INTELLIGENT KNOWLEDGE BASE FOR CANCER PAIN TREATMENT

描述：此快速通道SBIR赠款应用程序建议确定 建立计算机辅助决策支持系统的可行性研究 癌症疼痛治疗。调查者之前的NCI研究开发了 并测试了一种基于AHCPR指南的药物算法方法 用于癌症疼痛管理，在门诊环境中。药理学 算法利用有效性与毒性的决策点来漏斗 将综合评估数据纳入治疗建议流程图。 根据严重程度，重新评估参数指导后续护理 患者的疼痛强度随机分配到算法过程中 一项对照试验。第一阶段项目将转换评估 将“纸和笔”算法的组件整合到医疗工作流程中 软件应用程序。工作流中嵌入的评估元素 将根据原始数据集的实际数据集进行数据建模 算法研究。工作流的可行性和功能限制 将对模型进行评估。长期目标将是利用 优化的评估工作流应用程序，以启动快速原型 将完整的算法转化为基于知识的决策支持系统。 建议的商业应用：不可用

DESCRIPTION: This FAST-TRACK SBIR grant application proposes to determine the feasibility of building a computerized decision support system for cancer pain treatment. The investigator's previous NCI research developed and tested a pharmacologic algorithm method, based on the AHCPR Guideline for Cancer Pain Management, in the outpatient setting. The pharmacologic algorithm utilizes an efficacy versus toxicity decision point to funnel comprehensive assessment data into a treatment recommendations flow chart. Re-assessment parameters guide follow-up care dependent upon the severity of pain intensity for patients randomized to the algorithm process during a controlled trial. The Phase I project will convert the assessment components of the "paper and pencil" algorithm into a health care workflow software application. The assessment elements, embedded in the workflow will undergo data modeling against actual datasets from the original algorithm study. Feasibility and feature limitations to the workflow model will be assessed. The long term objective will be to utilize the optimized assessment workflow application to launch a rapid prototyping of the complete algorithm into a knowledge-based decision support system. PROPOSED COMMERCIAL APPLICATION: NOT AVAILABLE