In the US alone, one million injuries occur every year as a result of prescription errors. Mistakes are understandable when you consider the sheer number of prescriptions filled out on any given day, but the risks associated with those errors are very real, and result in thousands of preventable deaths. Hoping to drastically reduce the potential for such costly accidents, Medaware is a platform which uses big data analytics to flag up errors and enable clinicians and pharmacists to correct mistakes before patients are put in danger.
Medaware offers a significant improvement on current systems, which operate using rule-based solutions and therefore only catch a fraction of errors. Conventional systems usually focus on spotting potentially dangerous drug interactions, dosage problems or allergies and so will miss any problems outside of their predetermined rules. Medaware, on the other hand, uses big data analytics, enabling it to highlight a broader range of potential mistakes with more accuracy.
When a physician prescribes a new drug, the system immediately evaluates whether this medication is a deviation from the prescription pattern of similar patients. If Medaware detects a deviation, it is most likely an error, and the system notifies the clinician immediately.
Conventional alert systems are overridden by physicians in 96 percent of cases. Medaware has a 10 percent false alarm rate, which reduces the risk of alarm fatigue. How else could big data be used to detect deviations and errors in the medical field?