OncoPath: Intelligent Clinical Pathway Decision Support Tool for Pre-Authorization Documentation in Non-Small Cell Lung Cancer Treatment

工程摘要 在现实世界的临床环境中，忙碌的肿瘤学家缺乏时间在所有可行的情况下进行调查性病例分析。 治疗方案、经常更新的治疗指南和付款人的具体要求。这导致了亚- 最佳决策、不完整的预授权（pre-auth）文档以及 报销总体而言，这增加了肿瘤学的医疗成本和支付赤字。例如，预- 据估计，认证效率低下每年使每位医生的医疗保健成本增加83，000美元，即11亿美元 每年仅在肿瘤学上。为了制定治疗计划，肿瘤学家参考了美国国家综合癌症研究所（National Comprehensive Cancer） 网络指南®（NCCN）、其他临床学会标准和付款人特定要求 患者的病史、肿瘤特征和治疗阶段。最常用的肿瘤学之一 肿瘤学家参考的治疗指南和大多数付款人遵守的是国家综合 癌症网络（NCCN）指南®。这些指导方针以跨越100页的模式呈现。 技术驱动的临床决策支持（CDS）系统可用于解决以下需求： 简化治疗指南分析、付款人规则审查和治疗决策文件， 降低了肿瘤学实践的总体成本。该提案的重点是开发一个创新的和第一的- 一种用于CDS的技术，使用非小细胞肺癌（NSCLC）作为初始测试案例，并结合 NCCN指南、一般付款人特定要求和患者数据叠加，以计算可行的治疗 途径。该小组提出以下第一阶段具体目标： 目标1：开发基于图形的NSCLC NCCN治疗数学模型和可视化表示 具有通用付款人特定要求的准则。开发基于图形的可视化交互式 NCCN Guidelines®。将指导方针建模为可视图（节点和弧）将使 肿瘤学家，以确定最佳的治疗途径，为他们的病人。 目标2：构建一个分析引擎，突出显示具有可行治疗选项的NCCN图形模型 考虑到病人的病例细节和共同的付款人要求。使用开源工具创建 与肿瘤学家和健康计划专家一起合成患者数据和常见的支付者约束。开发一个 图形遍历算法库，用于在可视用户界面中覆盖和可视化患者数据。 目标3：使用OncoPath执行、验证和测试概念验证CDS工作流程。运行完整的 端到端CDS工作流程，记录患者详细信息、NCCN指南、付款人要求和 使用Aim 2中生成的合成患者数据和付款人约束进行治疗决策。 OncoPath将为治疗决策和记录提供一种高效、肿瘤学家友好的方法， 从而使患者受益并降低肿瘤学成本。第二阶段将部署一个实时的 OncoPath在单一胸部肿瘤学实践中用于集成工作流程和节省时间的验证。

Project Abstract In a real-world clinical setting, busy oncologists lack the time for investigative case analysis across all feasible treatment options, frequently updated treatment guidelines and payor specific requirements. This results in sub- optimal decision making, incomplete pre-authorization (pre-auth) documentation, and problems with reimbursement. Overall, this increases medical costs and payment deficits within oncology. For example, pre- auth inefficiencies are estimated to add $83,000 a year per physician to healthcare costs, which is $1.1 billion annually in oncology alone. To devise a treatment plan, oncologists reference National Comprehensive Cancer Network Guidelines® (NCCN), other clinical society standards, and payor specific requirements in the context of a patient’s medical history, tumor characteristics, and phase of treatment. One of the most used oncology treatment guidelines referenced by oncologists and adhered to by most payors is the National Comprehensive Cancer Network (NCCN) Guidelines®. These guidelines are presented as a schema that span 100s of pages. A technology driven clinical decision support (CDS) system could be employed to address the need to streamline treatment guideline analysis, payor rules review, and treatment decision documentation for reduced overall cost to oncology practices. This proposal focuses on developing an innovative and first-of- a-kind technology for CDS using non-small cell lung cancer (NSCLC) as the initial test case and incorporating NCCN Guidelines, general payor specific requirements and patient data overlaid to compute feasible treatment pathways. The team proposes the following Phase I Specific Aims: Aim 1: Develop a graph-based mathematical model and visual presentation of NSCLC NCCN treatment guidelines with generalized payor specific requirements. Develop a visually interactive graph-based representation of NCCN Guidelines®. Modeling guidelines as a visual graph (nodes and arcs) will enable oncologists to identify the optimal treatment pathway for their patients. Aim 2: Build an analytics engine that highlights the NCCN graph model with feasible treatment options given the patient’s case details and common payor requirements. Use an opensource tool to create synthetic patient data and common payor constraints with an oncologist and health plan experts. Develop a library of graph traversal algorithms to overlay and visualize the patient data in a visual user interface. Aim 3: Execute, validate and test a proof-of-concept CDS workflow using OncoPath. Run the complete end-to-end CDS workflow with documentation of patient details, NCCN guideline, payor requirements and treatment decision using synthetic patient data and payor constraints generated in Aim 2. OncoPath will enable an efficient, oncologist-friendly approach to treatment decisions and documentation, subsequently benefitting the patient and decreasing oncology cost. Phase II will deploy a real-time instance of OncoPath in a single thoracic oncology practice for integrated workflow and time savings validation.