The Road to AI Use in 2023
As we wrap our series on the 2023 trends in healthcare AI, we hear from Ferrum Health’s Head of Market Development, Keith Chew.
For more than 40 years, Keith has served as a healthcare thought leader and subject matter expert with direct experience as a Consultant, Hospital VP of Physician Network and Ancillary Services, Director of Practice Management, Practice Administrator, and Chief Executive Officer for large and small medical practices. Over the past 22 years, Keith has developed a specialty practice focusing on hospital-based practices, especially medical imaging and radiology.
He has demonstrated expertise assisting physicians, hospitals, and health systems with practice leadership solutions, management, operations improvement, governance, strategic planning, and strategic positioning. Keith holds multiple degrees and is a past president of the RBMA. During his career, he has been a guest speaker for the RBMA, HFMA, ACR, MGMA, Becker’s Hospital Review, The Leader’s Board, multiple state radiology societies, RBMA Chapters, and other professional organizations across the country.
What hasn’t been said about Healthcare AI. It’s going to replace entire medical specialties; it’s going to solve the problems of inequity; it is going to make medicine error-free; it will predict disease well in advance of symptoms so it can be cured. If you believe all of the hype about Healthcare AI, you see it as a true panacea for the world. But the reality is that Healthcare AI is nascent. Due to the disconnect between the hype and the truth, many of the current approaches to AI utilization seem to be a solution looking for a problem to solve. That is not to say that there are not exceptional algorithms that have been developed that aid in diagnosis, monitoring of or even predicting a patient’s condition, but the industry has very poorly evaluated, deployed, and utilized the AI tools developed thus far.
Most institutions deploying AI solutions have not fully developed a long-term strategy for this emerging healthcare technology. Far too many organizations are not considering the full impact on resources with individual algorithm deployments instead of establishing a platform strategy. Even those organizations trying to develop a platform strategy are not understanding the necessity of private deployment when you consider the cybersecurity risks, human resource utilization for interface development and maintenance, ease of algorithm evaluation, and the list continues. Far too many organizations are just wanting to market that they have deployed and are utilizing AI in their institutions without any true understanding of the value or the improvement in patient care quality that is or, in many cases, is not being provided.
Institutions need to begin to critically think through their strategy of AI evaluation, deployment, and utilization and not be caught up in the hype. Look for an AI Partner that will be able to meet the IT deployment strategies of the institution, whether they are private or public network approaches; look for an AI Partner that is AI solution developer agnostic so that all AI solution developers can be positioned, evaluated, deployed, and utilized on that AI Partner’s platform. Start thinking about Healthcare AI from a Quality Deployment perspective to allow the institution to ascertain the value the AI solution brings to the institution and the patient population before making long-term financial investments in the AI Solution; realize the unintended consequences on provider productivity, patient care quality and over-all value when a poor performing AI Solution in positioned within an institution and the financial impact brought not just from the cost of the solution, but also the resource utilization impact just noted.
Healthcare AI is in its infancy and needs to be viewed as such by all institutions considering its evaluation, deployment, and utilization. If those institutions take the time now to consider the consequences, both intended and unintended, on resources, patient care, and the future of healthcare with the deployment and utilization of AI Solutions, then their paths will be far less strewn with waste and disappointment in the technology; those institutions will be considerably more productive and successful due to their efforts and be the leaders in the ever-changing healthcare environment.
You can read the other article in our AI 2023 trend series, and don’t forget to join us next week as we hear from Ferrum’s Head of Market Development.
That’s a wrap for our series on healthcare AI trends in 2023.
We’ll leave you with an invitation to learn more about the benefits of using an AI Hub to manage multiple applications across your clinical needs and offer you a personal demo of Ferrum’s platform and growing AI catalog.
If you have AI tips, suggestions, or resources you’d like to share, leave us a note below, and please feel free to suggest topics you would like to see covered in future posts.