title: Quality of data entry using single entry, double entry and automated forms processing--an example based on a study of patient-reported outcomes.
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.
authors.affiliation: Department of Orthopaedic Surgery and Traumatology, Odense University Hospital, Odense, Funen, Denmark. Aksel.Paulsen@ouh.regionsyddanmark.dk
authors.forename: Aksel
authors.initials: A
authors.lastname: Paulsen
authors.forename: Søren
authors.initials: S
authors.lastname: Overgaard
authors.forename: Jens Martin
authors.initials: JM
authors.lastname: Lauritsen
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D001330:Electronic Data Processing / Q000458:organization & administration / Q000706:statistics & numerical data*; D005260:Female; D005568:Forms and Records Control; D006801:Humans; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated; D011996:Records; D011795:Surveys and Questionnaires / Q000706:statistics & numerical data*