Improving patient outcomes, minimizing medical errors and reducing costs are worthy goals. The key to accomplishing all of these is data. DATAVERSITY brought this interesting news to us in their article, “Improving Clinical Insights with Machine Learning.”

Data is the catalyst for eliminating unwarranted clinical variation and is essential to care models based on value. However, the complexity and growth of patient data can be overwhelming to even the most advanced organizations. Many providers are looking to machine learning to overcome these challenges.

Machine learning is connecting the dots for clinical pathway development. High-performance machines and algorithms can examine complex data elements far faster and, as a result, capture insights more comprehensively than traditional or homegrown analytics tools.

Out-of-the-box thinking and solutions are far less likely to happen with traditional methods. Machine learning brings to light possible treatments that no one would have any reason to consider.

Melody K. Smith

Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.