Novel Approaches for Identifying, Tracking and Preventing Technology-Induced Error

In Canada healthcare is being modernized and transformed through a range of new healthcare information technologies and systems. Applications of information systems such as electronic health records (EHRs), electronic medical decision support and an increasing range of mobile health applications promise to transform and improve healthcare and increase patient safety. However, although such technology has huge potential benefits, research has shown that if not designed, tested and implemented properly such technology also has the potential to introduce new types of error – i.e. technology-induced error that arises during the complex interaction of health information systems with healthcare workers under the varied complex situations and environments in which healthcare IT is deployed. In this proposal AE Informatics will be able to extend its pioneering research in this area in developing new and novel methods for detecting, classifying and mitigating technology-induced error in healthcare IT. The cluster of projects include work in improving the safety of key healthcare processes for ensuring medication safety and correctness of health data, developing ways of classifying errors that inadvertently result from use of healthcare information technologies and developing an automated approach to detecting errors that may arise through the analysis of transmission of healthcare data.

Faculty Supervisor:

Dr. Alex Kuo

Student:

Helen Monkman

Partner:

AE Informatics

Discipline:

Computer science

Sector:

Life sciences

University:

University of Victoria