- More accurate diagnoses. Predictive analytics software searches through huge amounts of information such as past treatment outcomes and recent published medical research. It then analyzes the data to predict the likelihood of disease for an individual patient based on a multitude of factors (age, health status, gene studies, etc.)
- Improved treatment plans. Big data allows physicians to go a step beyond evidence-based medicine by helping them develop highly individualized treatment plans. James Noga, CIO of Partners HealthCare, likens it to the difference between plotting your trip on a paper map and using a GPS that plans your route based on real-time traffic information.
- Patient engagement. Much has been said about the importance of getting patients involved with their care. Predictive analytics can play a role here, suggesting gene markers for certain diseases. In cases where gene treatments are not available, evidence-based research can be used to indicate lifestyle changes for patients with the gene (e.g., exercise, nutrient-rich diet, brain games, and frequent memory tests for patients with a gene marker for early-onset Alzheimer’s). Using a patient portal to record sleep patterns, dietary changes, and so on is an ideal way to engage patients in these activities while providing data that can be used by the physician to develop a predictive model for things like memory maintenance.
Currently, one of the most popular uses for predictive analytics is by hospitals, which are using custom and publically available algorithms to predict which patients are most likely to return to the hospital with 30 days of discharge for the same condition. But as experts explore this technology, physicians should expect to see more widespread uses, including areas that directly affect the way they care for patients.
Partners HealthCare’s Noga, who will speak on this topic at the HIMSS Media and Healthcare IT News Big Data & Healthcare Analytics Forum in November in Boston, put it this way when talking to Government HealthIT. “With big data, you’re talking about data that’s fast moving and perpetually occurring—actually able to intercede rather than merely advise in terms of the care of patients. On the discovery side with genetics and genomics using external data sources, I think the possibilities of evidence-based medicine and being able to drive better protocols on the clinical side is endless in terms of the possibilities.”
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Last Updated on November 6, 2014