The use of AI in the healthcare industry has become a common trend. It has already proven to be an effective tool to help hospitals improve coding and auditing performance by driving efficiencies and saving time for health information management and revenue cycle management professionals.

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Healthcare facilities are searching for innovative approaches to solving current healthcare challenges and are turning to artificial intelligence (AI) as the solution. In fact, AI healthcare funding has increased globally by 140% between 2020 to 2021. AI acts as a way to simplify processes and create impactful results for healthcare teams. Healthcare organizations are using AI to target short-term and long-term challenges, including:

• Performing healthcare data management tasks and improving data quality
• Managing employee workload by reducing the number of repetitive tasks
• Powering predictive analytics to manage population health

Semantic Health is leading the way for hospitals to adopt proprietary AI and machine learning  (ML) technology to improve auditing processes in healthcare. With proven results, AI is being used to drive efficiencies, improve accuracy, and save time for HIM and RCM professionals. Specifically, Semantic Health is leveraging AI to help hospitals streamline current coding and auditing processes by sourcing specific opportunities to close gaps and open pathways for better workload management.

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AI can be used to target pressing short term and long term challenges

AI is constantly evolving to meet the demands of organizations to help manage and increase productivity towards the completion of complex tasks. As healthcare organizations begin a more comprehensive digital transformation process, AI will continue to be fundamental in driving efficiencies. AI is able to continue learning given a stream of healthcare data. Using the Semantic Auditor, for example, HIM and RCM teams are able to effectively assess coding and conduct auditing processes with continually learning AI software. In the short term, this will result in productivity and less time spent by HIM and RCM professionals on time-consuming tasks by easing the workload burden. In parallel, the long-term impacts enforce that the Semantic Auditor will learn based on key indicators to create even more efficiencies and accuracies in data quality. As a result, the use of AI is effectively managing data quality and ensuring that there is less time spent on repetitive tasks. HIM and RCM teams can benefit as more data is ingested - opening up opportunities for tailored software solutions.

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Tailored AI Technology Solutions

AI technology is unique in its ability to be tailored to best target the demands of specific use cases by ingesting data. For example, at Semantic Health, we identify flagged issues for specific hospitals based on their unique data set to source and provide the most relevant information. In fact, specialized patient populations require specialized tools as represented by many healthcare organizations trying to enhance customer offerings through AI. Clearly, there is a shift toward AI adoption which allows for the management of issues such as extreme backlog, very expensive overtime bills, low-quality work-life balance, and reduced reimbursements. Hospitals with inefficient/outdated software are unable to address these challenges and cannot capture relevant data in many unique hospital data sets.

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The Semantic Health Impact

The Semantic Health Information Platform has had many successful deployments at leading hospitals across the country, resulting in significant improvements at leading hospitals by:

• Reviewing 100% of claims data using AI and increasing audit speeds by 3x
• Increasing the audit yield, measured in increased relative weighted cases, by up to 50%
• Where the Semantic Coder is installed, improving coding efficiency by 25%
• Creating an actionable data layer to enable further analysis and research of unstructured data

Importantly, in considering the applicability of AI for your organization, it is important to consider the quality of data that you will input into such models. The Semantic Health Information Platform can be the essential foundation to improve your coded data quality. With these improvements, you can enable new use-cases of this data downstream for your organization, including in population health management, follow-up management, and care delivery.