Rethinking the Care Plan: Clinical Decision Making

February 25, 2016

When we’re not feeling well, our first thought is usually -- should I see a doctor? We expect our doctors to make the correct diagnosis and give the right treatment at the right time to make us feel better. The expectations we have for physicians to provide the best care possible for patients continues to grow, largely due in part to the recent explosive increase in, and availability of data. However, all this added data can be overwhelming without an easy way to analyze and digest its importance. The data itself is useless without a way to determine its value for the patient at the point of care, without gleaning the necessary information and knowledge from the data and from other sources.  

From a pragmatic perspective, these expectations can be unattainable because so much information is available within each area of clinical specialty that no doctor could possibly retain all that is necessary to guarantee delivery of the best possible care to each possible patient. This problem will only get worse, particularly as we move towards increased utilization of genomics, proteomics, patient-generated data and more.

Simply having more data available does not in and of itself ensure better treatment decisions. All data must be fed into an intelligent system that analyzes the data in order to support better clinical decision making, that continuously learns from every piece of data. This approach can drastically lower the potential for human error and is critical for success in value-based care.  

Enter Flow Health.

The solution is to have intelligent clinical decision automation that combines known advances and evidence-based protocols with data science and machine learning to create individualized treatment plans so patients get the best care possible.

Symptoms and treatments can vary, but artificial intelligence can help healthcare providers and payers establish treatment plans for patients in order to promote the best outcomes. At Flow Health, we use artificial intelligence to automate clinical decision-making. We detect patterns and trends in patient information to better diagnose and personalize treatment decisions, unlike existing care decisions that are guided by evidence-based protocols that only consider a limited set of data to guide physician and payer decisions for broad populations. This has widespread implications from point-of-care decisions to administrative functions, including utilization management (prior-authorizations approvals).

We’ve designed Flow Health as a “networked platform” that integrates data and connects the entire care team, the patient and the payer. We partner with payers to integrate all of their data collection and exchange activities onto our networked platform, which lays the foundation for the future of healthcare decision making. Our approach gives us the potential to achieve the needed “Data Network Effects” to enable artificial intelligence that can determine the best treatment decision for personalized care decisions for nearly every population and situation.

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