title: Automated entry of nosocomial infection surveillance data: use of an optical scanning system.
abstract: Surveillance of nosocomial infections is the foundation of any infection control programme. One of the main obstacles to surveillance is the speed and accuracy of data collection and entry. To overcome this bottleneck, we instituted automated data capture and processing in a number of point-prevalence and continuous nosocomial infection surveillance programmes. The system incorporated a document scanner, form design and processing software (Formic for Windows version 2) and statistical analysis software SPSS (Statistical Products and Service Solutions). After designing the surveillance questionnaire, it was completed by putting an X or a numeral in the the appropriate boxes. Information was collected by the infection control nurse and/or by members of clinical staff depending on the type of surveillance being undertaken. Once the form was completed it was returned and scanned using a document scanner with automatic feed. The software read and evaluated the data on each page. Data from 16741 A4 sides of surveillance questionnaires were automatically processed in a total time of 37.3 hours. This system was found to have a 99.98% accuracy rate and it was estimated to be 22 times quicker than manual entry of data. Infection control teams who are required to carry out surveillance activities should consider automatic data-entry systems. The versatility of such systems makes it possible to achieve extensive surveillance with limited resources.
authors.affiliation: Bacteriology Department, The Royal Hospitals, Belfast.
authors.forename: I M
authors.initials: IM
authors.lastname: Thompson
mesh_terms: D003428:Cross Infection / Q000517:prevention & control*; D003625:Data Collection; D001330:Electronic Data Processing; D006751:Hospital Information Systems; D006785:Hospitals, University; D006801:Humans; D017053:Infection Control / Q000379:methods*; D009660:Northern Ireland; D018571:Sentinel Surveillance; D012984:Software