Reference: Harris, M. Z.; Felciano, R. M.; Strain, J. J.; Rindfleisch, T. C.; Shortliffe, E. H.; & Saxberg, B. E. H. RightRX: Decision Support for the Optimization of Prescribing Practice. Knowledge Systems Laboratory, Medical Computer Science, February, 1995.
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.