Big data is everywhere at the moment, with many believing it is the next big leap in medicine. So great is the interest in this area that Health Affairs journal recently dedicated an issue to the progress, possibilities and challenges of using big data in health. Big data obtained from thousands of electronic records combined with predictive analytics is thought to have huge potential not only in identifying patients at risk but in areas such as research and fraud detection.
In America, many companies are jumping in to see where big data can take them in health care. Not surprising given that, according McKinsey , making sense of big data in health could save in excess of $300 billion a year in the United States.
In an article in the MIT Technology Review “Can technology fix medicine?” a number of potential uses for big data currently being explored are discussed including understanding drug compliance, receiving alerts for potential adverse drug interactions and determining genetic predisposition.
The potential of big data combined with modern analytics is exciting, especially the research possibilities. The problem occurs when people start thinking big data and end up thinking about personal data.
In a recent Bloomberg article “Hospitals are mining patients credit card data to predict who will get sick” the possibilities start to get uncomfortable. Carolina Health Care is using the consumer data of more than 2 million people in algorithms that they hope will allocate patients with a risk score to be provided to doctors so that they can “reach out” to high risk patients. While the service is not yet able to access an individual’s purchase data – they hope to. “The idea is to use Big Data and predictive models to think about population health and drill down to the individual levels.” This of course is undertaken in the name of early intervention. According to the Chief clinical officer for analytics and outcomes research “The data is already used to market to people to get them to do things that might not always be in the best interest of the consumer,” he says. “We are looking to apply this for something good.” Examples given include understanding whether an asthmatic might end up requiring emergency care by combining information such as whether scripts are filled, pollen count where they live and whether they buy cigarettes.
The Australian system is not the American system, however the changing role of health insurers in Australia does make one wonder how long it might be until data from credit and loyalty cards prompts a call from your insurer. In the mean time I might start making the move back to cash…….