The necessity of real-world evidence and sustainable reimbursement to support AI in healthcare
The New England Journal of Medicine (NEJM-AI) published a paper authored by Digital Diagnostics’ founder and executive chairman, Michael D. Abramoff, MD, PhD, titled “Scaling Adoption of Medical AI: Reimbursement from Value-Based Care and Fee-for-Service Perspectives.” The publication highlights the transformative power of artificial intelligence (AI) in healthcare when all stakeholders and real-world evidence support AI adoption and sustainable reimbursement.
The groundbreaking contributions to healthcare AI by Dr. Abramoff and others extend beyond this latest publication, with earlier works that focus on establishing an ethical foundation for AI, overcoming the challenges of integrating AI in healthcare, and setting the stage for AI solutions to become the new standard of care.
In a recent publication, researchers at Stanford University identified AI solutions for diabetic retinopathy (DR) as one of the fastest growing sectors in healthcare, citing Digital Diagnostics’ flagship product, LumineticsCore™ as the first solution to gain FDA clearance in this field.
As the trailblazer for autonomous AI in healthcare, Dr. Abramoff continues to be a leader in the field, conducting pivotal studies and authoring scholarly articles alongside his colleagues that underscore the effectiveness of AI in healthcare and highlight the need for sustainable reimbursement to support the long-term success of AI solutions.
Looking Back
The initial work that would lead to Digital Diagnostics gaining FDA clearance in 2018 started decades earlier when our founder was focused on pioneering the development of medical AI, working to demonstrate that computers could effectively make diagnostic decisions traditionally reserved for physicians.
In a 2007 study, it was demonstrated that computers could analyze eye images to monitor glaucoma as effectively as eyecare specialists. Building on this, subsequent research showed that computers could detect DR with the same, or better, accuracy as human experts. These findings showed the potential for computer-assisted diagnostics to not only alleviate the workload of specialists but also expedite the diagnosis and treatment process for patients with DR.
Developing an Ethical Foundation
As work was being done to develop the technology, an equally important field of study was being explored, namely, the ethical considerations of bringing AI to patient care. The ethical considerations of healthcare AI is a recurring theme in Dr. Abramoff’s extensive body of work, with ethics forming the foundation of a significant portion of his contributions to the healthcare AI industry. Several papers authored by Dr. Abramoff, in partnership with other medical, research, and government entities, explore the critical need for AI in healthcare to be built on a strong ethical foundation.
A 2022 publication that established the groundwork for ethical considerations being essential for AI implementation in healthcare highlights the prerequisites for gaining reimbursement. Another notable paper, which identifies ethical considerations for machine learning healthcare applications, outlines a systematic approach for addressing ethical concerns in healthcare AI. This approach is crucial for developing sustainable reimbursement models that include ethical implications, echoing discussions from the NEJM publication on scalable adoption. Most recently, a 2023 publication focusing on bias in AI delves into the continuous and crucial process of analyzing, addressing, and mitigating biases within healthcare AI, underscoring the importance of these efforts in leveraging AI to enhance health equity.
Implementing LumineticsCore to Improve Patient Outcomes
After decades of collaborative research by Dr. Abramoff and his colleagues, a significant milestone was achieved in 2018 when the FDA granted De Novo clearance to LumineticsCore, the first autonomous AI diagnostic system in healthcare.
Leading up to FDA clearance, Nature Digital Medicine published the results from LumineticsCore’s pivotal clinical trial, highlighting its proficiency in detecting DR and demonstrating the effectiveness of AI in healthcare. A follow-up paper on the use of autonomous AI for the detection of DR helped lay the groundwork for the safe and effective integration of AI in healthcare settings. This concept is further explored in the scalable adoption NEJM publication, which addresses the financial infrastructure necessary for AI’s widespread adoption and realization of its potential benefits in healthcare.
Real-World Evidence
The adoption of LumineticsCore in real-world settings has shown that medical AI is not only feasible but can revolutionize healthcare by improving health equity and care quality, increasing access, and reducing costs. Using LumineticsCore as a prime example, Dr. Abramoff, along with other industry leaders, has authored several papers that demonstrate AI’s transformative impact in healthcare.
A reimbursement framework published in 2022 emphasizes the critical role of reimbursement strategies for the scaled adoption of AI in healthcare settings – a central theme also explored in the NEJM publication on scalable adoption. Another significant paper, which focuses on the determinants for the scalable adoption of autonomous AI, identifies essential factors, such as regulatory clearance, reimbursement, and clinical workflow, necessary for AI scalability and integration.
Another of the collaborative works authored by Dr. Abramoff reveals the potential impact of AI on healthcare delivery. It underscores the transformative capacity of AI in healthcare, while emphasizing the importance of financial models and stakeholder collaboration for reaping the full benefits of healthcare AI. Additional research on the impact of autonomous AI on healthcare delivery examines the productivity benefits of autonomous AI, aligning with findings highlighted in the scalable adoption NEJM publication.
Looking to the Future
Ultimately, the success of AI-based healthcare solutions, like LumineticsCore, hinge on both robust real-world data and sustainable reimbursement. Dr. Abramoff and his co-authors throughout the years have played a crucial role in collecting and supplying the data essential for ensuring reliable evidence guides the development and application of these technologies. Following the data requirements, sustainable reimbursement strategies become vital. Without such financial frameworks in place, innovative products cannot thrive, adversely affecting patient outcomes, healthcare equity, and accessibility.
Dr. Abramoff emphasized the urgency of this situation, saying, “Without sustainable reimbursement, widespread adoption of healthcare AI wouldn’t be possible. There is a ton of noise out there about AI, and we need to stop talking about it in terms of ‘potential,’ as the scientific evidence is now in and actionable; we need to focus on adoption at scale because people’s vision and lives are at stake.”