RightRX: Decision Support for the Optimization of Prescribing Practice

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KSL-95-22 +  redirect page

RightRX: Decision Support for the Optimization of Prescribing Practice +  Has identifier

RightRX: Decision Support for the Optimization of Prescribing Practice +  Ksl tr id

RightRX: Decision Support for the Optimization of Prescribing Practice +  Number

RightRX: Decision Support for the Optimization of Prescribing Practice

Bibtype  techreport

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

Title  RightRX: Decision Support for the Optimization of Prescribing Practice

Year  1995

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.

Note  Medical Computer Science

Author  Merav Harris and Ramon M. Felciano and Jay Strain and Thomas C. Rindfleisch and Edward H. Shortliffe and Bo E. H. Saxberg +

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  RightRX: Decision Support for the Optimization of Prescribing Practice +

Institution  Knowledge Systems, AI Laboratory +

Ksl tr id  RightRX: Decision Support for the Optimization of Prescribing Practice +

Month  February +

Number  RightRX: Decision Support for the Optimization of Prescribing Practice +

Process note  NO +

Categories  KSL Technical Report +, Publication +, Technical Report +

 

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