Development and Knowledge Translation of Decision-Support Tools

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The main goal is to continue to develop information technology systems that can provide knowledge that enhances decision-making by users for the various problems under study. The decision-support tools use a systems engineering approach, combined with web services, to provide relevant information in an easy and intuitive manner; this phase of our research program focusses on delivering knowledge to physicians and patients/parents in a perinatal care context. It is important to note that the methods developed in this research program can be applied to non-clinical databases like weather and climate measurements to predict severe weather patterns, or changes to the stock market, and help classify outcomes for non-medical applications. The major part of this research resides in the domain of systems, computer, and software engineering; the evaluation of the results (usability studies) use software engineering methods. The application of these systems to a medical environment represents around 10 % of the research proposed. The objectives are to develop prediction tools to identify the risk of premature birth in pregnant women, delivery mode (vaginal or Caesarian), and Apgar Score (state of infant at birth); and improve our risk prediction models for intensive care infants regarding mortality and a number of complications, using real-time data collected from up to twenty infants simultaneously. No currently available approaches predict these outcomes. We plan to identify the variables that best predict the various outcomes being studied as well as incorporate warnings and alarms when notable changes occur. The next step will be to present the information to physicians and parents of infants in an easy, secure manner using web services, which can be accessed locally or from remote locations, by several users. The characterisation of risks and the comprehensive obstetrical and perinatal information need to be integrated in an original manner to provide a useful tool for physicians and patients. The risk estimation results, along with response to treatments and patient prognosis, will offer a unique clinical tool not available in current research or commercial systems. There is a considerable level of interest by physicians for our approaches. The research is entirely novel and the team has considerable and complementary expertise: Dr Bariciak, neonatologist, for clinical aspects; Dr Gilchrist, a Computer Scientist, for software questions; Dr Frize, for biomedical engineering and research methodology. The estimation tools will help to intervene earlier and improve patient outcomes. The principal applicant has trained more than fifty highly qualified personnel over twenty years; this application will expose research students to a multidisciplinary environment in an area of great demand for Canada. All former research students found relevant employment after degree completion.  ******