The use of personal computers in hospital infection control

Implementation of an interactive computer-assisted infection monitoring program at the bedside

A new computer-assisted infection monitoring (CAI) software program has been developed for use in an intensive-care unit (ICU). By means of an interactive dialogue with physicians at the bedside, infection diagnoses and therapeutic decisions were recorded prospectively during a 3-month test period. By linking epidemiological data with information about therapeutic decisions, CAI could assess the quality of the therapeutic decisions. Antibiotics chosen empirically before the availability of any culture results, matched the antibiotic susceptibility patterns of the subsequently identified pathogens in 74% of the cases. Therapy chosen in collaboration with the computer after the pathogen was known, but before sensitivity results were available, corresponded with the eventual antibiograms of the microorganisms in 90% of the cases. Data analysis by CAI allowed us to assess critically the diagnostic and therapeutic habits in our ICU. Using the query-by-example method, CAI automatically calculated device-associated infection rates.

Survey of infection in hospitals: use of an automated data entry system

This paper describes an automated approach to data entry which substantially reduced time and effort involved in infection control surveillance within a large teaching hospital. As part of our involvement in the Second National Prevalence Survey of infection in hospitals, a hospital-wide prevalence survey of infection was carried out during January and February 1994. We simultaneously entered the results manually into an "in-house' database to enable analysis of data within the hospital. The prevalence survey was repeated during January and February 1995 using a paper questionnaire designed "in-house' and read automatically using a sheet-fed optical scanner. There was a substantial 17-fold decrease in data entry time using this method compared with manual entry. The new approach enabled more rapid analysis of surveillance data and feedback to hospital staff. If hospital clinical data is collected routinely in a format suitable for scanning, then potentially useful data could be rendered accessible. Automated data entry systems are invaluable in reducing time spent on data input and should be considered by all those involved in surveillance and audit. There would appear to be little hope in the near future of having all patient clinical data in an electronic format so that the prospects for scanning initiatives are excellent.