U.S. Healthcare Payers and GenAI: Benefits, Risks and Investment
In this blog
The U.S. healthcare ecosystem is undergoing a transformative shift thanks to generative AI (GenAI), with significant implications for healthcare payers. These organizations are at the cusp of harnessing the power of GenAI to redefine their operations, customer engagement, employee experience and overall service delivery.
The advent of GenAI in healthcare insurance
GenAI, a subset of artificial intelligence, specializes in creating new, original content that ranges from text to images to video and beyond. In the land of healthcare insurance, this technology promises to revolutionize various facets of the industry.
Enhanced member services
One of the most immediate GenAI applications for healthcare payers is improving member services. UnitedHealth Group, for example, is using a GenAI-powered virtual assistant for patient communication. This tool can guide members through the complexities of healthcare plans, provide personalized assistance, and improve the overall member experience by shepherding members along their journeys 24/7.
GenAI tools can also positively impact the employee experience by freeing up their time to focus on more complex issues.
Streamlining operations
GenAI also offers the potential to streamline claims processing and prior authorization. By automating these processes, insurance companies can reduce manual workloads, expedite care delivery, and minimize the potential for human error. When a patient is in the middle of a care journey, any steps that can minimize or eliminate bureaucratic delay and expedite care are critical.
For example, a physician who orders a study or medication may believe they need prior authorization from the patient's insurer before the study can be scheduled or medication dispensed. In most instances, they would not be wrong. However, there are times when, depending on the insurer or diagnosis, prior authorization is not needed and the treatment plan can move forward. The physician's office is often unaware of these exceptions, which can result in care delays.
Or consider dealing with cancer and other diseases where time is of the essence and administrative rate-limiting steps do not help. Real-time, reticent AI solutions capable of informing clinical teams what can done now, without further delay, will win the day. Additionally, GenAI solutions that assist in documentation, billing and claims processing can offer clinical and financial efficiencies when used judiciously.
Unfortunately, if appropriate regulations are not implemented, GenAI solutions can bring care delivery to a screeching halt. Recently, claims processing came under fire at Humana and United Healthcare. A class-action lawsuit was filed in mid-December 2023 that asserts these companies utilized AI technologies to incorrectly deny medically necessary care.
Improving clinical documentation
Insurance companies that also deliver clinical care (a.k.a. "payviders"), such as UPMC, Kaiser and others, are exploring GenAI, natural language processing (NLP), and ambient listening technologies to help author clinical notes, discharge summaries and care coordination notes. Shifting to tools like this can significantly reduce clinician burnout, a pervasive problem today, allowing clinicians to focus more on patient care. For example, the AAFP (American Academy of Family Physicians), in conjunction with Suki.ai, reported in a study that physician documentation time was reduced by 72 percent when utilizing these technologies.
Investment and partnerships
Even though 2022 and 2023 saw a decrease in venture capital funding for digital health startups, GenAI's potential has attracted significant investment dollars. Companies like Hippocratic AI and Genesis Therapeutics draw capital from venture sources and growth equity funds to advance their AI solutions. Additionally, mature private equity firms are investing in partnerships to leverage OpenAI's ChatGPT in clinical trials (e.g., see the collaboration between Syneos Health and Microsoft).
The investments do not end there. U.S. healthcare payers are also investing significantly in their IT infrastructure and digital/data transformation tools. According to the 2024 Gartner Healthcare Payer CIO and Executive Survey, AI/ML technologies are most likely to be 100 percent implemented by 2026, with GenAI predicted as the top game-changing technology in the next three years.
Surveyed executives also shared they expect to increase their investment in AI/ML, cloud platforms and integration technologies. The technology areas expected to see less investment, on the other hand, include legacy infrastructure and data centers, enterprise resource planning, IoT, and digital workplace.
Navigating challenges and ethical considerations
Despite its potential once integrated, GenAI has its own set of risks for healthcare payers to navigate.
Data privacy and bias
The paramount concern in healthcare is patient privacy. GenAI systems require access to vast amounts of data, raising concerns about privacy and security. Moreover, there's the risk of AI systems developing biases based on the data they are trained on, which could lead to discriminatory practices.
Regulatory landscape
The regulatory environment for GenAI in healthcare insurance is still evolving. Insurers are advised to build explainable pilots involving non-patient data and document system functions to avoid legal issues. This approach can be very time and labor-intensive, especially when many lack the required employee resources (e.g., IT, engineers and data scientists) to proceed. The need for clear regulations necessitates a cautious approach to adopting GenAI technologies.
Ethical AI
To mitigate the risks of GenAI, insurance companies should prioritize the development of ethical AI. This practice involves leveraging diverse and representative training data, consistent evaluation, and auditing AI systems through robust governance models. At WWT, we recommend all businesses follow UNESCO's 11 policy considerations for implementing the practice of Responsible AI.
The future landscape
Looking ahead, the convergence of GenAI across different sectors offers vast innovation opportunities for healthcare payers. The industry stands on the brink of a paradigm shift, one where AI-driven solutions could lead to substantial value creation, cost savings and operational efficiencies.
Realizing the potential
The key to unlocking the full potential of GenAI lies in strategic investments focused on profitability, growth and operational intelligence. By harnessing GenAI for autonomous coding and content creation, insurance organizations can accelerate software development cycles, enhance workforce productivity, and improve customer engagement and satisfaction.
Building a seamless end-to-end solution
The real game-changer will be integrating disparate GenAI use cases to build holistic, seamless solutions at scale. This requires deep domain expertise, contextual understanding, and the ability to customize and fine-tune existing AI models to achieve specific outcomes. The future of healthcare insurance will likely be characterized by such comprehensive, AI-driven ecosystems.
In summary, GenAI is poised to revolutionize the healthcare insurance industry. From improving member services to streamlining operations and clinical documentation, the possibilities are vast. However, navigating the challenges of data privacy, regulatory uncertainties, and the need for ethical AI practices are critical for its successful integration.
As healthcare insurance companies prepare to leverage this technology, they stand at the forefront of a significant shift toward more efficient, responsive and patient-centered care. They also understand they need help to be successful. That's why they're choosing to partner with a global solutions provider like WWT. Not only have we been delivering advanced AI/ML solutions to clients across industries for over a decade, but we just introduced our new AI Proving Ground, where healthcare organizations can accelerate their ability to experiment, test and innovate with hands-on access to the latest AI hardware, software and reference architectures — all in a secure, scalable and transparent manner.