Creating a more human healthcare future with AI The COVID-19 pandemic increased the amount of time we spend communicating through screens instead of in person. The result: a growing sense of isolation, one that the US Surgeon General Dr. Vivek Murthy believes contributed to an “epidemic of loneliness.” This highlights a paradox: Healthcare, one of the most personal of services, now lacks connection when we need it most. This lack of human connection hurts everyone – from patients to providers, healthcare professionals, and the supporting ecosystem. So, how can humanity be restored in healthcare? Given how fast technology is advancing, defining a strategy that deliberately creates space for more-meaningful human connection needs to be top of mind. The good news: Stakeholders seem aligned on making it happen. The recent GE HealthCare report Reimagining Better Health 2023 reveals that both clinicians and patients agreed that a “more human” future is necessary for healthcare — one that is “flexible, focusing on the needs of both clinicians and patients.” AI or humans? It doesn’t have to be an either/or decision If you’ve ever been a patient or a caregiver, you’re familiar with the responsibility of sharing information between your doctors. It shouldn’t come as a surprise that the back-office technologies that house our information are not well integrated. Our patient and health plan information is locked in silo after silo. This makes patient and clinician interactions less than ideal, in addition to making back-office transactions (e.g., cases between payor to provider) inefficient. While the industry is keen on making progress through initiatives such as the Cares Act and other methods of interoperability, there is still a huge communication gap to address. There are dozens, if not hundreds, of touchpoints in a patient’s healthcare journey, involving providers, care teams, insurance companies, and pharmaceutical organizations. All of these touchpoints are necessary, but they don’t carry the same emotional weight. Based on the use case, you could rely on an AI-led, human-led, or have a partnership of AI and humans. For example: AI-led: Logistical, repetitive administrative tasks, such as appointment reminders, prescription renewals, benefit checks, and form submissions. AI and human: Frequently asked questions that an empathic AI could draft answers to, which could then be edited as needed and sent by a care team member. Human led: Clinicians calling to explain test results or explain financial assistance options to a provider or patient. The key is to carefully consider which tasks can be automated and how to incorporate human oversight. For example, if your use case requires access to data that is trapped in a silo (like a digital or physical knowledge base), humans may need to be involved to provide context from other sources, such as their past experiences or internal resources. Expert framework for selecting AI use cases What tasks should we apply AI to? There is no magic formula, but industry experts at Andreesen Horowitz suggest two more detailed sets of criteria in Commercializing AI in Healthcare: The Jobs to be Done. They found that healthcare tasks that are well-suited to AI: Use large amounts of complex and esoteric data that must be synthesized in real time to inform a consequential decision or action. These are tasks that no human would, or could, perform as well as a computer. Are labor-intensive, usually requiring ongoing, extensive (and expensive) employee training where there is low adoption of tech-enabled solutions. Our industry suffers high turnover and burnout, so the need for continuity and retention of capability is acute. Given that reality, Andreesen Horowitz concludes that building specialist AIs to perform healthcare tasks offers the “greatest opportunity for impact.” The same point is made in the GE report, which found that moving from manual to smart workflows aided by interoperable, smart devices and conversational AI systems would generate better, more data-driven care decisions. Advanced technologies can benefit all stakeholders Much of AI discussion in healthcare focuses on how it can help patients, because it’s an experience we all know firsthand. But that’s only part of the story. If we enable the employees responsible for back-office tasks with better solutions, we could help retain experienced staff and make their roles more fulfilling by freeing time for more substantive, human work. This could improve staff retention and satisfaction, as well as patient outcomes. Consider this: An American Medical Association survey found physicians and their staff spend almost 14 hours per week completing prior authorizations, while the US Government Accountability Office (GAO) estimates that federal agencies made an estimated $247 billion in payment errors in 2022. AI, when integrated across the care flow, can address these inefficiencies. There is massive enthusiasm for AI solutions that improve patient outcomes and enable a strong human connection. Infinitus was founded on the belief that the use of AI can help both healthcare providers and patients streamline communications and accelerate access to care. Our solutions free up hours of back-office staff time by automating benefit verification and prior authorization processes, and due to higher accuracy of the data we capture, it also improves the downstream billing, claims, and denial and appeal processes. To learn more about how we’re creating time for healthcare to improve access, adherence, and affordability, contact us today.