Towards a More Effective Hospital: Helping Health Professionals to Learn from their Own Practice by Developing an Easy to use Clinical Processes Querying Language

Application of complex socio-technical systems theory to optimization of clinical processes in hospitals highlights the importance of the acceptance and promotion of responsible autonomy among health professionals. Therefore the independent ability for clinicians to search for answers to questions which are outside the scope of pre-made reports is important. However, the ad-hoc data querying process is slow and error prone due to inability of health professionals to access data directly without involving IT experts. The problem lies in the complexity of means used to query data. We propose a new natural language- and star ontology-based ad-hoc data querying approach which reduces the steep learning curve required to be able to query data. The proposed approach would significantly decrease the time needed to master the ad-hoc data querying and to obtain direct access to data by health professionals.