5. Conclusions
Nurses often encounter problems in triage-level decision making on diagnosis. The use of a CDSS is a well-recognized solution to increasing the quality and efficiency of care. The correspondence between CDSS design and guidelines and clinicians’ opinions is of utmost importance because this reduces over-triage and under-triage cases and improves safety. Conducting interviews with users and clinicians early in the development process informs the identification of design requirements and provides a context for how a CDSS will be most useful to providers. Insight into end-users’ cognitive processes can facilitate the design of CDSS systems with promising usability. Analyzing CDSSs before deploying these systems for real-world application potentially saves money, time, and effort during implementation. Tool developers are responsible for ensuring the safety, usability, and usefulness of such systems.
The essence of this study lies in its combination of FLC and RBR, which can improve the triage outcomes and will be useful in medical areas. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner. We expect the use of this method to minimize the design iterations of the developed CDSS, which combines two or more methodologies. The measurements obtained in this work are consistent with those reported in other related studies. The developed system proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines, and improved the quality measures for accuracy and documentation in the triage process. We designed and evaluated the CDSS on the basis of ESI triage guidelines and found that the designed system effectively determines the triage level required for patients. The methods put forward in this work can be applied to other clinical decision support systems and settings, and we hope that further exploration of the system will provide improved results.
