Cloud-based Analytical solution that predicts occurrences of cancer (breast, lung, colon, prostrate) based on Vitals EMR data, family history, genomics data, HIE’s and patient health in general. The solution calculates the risk score for at risk- patients, against various attributes of oncology. This solution requires interoperability with ACO’s, HIE’s and Health Systems.
Cloud-based predictive analytical software to detect cancer (Breast, Colon, Prostrate, Lung), using next generation gene sequencing (NSG), genome data, gene markers and certain demographic data and EMR data. ONCOGENOME Analytics, software predicts a risk score for at- risk patients and generates a care plan base on the risk score. Some cancers, or most cancers, do not show signs or symptoms in their early stage. Especially Lung Cancer and Colon Cancer. Current efforts to diagnose cancer (breast, colon, lung, prostate) rely on many different schemata, including histopathology, tumor grading, international staging classifications, and receptor status, e.g., ERG+/-.
Each of these aspects inform and influence treatment decisions, however none of these classification systems have yet to include the revolutionary high through put genomics data.
Early prediction of cancer using gene sequencing and relevant attributes and assigning a risk score for at risk patients. Risk score determines the next steps in the process. Gene Sequencing is obtained either by vendor or user may have an exsisting file. The value of our solution is vested in lowering the overall total cost incurred for treatment of cancer at the different stages, particularly at the screening level which has seen a rise in controversy in recent years due to direct costs, indirect costs, complications of diagnosis and treatment, and the risk of over diagnosis and defensive medicine. Risk score will determine customize care plan based on at- risk patient evidence based medicine and pre-established results. Continuous monitoring of patient’s progress and adherence to care plan and successful reduction in the risk levels. This solution recommends any treatment option and care plans for the potential at risk patients with occurrence index between 10-100% risk score.