Despite the potential big data poses for improving healthcare, it also creates huge data quality, privacy and security problems.
It’s already being used in exciting ways. Technology developed by McLaren Applied Technologies to monitor conditions during Formula One races is being used to reduce leakage in the design of asthma inhalers and analyze heart and breathing rates among patients at Birmingham Children’s Hospital in the United Kingdom. Imperial College London uses its sensor technology to detect neurological dysfunction, reports the Financial Times.
Plans for a massive biobank in Latin America call for collecting genomic data from 1 million people over the next three years, analyzing 100 million data points as well as those of the other 19 biobanks around the world, in a quest to advance personalized medicine.
President Obama's Precision Medicine Initiative aims to collect data from similar numbers.
Yet “the risk is in big bad data,” Doug Given, director of Health2047, a San Francisco-based health systems consultancy, says in the article. “There is a real issue around quality.”
Mayo Clinic researchers recently warned of an increase in “fumbles” in genetic testing due to databases that haven’t been updated.
And though the Organization for Economic Co-operation and Development (OECD) cited the need for better governance to protect patient data among member countries, Google’s artificial intelligence company DeepMind recently signed a deal with the UK’s National Health Service that will allow its mobile app to process data on 1.6 million patients, sparking privacy fears.
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Brian Hengesbaugh, partner at law firm Baker & McKenzie in Chicago, warns in the article that the process of solving these big data problems remains “under-developed.”