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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

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Published on: December 11, 2016

A comprehensive e-prescribing model to allow representing, comparing, and analyzing available systems.

S Marceglia¹, L Mazzola, S Bonacina

¹e-Health Lab, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy. sara.marceglia@polimi.it

Methods of Information in Medicine

|April 18, 2013

Summary

This summary is machine-generated.

This study introduces a comprehensive model for electronic prescribing (ePrescribing) to analyze and compare existing systems. The model aids in designing new ePrescribing systems for national healthcare, improving care quality and access.

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Area of Science:

Health Informatics
Digital Health
Healthcare Management

Background:

Electronic prescribing (ePrescribing) systems are vital for eHealth but exhibit significant heterogeneity in functionality and performance.
Existing ePrescribing systems vary widely, posing challenges for standardization and interoperability within healthcare.

Purpose of the Study:

To propose a comprehensive model for the ePrescribing process.
To enable analysis, comparison, and design of advanced ePrescribing systems for National Healthcare Systems.

Main Methods:

A literature review identified six core phases: Assign, Transmit, Dispense, Administer, Monitor, and Analysis Decision.
Each phase generates digital objects with formal properties crucial for data integrity and process flow.
The model links the formal properties of digital objects to benefits in governance, drug surveillance, and care quality.

Main Results:

The model-based implementation of ePrescribing phases impacts care quality, access, and effectiveness.
Benefits are observed at individual, territorial, and governmental levels.
While not including cost evaluation, the identified benefits support cost-benefit analyses.

Conclusions:

A standardized ePrescribing model enhances the quality, access, and effectiveness of care delivery.
The proposed model provides a foundation for evaluating and improving diverse ePrescribing systems.
Further analysis can leverage the model's benefits for cost-effectiveness studies in healthcare.