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 ad...