Field testing of a simple ODK application for Double Data Entry for community-based healthcare research and disease surveillance

Iwara I. Arikpo, Anthony T. Okoro, Ememobong N. Aquaisua, Martin M. Meremikwu


Data quality plays a vital role in the reliability of data for planning and decision making. The methods used for data collection and entry further heightens the concern for data quality. This paper addresses the techniques of double data entry as an efficient and simplified approach designed to improve the quality of paper-based records. 

Data from implementation of the operations research component of a larger health intervention project in Abia State, South-east, Nigeria, was used for the implementation. Paper-based data were entered independently by two data entry clerks with unique identifiers (IDs) using ODK application. The data was then exported in .csv format into Microsoft Excel application and compared for discordant entries.

The algorithm auto-compared all records by the data entry clerks and returned zero and non-zero values for all concordant and discordant entries respectively. This allowed for easy spot checks on the questionnaires and subsequent correction of the erroneous entries.

Double data entry is efficient, cost effective and robust in achieving high data quality with paper-based records.


data quality; double data entry; data cleaning; paper-based records; data entry errors; paper forms

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References (2017). International Programs - Census and Survey Processing System (CSPro) Documentation. Retrieved from United States Census Bureau:

Coleman Data Solutions. (2014). Advantages of Double Key Data Entry and Verification. Retrieved from Coleman Data Solutions:

EPiData. (2019). EpiData Software. Retrieved from

Google Cloud Platform. (2016). Google Cloud Computing. Retrieved January 2015, from Google Cloud Platform:

Gregg, M. (2008). Field Epidemiology (3rd ed.). New York: Oxford University Press, Inc.

IHSN. (2017). Finalize collection (data entry). Retrieved from International Household Survey Network:

Krishnankutty, B., Bellary, S., Kumar, N., & Moodahadu, L. (2012). Data management in clinical research: An overview. Indian Journal of Pharmacology, 44(2), 168-172. doi:10.4103/0253-7613.93842

Ndume, V., Nkansah-Gyekye, Y., & Ko, J. (2014). Double Entry Data Capture as an Alternative Solution for Quality of E-Health Records. International Journal of Computer Applications, 93(4), 29-35. doi:10.5120/16204-5490

NISR. (2016). Data Processing. Retrieved from Rwanda - Integrated Household Living Conditions Survey 2005-2006:

Open Data Kit. (2017). Open Data Kit: Collect. Retrieved 2017, from OpenDataKit:

OpenClinica. (2017). Entering Data for an Event Into CRFs. Retrieved from OpenClinica Reference Guide:

REDCap. (2019). REDCap. Retrieved from

Scott, J., Thompson, A., Wright-Thomas, D., Xu, X., & Barchard, K. (2008). Data entry methods: Is double data entry the way to go? Poster presented at the Western Psychological Association Annual Convention. Irvine, CA.

Shaffer, T. L., & Groninger, N. P. (1995). Double Data Entry for Novice Users. 20th Annual SAS Users Group International Conference (pp. 111-1116). Orlando, FL: SAS Institute, Inc.



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