Incorporating scannable forms into immunization data collection processes: a mixed-methods study

• Published in: PloS one Vol. 7; no. 12; p. e49627
• Main Authors: Heidebrecht, Christine L, Quach, Susan, Pereira, Jennifer A, Quan, Sherman D, Kolbe, Faron, Finkelstein, Michael, Buckeridge, David L, Kwong, Jeffrey C
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 18.12.2012; Public Library of Science (PLoS)
• Subjects: Analysis; Automatic Data Processing - methods; Automation; Biology; Clients; Clinical decision making; Consent; Data collection; Data Collection - instrumentation; Data Collection - methods; Data processing; Decision making; Demographics; Disease control; Ethics; Family medical history; Feasibility Studies; Health surveillance; Humans; Immunization; Immunization Programs; Infectious diseases; Influenza; Influenza vaccines; Influenza Vaccines - therapeutic use; Influenza, Human - prevention & control; Information management; Information systems; Medical personnel; Medical screening; Medicine; Methods; Mixed methods research; Models, Statistical; Ontario; Pandemics; Pilot Projects; Printing; Public health; Reproducibility of Results; Research Design; Software; Statistics as Topic; Surveys and Questionnaires; Usability; Vaccination; Vaccination - methods; Vaccines; Workflow; Ontario; Ontario Canada; Canada
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0049627

Individual-level immunization data captured electronically can facilitate evidence-based decision-making and planning. Populating individual-level records through manual data entry is time-consuming. An alternative is to use scannable forms, completed at the point of vaccination and subsequently scanned and exported to a database or registry. To explore the suitability of this approach for collecting immunization data, we conducted a feasibility study in two settings in Ontario, Canada. Prior to the 2011-2012 influenza vaccination campaign, we developed a scannable form template and a corresponding database that captured required demographic and clinical data elements. We examined efficiency, data quality, and usability through time observations, record audits, staff interviews, and client surveys. The mean time required to scan and verify forms (62.3 s) was significantly shorter than manual data entry (69.5 s) in one organization, whereas there was no difference (36.6 s vs. 35.4 s) in a second organization. Record audits revealed no differences in data quality between records populated by scanning versus manual data entry. Data processing personnel and immunized clients found the processes involved to be straightforward, while nurses and managers had mixed perceptions regarding the ease and merit of using scannable forms. Printing quality and other factors rendered some forms unscannable, necessitating manual entry. Scannable forms can facilitate efficient data entry, but certain features of the forms, as well as the workflow and infrastructure into which they are incorporated, should be evaluated and adapted if scannable forms are to be a meaningful alternative to manual data entry.