In the last few years, artificial intelligence (AI) has gone from a scarce novelty to an almost pervasive technology in the healthcare industry.
Hospitals, physicians’ offices, insurance companies and clinics are leveraging AI in countless ways. Today, AI is used to accelerate drug discovery, streamline administrative tasks, devise treatment optimization plans, analyze medical images and patient data and so much more. The early benefits are clear: AI is proven to help improve patient care, streamline operations and advance medical research across the healthcare spectrum.
Growth in adoption is showing no signs of slowing down as countless emerging startups, investors and established industry behemoths pour billions of dollars into innovating the next greatest AI tools and applications. The Cleveland Clinic projects that AI in healthcare will become a $188 billion industry by 2030.
The future of AI in healthcare is bright. But to support its continued adoption, emerging tech innovators and established health systems will still face operational, legal, financial and regulatory challenges.
Buchanan recently brought together several industry leaders with expertise at the cross-section of healthcare and technology to discuss AI’s growing role in the industry. The panel included Harsh Dharwad, President and CEO of NK Digital Health Solutions and AMP3D; Paul Grand, CEO of MedTech Innovator; Dr. Richard Shannon, MD, Senior Vice President and Chief Quality and Medical Officer at Duke Health; and Kevin Passarello, Buchanan Shareholder and Co-Chair of the firm’s Advanced Technology Group. View the panel discussion recording here.
Here are eight key takeaways from this discussion:
New AI capabilities must fit into existing clinical workflow
One of the most significant predictors of success for new healthcare AI capabilities will be their ability to seamlessly fit into the current clinical workflow at health systems across the U.S. Emerging AI undoubtedly has incredible implications for countless applications. But if clinicians have to significantly alter their normal workflow to use it, adoption will likely stall. Innovators that work closely with clinicians to tailor their AI offering to existing workflow will likely see the highest rates of adoption and success.
Successful new AI capabilities will solve existing problems
Many of the most successful AI applications today were developed in response to existing and pervasive problems in the healthcare industry. For example, there is massive room for improvement in predicting fall risks among hospital patients. AI has since been developed to analyze the data of patients who suffered falls over the last several years to identify the similarities and key predicting factors. With a more sophisticated understanding of patients with fall risks, hospitals have since eliminated an enormous amount of wasted effort and cost. AI developers who follow this approach to solving existing problems will be the most successful.
Impact must be measurable to drive adoption of new AI capabilities
Hospitals and health systems need to be able to economically justify their investments in AI. As a result, technology companies must be able to measure and articulate the financial value and impact of their offering. Many technology startups today lack an understanding of how they are going to eventually sell their product to providers. A better approach is to identify what measurable impact you are able to provide before the technology is fully developed. This way, technology developers will be better prepared to articulate their value to healthcare providers when the product is ready for commercialization.
Healthcare is facing a data overload
Advanced data analytics is a powerful tool that can transform the way doctors diagnose and treat patients. However, physicians today are facing an overload of clinical data that makes it difficult to find insights and discern which information is most relevant. New platforms are emerging that enable medical professionals to utilize data in the ways that serve them best. They can easily find the data and analysis that are relevant to their practice, enabling them to more quickly identify insights that move the needle for their patients.
Staff buy-in will be essential to driving adoption
Another driver of success for emerging AI capabilities will be securing the buy-in of existing clinical staff. Innovators should closely consult with clinicians to gain insights into where and how their capability can be used. When rolling out new technology, it will be important to take feedback from the personnel who will be using it in the field. Implementing effective and efficient staff training sessions will also be essential to boosting adoption.
Emerging startups must collaborate with established healthcare institutions
Collaboration between established healthcare providers and innovative technology companies will be essential to supporting the advancement of AI. While nimble startup businesses may be well suited to develop cutting edge technology, they will need the guidance and support of institutions with decades of experience in the healthcare space to ensure these new products are created in ways that will be useful and impactful. Further, many of these emerging companies may end up as acquisition targets, and creating close relationships early on in their development may be in their long-term best interest.
Regulatory support will be essential to success
Regulators at the U.S. Food and Drug Administration (FDA) are working tirelessly to stay up to date on the rapid AI advancements in the healthcare and life sciences industries. New AI capabilities will need the support and approval of regulators in order to be commercialized. Healthcare providers and technology companies should work closely with regulators to help them understand the wide range of new capabilities that are coming to market.
Ethics concerns remain and must be addressed
Those on the front lines of developing AI capabilities for healthcare applications will need to ensure this new technology is ethical and equitable. Regulators are currently working on a framework to help set ethics guidelines and rules for the industry. In an industry like healthcare where lives are at stake, algorithms must be closely monitored for biases and weaknesses. Data security must also be prioritized to protect patient privacy.
Helping AI reach its fullest potential
AI has a promising future in the healthcare and life sciences industries, and there are countless life-saving applications currently being developed. However, healthcare providers, payers and technology developers will need support to ensure these powerful capabilities reach their full potential. At Buchanan, our Advanced Technology and Healthcare attorneys have deep industry experience and are following these developments closely. Our attorneys can help the industry navigate this rapidly evolving landscape to bring more powerful AI capabilities to market in ways that improve lives.
Authors:
Kevin Passarello, Shareholder
Email: kevin.passarello@bipc.com