AI has created an enormous buzz in the last 18 months, with every industry set to be “transformed” by this new technology. But many value-based care providers are still unsure exactly how they should approach the prospect of AI.
This article explores how AI will really be used in healthcare organizations – and which solutions you can start adopting today.
The Role of AI in Healthcare: An Executive Overview
What is AI?
Artificial Intelligence (AI) is a broad category of technologies that exhibit human-like intelligence and perform a range of useful functions. It can be broken into two distinct groups:
- Extractive AI: Solutions designed to ingest and analyze data, before “extracting” insights or answers to the user’s questions.
- Generative AI: Solutions designed to synthesize large data sets and produce novel outputs, such as new texts or images.
Both forms offer clear benefits for healthcare organizations. With the ability to extract vital information, produce text faster, and analyze larger, complex datasets in seconds, AI is set to revolutionize healthcare – if providers find the right use cases to implement.
How Quickly is AI Advancing in Healthcare?
With patient safety and ethics to consider, the healthcare industry tends to be slow in adopting technology. However, the clear benefits of AI have led to a lot of excitement, and two clear indicators point in a positive direction:
- Interest Is High: A recent study surveyed payers, providers, and healthcare services and technology (HST) groups about their adoption of AI. The researchers found that 29% of organizations had already implemented AI solutions – and 60% were proactively exploring the possibility of adoption.
- Solutions Are Growing: The FDA has cleared 700 AI algorithms for healthcare, with the majority in radiology but cardiology increasing swiftly too. As more tools enter the market, providers will be able to focus less on the abstract concept of “AI in healthcare” and think instead about concrete steps to implement specific solutions.
Three Ways AI Can Help Value-Based Value Providers
1. Improve Documentations
Documentation is a major challenge for most value-based care providers, with data silos and gaps in patient medical histories leading to persistent issues with both HCC coding accuracy and the quality of care. Estimates vary, but some studies have found at least 50% of EHRs contain errors, while another found that over 85% of inaccuracies in documentation were considered “major errors”.
AI can help value-based care providers improve their documentation in two ways:
- Generative AI can be leveraged to accelerate and improve the accuracy of documentation. Structure and unstructured data (such as handwritten notes) can be synthesized to create a centralized store of information that eliminates data silos and provides a fuller view of the patient.
- Extractive AI can then be used to more quickly and reliably produce the relevant information or insights from that documentation.
2. Elevate Patient Care
Every value-based care provider wants to offer better service and increase their quality scores. AI offers several powerful ways to achieve this goal:
- Improve Diagnostic Accuracy: AI models can be trained to identify patterns in medical data such as imaging that humans are prone to miss. Researchers find that AI can improve multiple measures of diagnostics accuracy, such as sensitivity and specificity, area under the curve, positive predictive. and negative predictive values.
- Optimize Treatment Plans: AI models can identify the most impactful care pathways and help providers access relevant data to make treatment decisions.
- Streamline Workflows: Research suggests value-based care providers spend roughly twice as much time on manual tasks such as grappling with EHRs than they do focused on patient care – which limits the impact they can have on patients. AI can take over a wide range of manual tasks such as reading endless radiology reports or HCC coding and ensure providers can focus on direct patient care. Some suggest this will increase productivity by as much as 250%.
3. Optimize HCC coding and Risk Adjustment Workflows
HCC coding and risk adjustment are vital to ensure value-based care providers receive adequate reimbursements from Medicare Advantage patients. But many organizations find the process time-consuming and convoluted, often struggling to produce accurate HCC coding and therefore missing out on vital funding.
The right AI algorithm can identify relevant diagnoses and recommend HCC codes at the point of care. HCC Assistant does this with 97% accuracy, providing several clear benefits:
- Time Savings: Providers no longer have to spend hours on HCC coding; they can simply review and accept or reject suggestions.
- Eliminate Data Gaps: By factoring all structured and unstructured data into their HCC coding, providers will gain a more accurate and comprehensive view of their patients’ medical histories.
- Avoid HCC Coding Errors: Providers will reduce the frequency of missed or overlooked diagnoses in their HCC coding – which in turn produces higher RAF scores.
All of which suggests every value-based care provider ought to be using a tool like HCC Assistant to enhance their risk adjustment workflow. This raises the pivotal question…
What Are the Barriers to AI Adoption in Value-Based Care?
There are four common challenges providers face when approaching AI solutions:
- Data Reliability: AI requires accurate data, otherwise it cannot produce reliable outputs. But many value-based care providers still struggle with gaps in patient data. This is often a result of poor data capture and documentation.
- Data Fragmentation: Even providers that do have complete patient data often struggle to access it all when they need to. For example, information may be stored in a separate practice or digital system which is not readily available.
- Digital Skill Gaps: Many providers fear that a lack of digital skills may hold them back from adopting AI. There is a common perception that AI requires expertise in computer science or will only be safe to use if providers are highly skilled with technology.
- Cost and Safety Concerns: While most providers see the long-term benefits of AI, many believe AI will be a short-term loss for their organization – and struggle to make a strong enough business case for adoption.
Overcome Healthcare AI Adoption Barriers with HCC Assistant
HCC Assistant is a natural-language processing (NLP) tool that streamlines your risk adjustment workflows and produces accurate HCC coding recommendations at the point of care. It eliminates the biggest barriers value-based care providers face when introducing AI, including:
- Usability: HCC Assistant is designed to fit seamlessly with your providers’ workflows. It does not require any specialist skills to use with confidence and make reviewing and accepting HCC coding recommendations fast and easy.
- Data Unification: HCC Assistant ingests structured and unstructured data to enhance documentation and create a single, easily accessible store for all patient data.
- Compliance: HCC Assistant is 100% compliant with existing regulations, and we take active steps to stay ahead of upcoming regulatory changes to ensure providers can use the tool with no compliance issues.
Want to explore how the tool could help your practice leverage AI and optimize RAF scores?
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