Improving Clinical Insights with Machine Learning

by Angela Guess Mark Hardy recently wrote in Health Data Management, “Understanding and managing unwarranted clinical variation is a significant and costly challenge in today’s value-based health economy. Every patient is unique, so variation is a natural element in most healthcare delivery. But improving patient outcomes, minimizing medical errors and reducing costs is difficult when hospitals are unable to draw hidden insights from their own data. Data is the catalyst for eliminating unwarranted clinical variation and is essential to care models based on value. However, the complexity and exponential growth of patient data can be overwhelming to even the most advanced organizations. Machine learning is helping to overcome these barriers. These applications, which combine algorithms from computational biology and other disciplines, find patterns within billions of data points and help…

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