Camille Bautista2013-03-29 23:24:54 UTCThe American Society of Clinical Oncology is looking to further personalize and improve cancer care by tapping into data from millions of patients around the nation.
The organization completed the prototype for CancerLinQ, a "learning health system" that collects and analyzes anonymous patient information to provide immediate feedback and guidance for physicians.
Very little is known about most people's experiences with cancer because information is locked in unconnected servers and paper files, says Sandra M. Swain, president of ASCO. Only 3% of cancer patients participate in clinical trials, but that small percentage isn't reflective of patients doctors see every day.
Privacy issues are a major concern with medical information but the organization says the prototype has undergone extensive technological and legal analysis.
The CancerLinQ prototype currently focuses on breast cancer with "de-identified" data from 100,000 patients, meaning identifying information has been removed through a third party prior to being available for search. The data is collected by physicians as part of the treatment, and the information used in the system is not typically something patients need to consent to, says ASCO’s corporate secretary Dina Michels.
Data collected from patients mainly consists of factors that can improve physicians' quality of practice, such as giving appropriate medicine or survivorship care issues. The organization is still working to ensure the database complies with HIPAA regulations.
The system collects real-time data directly from electronic health records including lab tests and doctors' notes. It also works to pinpoints patient characteristics, treatments and outcomes to further provide physicians with personalized suggestions based on similar cases.
ASCO joins the slew of healthcare professionals and organizations using big data to further improvements in treatment, including IBM's Watson, which is being used by Memorial Sloan-Kettering Cancer Center to help patients using algorithms and data computing.
Image via iStockphoto, konglinguang
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