Artificial Intelligence in Healthcare: Why it’s important and how to get started - Omega Healthcare

Artificial Intelligence in Healthcare: Why it’s important and how to get started

AI in healthcare can help reduce administrative burdens, improve clinical decision-making, and enhance the patient experience.

Author: Vijayashree Natarajan, SVP, Head of Technology

Where is the AI Market Going?

Artificial intelligence (AI) in healthcare is a burgeoning technology. A recent report from Boston Consulting Group and NASSCOM found that in 2023, $83 billion was invested in AI worldwide, with the global market value expected to reach $320-380 billion by 2027.[1] Advanced AI technologies like generative AI (GenAI) are expected to contribute approximately 33% of the overall AI market. Further, organizations are investing heavily in Data and Analytics ($42 billion), followed by GenAI ($23 billion), suggesting that organizations are putting in place the appropriate infrastructure to be able to leverage the full benefits of GenAI. At $23 billion, healthcare is one of the top three sectors after Technology and Banking to focus funding on AI.

Applying AI in Healthcare

The advancements of AI with cutting-edge technologies like GenAI and Large Language Models (LLM) help in mimicking human cognitive functions to generate complex responses, which can revolutionize patient care and medical research. Using GenAI and LLM is not just about adopting new technology; these capabilities can help enhance patient outcomes and experience while redefining the future of healthcare innovation.

AI in healthcare supports a foundation of better outcomes, increased efficiency, broader insight, improved accuracy, and improved patient experiences.

On the administrative side, AI leverages advanced algorithms to analyze data and optimize administrative workflows, thereby reducing errors and alleviating administrative burdens on employees. This allows organizations to allocate staff better, which is especially valuable given our industry’s ongoing labor shortage.[2]

AI can also help reduce clinician burnout by minimizing administrative burdens such as documentation. For example, an AI-enabled app on a mobile device can “listen” to a clinician’s patient exam and generate notes in real-time. Once the patient visit is over, the clinician can review the notes and accept or make changes where necessary. Considering the numerous hours clinicians spend outside of office hours completing their charts, this can significantly improve work-life balance.

AI in healthcare can drive improvement in both clinical and administrative processes.

On the clinical side, one of the most significant applications of AI in healthcare is in diagnostic imaging. According to the American Hospital Association, “AI’s ability to recognize and process a great amount of structured and unstructured data has led to nearly 400 Food and Drug Administration approvals of AI algorithms for the radiology field.”[3] AI can also facilitate more effective disease stratification through better risk prediction and timely and effective chronic disease diagnoses. Together, these activities help improve outcomes and the patient experience.

AI technologies can provide greater insights to clinicians to help make timely decisions and influence care plans.[4] These advanced technologies also can help support more effective pharmaceutical research and drug development to support clinical trials. Further, LLM models can help predict which patients would benefit most from a specific drug.[5]

AI’s Impact on Revenue Cycle Management

In revenue cycle management, GenAI technologies can play a major role in automating complex processes to improve efficiency and drive improved financial performance for provider organizations. For example, GenAI and LLM models can extract and classify data from unstructured correspondence letters (such as denial letters or other communications between health plans and providers), predict American National Standard Institute (ANSI) denials, post them to the provider billing system, and automate follow-ups with robotic process automation (RPA).

Automating revenue cycle management using advanced AI technologies can help improve overall efficiency, productivity, and accuracy—resulting in improved financial performance for providers.

How to Begin Using AI in Healthcare?

In a recent survey of healthcare IT leaders, half of respondents said they are or will have a strategy for using GenAI in healthcare, although just six percent have one today.[6] For many organizations, the reality is that while they may see the value of AI in healthcare and its subset technologies, they don’t have the financial resources or internal expertise necessary to implement and effectively apply those technologies. For these organizations, working with partners who can provide AI as-a-service may be the optimal solution.

Adoption of LLM models using AI as-a-service models helps accelerate the development of automation and workflow solutions. Partners with expertise in this field can provide the necessary infrastructure and pre-trained LLM models to develop solutions quickly.

When determining which processes to outsource to AI experts, organizations should prioritize those directly impacting revenue. Coding is a prime example. Poor quality coding can lead to increased denials, higher collection costs, and write-offs. Outsourcing all or a portion of the coding function to a partner that leverages AI can bring a quick return on investment. Partners who leverage AI and GenAI can deliver more accurate coding by proactively identifying and flagging potential coding issues so that they can be addressed before the claim hits the payer’s adjudication system and is rejected or denied.

Prior authorizations (PAs) are another quick-win area for AI and outsourcing. According to an analysis conducted by McKinsey & Company, “AI-enabled PA can automate 50 to 75 percent of manual tasks, boosting efficiency, reducing costs, and freeing clinicians at both payers and providers to focus on complex cases and actual care delivery and coordination.”[7]

The Time to Act is Now

AI in healthcare and related technologies aim to reduce administrative burdens, improve clinical workflows, and enhance the patient’s experience. Partnering with revenue cycle experts who incorporate AI-enabled technologies allows organizations to reap the benefits faster and without the hefty investment. Omega Healthcare can help.

Omega Healthcare has deep healthcare expertise and unmatched proprietary technology, including GenAI-enabled analytics solutions enabled by the Omega Digital Platform. We help clients increase revenues, decrease costs, and improve the overall patient-provider-payer experience through our comprehensive portfolio of technology and clinically enabled solutions. Hundreds of US healthcare enterprises depend on us to help them achieve their financial goals.


[1] “AI-Powered Tech Services: A Roadmap for Future Ready Firms,” Boston Consulting Group and NASSCOM, February 2024.

[2] The AI-Enhanced Future of Health Care Administrative Task Management,” Wiljeana Jackson Glover, Zhi Li, Dessislava Pachamanova, New England Journal of Medicine Catalyst, March 3, 2022

[3] “How AI Is Improving Diagnostics, Decision-Making and Care,” American Hospital Association

[4] “14 Machine Learning in. Healthcare Examples,” Mike Thomas, BuiltIn, February 28, 2023

[5] Ibid.

[6] “2023 Healthcare Provider IT Report: Doubling Down on Innovation,” Aaron Feinberg, Eric Berger, Rebecca Hammond, Bain & Company, September 12, 2023

[7] “2022 AMA prior authorization (PA) physician survey,” American Medical Association, retrieved from website November 9, 2023 (

Comments are closed.