Background: As a result of the disease’s high prevalence, chronic kidney disease (CKD) has become a global public health problem. A clinical decision support system that integrates with computer-interpretable guidelines (CIGs) should improve clinical outcomes and help to ensure patient safety. Objectives: The openEHR guideline definition language (GDL) is a formal language used to represent CIGs. This study explores the feasibility of using a GDL approach for CKD; it also attempts to identify any potential gaps between the ideal concept and reality. Methods: Using the Kidney Disease Improving Global Outcomes (KDIGO) anemia guideline as material, we designed a development workflow in order to establish a series of GDL guidelines. Focus group discussions were conducted in order to identify important issues related to GDL implementation. Results: Ten GDL guidelines and 37 archetypes were established using the KDIGO guideline document. For the focus group discussions, 16 clinicians and 22 IT experts were recruited and their perceptions, opinions and attitudes towards the GDL approach were explored. Both groups provided positive feedback regarding the GDL approach, but raised various concerns about GDL implementation. Conclusions: Based on the findings of this study, we identified some potential gaps that might exist during implementation between the GDL concept and reality. Three directions remain to be investigated in the future. Two of them are related to the openEHR GDL approach. Firstly, there is a need for the editing tool to be made more sophisticated. Secondly, there needs to be integration of the present approach into non openEHR-based hospital information systems. The last direction focuses on the applicability of guidelines and involves developing a method to resolve any conflicts that occur with insurance payment regulations.
- Chronic kidney disease
- Computer-interpretable guideline
- OpenEHR guideline definition language
ASJC Scopus subject areas
- Health Informatics
- Advanced and Specialised Nursing
- Health Information Management