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Many healthcare organizations underutilizing the rich insights from encounter data and associated risk analytics.
From retail to travel to education, artificial intelligence (AI) has created new efficiencies and experiences that continue to improve daily lives and business workflows. Research shows there is no sign of AI slowing down. In fact, according to a Gartner report in early 2020, 40% of organizations planned to deploy AI solutions by the end of the year. It’s clear that businesses continue to place big bets on AI, so how can healthcare better leverage this technology?
While there are multiple important use cases for AI in healthcare, one application that deserves more attention is encounter management. Today, many healthcare organizations, especially Medicare Advantage (MAO) plans are underutilizing the rich insights from encounter data and associated risk analytics. Why? Some plans are simply stuck in the past. These plans still use multiple, highly manual encounter submission systems where one small error could cause large scale revenue loss. Others still lack the ability to connect encounter, risk and clinical data together to reveal any meaningful insights about populations served. And finally, some health plans are still making the shift to FHIR (Fast Healthcare Interoperability Resources) standards, which is setting back their ability to experience the potential of applying AI to their data sets.
It is time health plans develop a risk adjustment strategy that incorporates AI in encounter submissions to accelerate compliance and risk-adjusted revenue accuracy and improve member outcomes. Below are just a few of the benefits of integrating AI into encounter management systems:
In a dynamic healthcare market, the health plans that invest in an intelligent encounter management system, driven by AI, will be best positioned to drive better health outcomes and generate revenue. Don’t be the plan catching up – lead the industry forward with a more informed encounter strategy.
Baker is Associate Vice President of Analytics at Edifecs.