Design and Implementation of a Standardised Clinical Decision Support Algorithm for Fever

Abstract

This study aims to design a decision support tool to assist in providing quality treatment that is consistent with World Health Organization (WHO) and Nigerian National guidelines. The system is designed to allow clinicians to administer care within their competent level working from one algorithm. The system will help them to identify emergencies associated with fever symptoms and to recommend stabilisation actions before a referral is made. This new system allows structured assessment of patients who should receive optimal care and improved data transmission to the next caregiver. In this study, we used an explanatory approach, starting with the quantitative data collection phase which is the administration of questionnaires and Pre and Post questionnaires followed by qualitative data from focus group discussions over the clinician experience using the Clinical Decision Support System (CDSS). Focus group discussions were performed to authenticate the quantitative data to have a more holistic view of the CDSS. Using elements of the decision support system together with the clinician's decision showed that the clinicians felt that they worked more systematically and communicated more effectively with others. They felt more professional when using the decision support system. 73% of clinicians reported using CDSS in almost every consultation and 93% used the CDSS in the majority of their consultations during the three-month testing period. The mean total test score before the CDSS was 2.5 and this increased by the end of the test period to a mean score of 9.6, an improvement of 74.4%. The results of this study showed that with the help of a decision support system, patients were properly identified and stabilised before they were referred, and the clinicians stayed on their competency level. It allowed caregivers to interact professionally without bias. However, the decision support system requires more extensive testing to enhance the evidence base relating to the vital parameters and the use of the decision support system.