RightRX: Decision Support for the Optimization of Prescribing Practice

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Citation: Merav Harris and Ramon M. Felciano and Jay Strain and Thomas C. Rindfleisch and Edward H. Shortliffe and Bo E. H. Saxberg. (1995) RightRX: Decision Support for the Optimization of Prescribing Practice. In KSL-95-22, February,1995.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author Merav Harris and Ramon M. Felciano and Jay Strain and Thomas C. Rindfleisch and Edward H. Shortliffe and Bo E. H. Saxberg
title RightRX: Decision Support for the Optimization of Prescribing Practice
number KSL-95-22
institution Knowledge Systems, AI Laboratory
year 1995
month February
Bibtex more
note Medical Computer Science
Access Paper
abstract Motivation A growing number of hospitals and managed care organizations are utilizing formularies to promote cost containment. Experience to date suggests that the use of formularies can result in a reduction of pharmacy costs, but these savings may be offset by related increases in other charges. The optimization of formulary use may lie in prescribing practices which balance population-based guidelines with individual patient needs. RightRX is designed to assist clinicians in striking that balance.Overview Eli Lilly and Company has initiated a collaboration with the Stanford Medical School to evaluate the utility and frame the character of a decision support tool for rational drug selection. In demonstrating patient-specific cost and quality tradeoffs among alternative pharmaceutical treatments, RightRX is intended to materially improve the quality of care. In automating the drug prescription process and providing online access to patient and drug information, the tool engenders physician acceptance. A paper prototype has been developed to profile physician work flow, to characterize information needs, to identify key factors affecting acceptance, and to evaluate proposed features. The use of a rapid prototyping has allowed the developers to efficiently identify fundamental issues in the early design process.

KSL Technical Report ID: KSL-95-22
Facts about RightRX: Decision Support for the Optimization of Prescribing PracticeRDF feed
Abstract Motivation A growing number of hospitals a … Motivation A growing number of hospitals and managed care organizations are utilizing formularies to promote cost containment. Experience to date suggests that the use of formularies can result in a reduction of pharmacy costs, but these savings may be offset by related increases in other charges. The optimization of formulary use may lie in prescribing practices which balance population-based guidelines with individual patient needs. RightRX is designed to assist clinicians in striking that balance.Overview Eli Lilly and Company has initiated a collaboration with the Stanford Medical School to evaluate the utility and frame the character of a decision support tool for rational drug selection. In demonstrating patient-specific cost and quality tradeoffs among alternative pharmaceutical treatments, RightRX is intended to materially improve the quality of care. In automating the drug prescription process and providing online access to patient and drug information, the tool engenders physician acceptance. A paper prototype has been developed to profile physician work flow, to characterize information needs, to identify key factors affecting acceptance, and to evaluate proposed features. The use of a rapid prototyping has allowed the developers to efficiently identify fundamental issues in the early design process. mental issues in the early design process.
Author Merav Harris and Ramon M. Felciano and Jay Strain and Thomas C. Rindfleisch and Edward H. Shortliffe and Bo E. H. Saxberg  +
Bibtype techreport  +
Has author Merav Harris and Ramon M. Felciano and Jay Strain and Thomas C. Rindfleisch and Edward H. Shortliffe and Bo E. H. Saxberg  +
Has identifier KSL-95-22  +
Has publishing details February,1995  +
Has title RightRX: Decision Support for the Optimization of Prescribing Practice  +
Has where published KSL-95-22  +
Has year 1995  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-95-22  +
Month February  +
Note Medical Computer Science
Number KSL-95-22  +
Process note NO  +
Title RightRX: Decision Support for the Optimization of Prescribing Practice  +
Year 1995  +
Retrieved from "http://tw.rpi.edu/wiki/RightRX:_Decision_Support_for_the_Optimization_of_Prescribing_Practice"
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