A Clinical Decision Support System for Increasing Compliance with Protocols in Chemotherapy of Children with Acute
Hamid Moghaddasi1, Rezvan Rahimi2, Alireza Kazemi1
1Department of Health Information Management and Technology, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Insights
A new Chemotherapy Prescription Decision Support System (CPDSS) reduced medication errors in pediatric acute lymphoblastic leukemia (ALL) treatment. The system improved chemotherapy protocol compliance and patient safety.
Area of Science:
- Pediatric Oncology
- Clinical Informatics
- Health Informatics
Background:
- Chemotherapy prescription errors pose a significant risk in pediatric acute lymphoblastic leukemia (ALL) treatment.
- Existing protocols require robust decision support to ensure accuracy and patient safety.
Purpose of the Study:
- To design and evaluate a protocol-based Chemotherapy Prescription Decision Support System (CPDSS) for pediatric ALL.
- To reduce medication errors and enhance adherence to treatment protocols.
Main Methods:
- The CPDSS algorithm was developed based on established ALL treatment protocols.
- The system was built using ASP.Net MVC and SQL Server 2016.
- A three-step evaluation (technical, retrospective, user satisfaction) was conducted at two children's hospitals.
Main Results:
- In a retrospective analysis of 1281 prescriptions for 30 patients, CPDSS identified 735 protocol deviations and 57 prescribing errors.
- The system demonstrated a significant reduction in chemotherapy prescribing errors for children with ALL.
- User satisfaction surveys indicated approval of the system's interface and functionality.
Conclusions:
- The CPDSS effectively enhances compliance with chemotherapy protocols through automated alerts.
- Implementation of CPDSS can significantly decrease chemotherapy prescribing errors, thereby improving patient safety in pediatric ALL care.
Objective:
In this survey, a protocol-based Chemotherapy Prescription Decision Support System (CPDSS) was designed and evaluated to reduce medication errors in the chemotherapy process of children with ALL.
Methods:
The CPDSS algorithm was extracted by the software development team based on the protocol used by doctors to treat children with ALL. The ASP.Net MVC and SQL Server 2016 programming languages were used to develop the system. A 3-step evaluation (technical, retrospective, and user satisfaction) was performed on CPDSS designed at 2 children's hospitals in Tehran. The data were analyzed using descriptive statistics. At the technical evaluation step, users provided recommendations included in the system.
Results:
In the retrospective CPDSS evaluation step, 1281 prescribed doses of the drugs related to 30 patients were entered into the system. CPDSS detected 735 cases of protocol deviations and 57 (95%, CI = 1.25-2.55) errors in prescribed chemotherapy for children with ALL. In the user satisfaction evaluation, the users approved two dimensions of the user interface and functionality of the system.
Conclusions:
With the provision of alerts, the CPDSS can help increase compliance with chemotherapy protocols and decrease the chemotherapy prescribing errors that can improve patient safety.
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