The Use of a Clinical Decision Support System to Identify Potential Drug-Related Problems: Focused on the Types of Alerts for Pediatric Patients
2022 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Student thesis
Abstract [en]
Background: Sweden is among the top countries with the greatest use of e-prescriptions at a national level. A clinical decision support system called Electronic Expert Support (EES) is available at all pharmacies in Sweden to examine e-prescriptions in connection with the dispensing to prevent drug related problems (DRPs). DRPs result in patient suffering and substantial costs for society. The types of alerts generated for pediatric patients at Swedish pharmacies using EES-system has not been studied before, to the best of our knowledge. Aim: The aim of this research is to study the use of EES at pharmacies in Sweden for the pediatric population (ages 0-12 years), by describing what types of alerts for potential DRPs are generated, how they are handled and how the use of EES has changed over time. Method: Data on the number and categories of EES analyses, alerts, and resolved alerts was provided by the Swedish eHealth Agency. Results: The study shows that the use of EES has increased. The most common type of generated alert for a potential DRP among pediatric was high dose pediatric (30,3% of all alerts generated). The most common type of alert for a potential DRP that was resolved among pediatrics was therapy duplication (45,8%). The most common reason for closing an alert was dialogue with patient for verification of the treatment (66,3% of all closed alerts). Conclusion: Knowledge of which type of alerts that are the most common may contribute to increased prescriber awareness of important potential DRPs. Future studies should investigate the clinical relevance of the generated alerts for the pediatric population.
Place, publisher, year, edition, pages
2022. , p. 36
Keywords [en]
CDSS, ESS, Dispensing, Pharmacist, Alerts, Sweden, Pediatric
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-478249OAI: oai:DiVA.org:uu-478249DiVA, id: diva2:1675162
Subject / course
Pharmacy
Educational program
Master of Science Programme in Pharmacy
Supervisors
Examiners
2023-01-172022-06-222023-01-17Bibliographically approved