Artificial intelligence (AI) and machine learning are more frequently being utilized as operational necessities for addressing healthcare’s more systemic challenges. This interesting news came to us from AIThority in their article, “How AI and Machine Learning Can Transform Utilization Management.”
Many clinical applications already leverage integrated AI capabilities. Unfortunately, utilization management has not yet evolved. Utilization management is the evaluation of the medical necessity, appropriateness, and efficiency of the use of healthcare services, procedures and facilities under the provisions of the applicable health benefits plan. For patients and providers, it is a manual process and a lot of hoops to jump through before procedures, treatments, and special equipment can be approved for care.
AI can not only in automate manual processes, but has the potential to make better, more consistent decisions. The transparent application of AI to utilization management can streamline clinical review, increase provider satisfaction and feed the continual identification and refinement of customized care paths.
In reality, most organizations have little knowledge of how AI systems make the decisions they do. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Why is this important? Because the results can have an impact on data security or patient safety.
Melody K. Smith
|Data Harmony is an award-winning semantic suite that |
leverages explainable AI.
Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.