13104-019-4574-8
Ley, Benedikt ; Rijal, Komal Raj ; Marfurt, Jutta ; Adhikari, Naba Raj ; Banjara, Megha Raj ; Shrestha, Upendra Thapa ; Thriemer, Kamala ; Price, Ric N. ; Ghimire, Prakash. / Analysis of erroneous data entries in paper based and electronic data collection. In: BMC Research Notes. 2019 ; Vol. 12, No. 1. pp. 1-6.
@article{a3fe84d561fe4996b15cb745a18922f1,
title = "Analysis of erroneous data entries in paper based and electronic data collection",
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",
author = "Benedikt Ley and Rijal, {Komal Raj} and Jutta Marfurt and Adhikari, {Naba Raj} and Banjara, {Megha Raj} and Shrestha, {Upendra Thapa} and Kamala Thriemer and Price, {Ric N.} and Prakash Ghimire",
year = "2019",
month = "8",
day = "22",
doi = "10.1186/s13104-019-4574-8",
language = "English",
volume = "12",
pages = "1--6",
journal = "BMC Research Notes",
issn = "1756-0500",
publisher = "BioMed Central",
number = "1",

}

Analysis of erroneous data entries in paper based and electronic data collection. / Ley, Benedikt; Rijal, Komal Raj; Marfurt, Jutta; Adhikari, Naba Raj; Banjara, Megha Raj; Shrestha, Upendra Thapa; Thriemer, Kamala; Price, Ric N.; Ghimire, Prakash.

In: BMC Research Notes, Vol. 12, No. 1, 537, 22.08.2019, p. 1-6.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Analysis of erroneous data entries in paper based and electronic data collection

AU - Ley, Benedikt

AU - Rijal, Komal Raj

AU - Marfurt, Jutta

AU - Adhikari, Naba Raj

AU - Banjara, Megha Raj

AU - Shrestha, Upendra Thapa

AU - Thriemer, Kamala

AU - Price, Ric N.

AU - Ghimire, Prakash

PY - 2019/8/22

Y1 - 2019/8/22

N2 - 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.

AB - 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.

KW - AKVO

KW - Electronic data entry

KW - Epidata

KW - Paper based data entry

UR - http://www.scopus.com/inward/record.url?scp=85071230377&partnerID=8YFLogxK

U2 - 10.1186/s13104-019-4574-8

DO - 10.1186/s13104-019-4574-8

M3 - Article

VL - 12

SP - 1

EP - 6

JO - BMC Research Notes

JF - BMC Research Notes

SN - 1756-0500

IS - 1

M1 - 537

ER -