Field Testing of a Simple Odk Application for Double Data Entry for Community-Based Healthcare Research and Disease Surveillance

Abstract

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.