Quality of Data Entry Using Single Entry, Double Entry and Automated Forms Processing–An Example Based on a Study of Patient-Reported Outcomes
Aksel Paulsen,
Søren Overgaard and
Jens Martin Lauritsen
PLOS ONE, 2012, vol. 7, issue 4, 1-6
Abstract:
Background: The clinical and scientific usage of patient-reported outcome measures is increasing in the health services. Often paper forms are used. Manual double entry of data is defined as the definitive gold standard for transferring data to an electronic format, but the process is laborious. Automated forms processing may be an alternative, but further validation is warranted. Methods: 200 patients were randomly selected from a cohort of 5777 patients who had previously answered two different questionnaires. The questionnaires were scanned using an automated forms processing technique, as well as processed by single and double manual data entry, using the EpiData Entry data entry program. The main outcome measure was the proportion of correctly entered numbers at question, form and study level. Results: Manual double-key data entry (error proportion per 1000 fields = 0.046 (95% CI: 0.001–0.258)) performed better than single-key data entry (error proportion per 1000 fields = 0.370 (95% CI: 0.160–0.729), (p = 0.020)). There was no statistical difference between Optical Mark Recognition (error proportion per 1000 fields = 0.046 (95% CI: 0.001–0.258)) and double-key data entry (p = 1.000). With the Intelligent Character Recognition method, there was no statistical difference compared to single-key data entry (error proportion per 1000 fields = 6.734 (95% CI: 0.817–24.113), (p = 0.656)), as well as double-key data entry (error proportion per 1000 fields = 3.367 (95% CI: 0.085–18.616)), (p = 0.319)). Conclusions: Automated forms processing is a valid alternative to double manual data entry for highly structured forms containing only check boxes, numerical codes and no dates. Automated forms processing can be superior to single manual data entry through a data entry program, depending on the method chosen.
Date: 2012
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0035087 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 35087&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0035087
DOI: 10.1371/journal.pone.0035087
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().