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VIPCare: Virtual Predictive Care workflow with integrated surveillance for optimal care protocol selection and management in at-risk prostate cancer patients

VIPCare: Virtual Predictive Care workflow with integrated surveillance for optimal care protocol selection and management in at-risk prostate cancer patients
VIPCare:虚拟预测护理工作流程,具有综合监测功能,可为高危前列腺癌患者提供最佳护理方案选择和管理
批准号:
10758350
负责人:
Sharon Hensley Alford
金额:
$40.65万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-09-01 至 2024-08-31

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中文摘要
翻译
摘要 前列腺癌是男性的主要癌症诊断(不包括皮肤癌),存活率高 (98 5年时的百分比),导致估计有320万美国男性目前患有前列腺癌。但数据 前列腺癌患者的随访仍然是一个重大挑战。最近在Dana的一项研究中, Farber/Brigham和妇女癌症中心(DF/BCC)展示了其新颖的虚拟前列腺癌诊所 (VPCC)在四年内将新患者获得护理的机会增加了1110%,收入增加了174%。 利用VPCC初步研究获得的知识,并应对市场上的这一挑战, Vizlitics将在其现有的Cancer Insights(CI)平台上开发软件即服务产品, 与DF/BCC的研究伙伴合作,为美国癌症中心和社区肿瘤学家提供服务。 这种新的CDSS被称为VIPCare,将自动监测,跟踪和最佳分类前列腺癌病例 通过将先进的算法应用于精选的医疗数据来进行分类。基于云的平台将摄取和 整理癌症患者的医疗记录,包括非结构化笔记,并应用马尔可夫决策过程(MDP) 根据已发表的监测指南对患者纵向数据进行建模。VIPCare将自动检索 新的医疗记录数据,以使模型与最新的测试和遭遇保持同步,然后计算 在每个护理协议中的患者的分类概率(主动监测、主动治疗或术后护理)。 治疗监视)和从一个护理协议转移到另一个护理协议的概率。此外,模型 将提供关于患者是否应该通过电子、虚拟或亲自随访的建议 通过APP或医生进行访问。这种方法将:1)通过缩放一个 已经验证的方法,2)利用MDP减少手动数据输入、病历审查的需求 和动手病人管理,3)改善诊所资源的分配。第一阶段的具体目标是: 1.通过将前列腺癌指南纳入纵向患者数据来开发MDP模型。使用 回顾性患者数据,该团队将应用MDP模型来计算当前和未来护理的概率 根据最新的测试和医疗记录数据。2.优化算法将使用创建的概率分数 在目标1中,患者偏好和提供者约束来计算每个患者的分类建议。 仪表板将提供每位患者的总体状态以及整个患者人群的总体状态。 3.将运行实验室可用性测试以及分类和优化算法的准确性测试。 在第一阶段结束时,公司将证明VIPCare的可行性,实现可接受的用户 测试和计算模型精度≥ 80%。第二阶段将是前列腺VIPCare的实时测试试点 癌症诊所,为商业化做准备。显著的市场 像VIPCare这样的工具存在机会,可以提供经证明的成本节约,提高实践效率 并改善患者的治疗效果。
英文摘要
Abstract Prostate cancer is the leading cancer diagnosis in men (not including skin cancer) and has high survival rates (98% at 5 years), resulting in an estimated 3.2M US men currently living with prostate cancer. However, data shows follow up among prostate cancer patients remains a significant challenge. A recent study at Dana- Farber/Brigham and Women’s Cancer Center (DF/BCC) demonstrated its novel Virtual Prostate Cancer Clinic (VPCC) increased access to care for new patients by 1110% and expanded revenue by 174% in four years. Leveraging knowledge gained by the VPCC’s preliminary studies and to address this challenge in the market, Vizlitics will develop a Software-as-a-Service product on top of its existing Cancer Insights (CI) platform in collaboration with its research partners at DF/BCC to serve US cancer centers and community oncologists. Known as VIPCare, this new CDSS will automatically monitor, track, and optimally classify prostate cancer cases for triage by applying advanced algorithms to curated medical data. The cloud-based platform will ingest and curate cancer patient medical records, including unstructured notes and apply Markov Decision Process (MDP) modeling of patient longitudinal data onto published surveillance guidelines. VIPCare will automatically retrieve new medical record data to keep models current with the latest tests and encounters and then compute a classification probability for a patient being in each care protocol (active surveillance, active treatment, or post- treatment surveillance) and the probability of moving from one care protocol to another. In addition, the model will provide a recommendation for whether the patient should be followed by an electronic, virtual or in-person visit with an APP or physician. This approach will: 1) improve follow-up of surveillance patients by scaling an already validated approach, 2) leverage MDP to reduce the need for manual data entry, medical record review and hands-on patient management, and 3) improve allocation of clinic resources. Phase I Specific Aims are to: 1. Develop a MDP model by incorporating prostate cancer guidelines on longitudinal patient data. Using retrospective patient data, the team will apply the MDP model to compute probabilities for current and future care based on latest tests and medical record data. 2. An optimization algorithm will use the probability scores created in Aim 1, patient preferences, and provider constraints to compute the triage recommendation for each patient. The dashboard will give the overview status of each patient individually and the entire patient population globally. 3. In lab usability testing will be run as well as accuracy testing of the classification and optimization algorithms. At the end of Phase I, the company will have demonstrated feasibility of VIPCare, achieving acceptable user testing and computation model accuracy ≥80%. Phase II will be a real-time test pilot of VIPCare at a prostate cancer clinic with additional technical enhancements in preparation for commercialization. Significant market opportunities exist for a tool like VIPCare that can offer demonstrated cost savings, increased practice efficiency and improved patient outcomes.
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OncoPath: Intelligent Clinical Pathway Decision Support Tool for Pre-Authorization Documentation in Non-Small Cell Lung Cancer Treatment
  • 批准号:
    10325551
  • 项目类别:
  • 资助金额:
    $39.87万
  • 财政年份:
    2021
  • 负责人:
    Sharon Hensley Alford
  • 依托单位:
海外基金