[Paper Review] A Secure Intelligent Decision Support System for Prescribing Medication

Adebayo Omotosho, Justice Emuoyibofarhe|arXiv (Cornell University)|Mar 27, 2015

Electronic Health Records Systems7 references3 citations

TL;DR

This paper proposes a secure, intelligent e-prescription system that integrates a drug knowledge base and inference engine to reduce prescribing errors, enhanced by multifactor authentication using passwords and biometrics. Built with C# and SQL Server, the system improves patient safety and privacy over paper prescriptions, demonstrating a functional prototype with strong security and clinical decision support features.

ABSTRACT

The process of electronic approach to writing and sending medical prescription promises to improve patient safety, health outcomes, maintaining patients privacy, promoting clinician acceptance and prescription security when compared with the customary paper method. Traditionally, medical prescriptions are typically handwritten or printed on paper and hand-delivered to pharmacists. Paper-based medical prescriptions are generating major concerns as the incidences of prescription errors have been increasing and causing minor to serious problems to patients, including deaths. In this paper, intelligent eprescription model that comprises a knowledge base of drug details and an inference engine that can help in decision making when writing a prescription was developed. The research implements the e-prescription model with multifactor authentication techniques which comprises password and biometric technology. Microsoft Visual Studio 2008, using C-Sharp programming language, and Microsoft SQL Server 2005 database were employed in developing the systems front end and back end respectively. This work implements a knowledge base to the e-prescription system which has added intelligence for validating doctors prescription and also added security feature to the e-prescription system.

Motivation & Objective

• To address rising prescription errors from paper-based systems by developing a secure electronic alternative.
• To improve patient safety and privacy through intelligent decision support in e-prescriptions.
• To integrate multifactor authentication (password and biometric) to secure the prescribing process.
• To develop a functional prototype using C# and SQL Server for real-world clinical deployment.

Proposed method

• The system employs a knowledge base containing comprehensive drug details for clinical validation.
• An inference engine evaluates prescriptions for drug interactions, contraindications, and dosage appropriateness.
• Multifactor authentication is implemented using password and biometric (e.g., fingerprint) verification.
• The front-end is developed using Microsoft Visual Studio 2008 and C#, while the back-end uses Microsoft SQL Server 2005.
• The system architecture ensures data confidentiality and access control through layered authentication.
• The model is tested as a working prototype to validate functionality and security in a simulated clinical environment.

Experimental results

Research questions

• RQ1 How can an intelligent e-prescription system reduce medication errors compared to traditional paper prescriptions?
• RQ2 What role does multifactor authentication play in securing the electronic prescribing process?
• RQ3 Can a knowledge base and inference engine effectively support clinicians in safe medication decision-making?
• RQ4 How does integrating biometrics improve the security and trustworthiness of e-prescriptions?
• RQ5 What is the feasibility of implementing a secure, intelligent e-prescription system using standard software tools?

Key findings

• The proposed system successfully reduces the risk of prescription errors through automated validation using a comprehensive drug knowledge base.
• Multifactor authentication significantly enhances system security by preventing unauthorized access.
• The integration of biometric verification adds a strong layer of identity assurance to the prescribing process.
• The prototype demonstrates functional viability using C# and SQL Server, supporting real-time decision support.
• The system improves patient privacy and data integrity compared to paper-based methods.
• The research contributes a working model that combines clinical intelligence with robust access control for e-prescribing.