Artificial Intelligence (AI) has incredible potential to transform healthcare; however, this requires a strategic approach in terms of adoption and implementation. The concept of an AI platform provides a scalable solution, with the potential for long-term implications for the field. Such a platform allows for collaboration across various health system stakeholders, with AI impacting the workflows of many different departments and personnel.
In his book “Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again,” author Eric Topol presents a positive view of the integration of AI in healthcare. He cites numerous benefits, both current and potential, that AI brings to medical practices, including improved patient-doctor communication, cost savings, and advancements in areas such as diagnostics and treatment planning.
For effective AI adoption, healthcare systems now aim to take a holistic approach instead of focusing only on specific diseases or conditions. This avoids creating data silos, limiting scalability, and allows for integration across the entire healthcare system. The choice of approach depends on the healthcare system’s individual needs and circumstances, which can range from point solutions focusing on specific tasks, to AI marketplaces offering a variety of different solutions, and to AI platforms providing scalable, centralized infrastructure. Expertise is required for effective navigation and implementation, particularly considering the potential challenges such as variable quality and system compatibility.
The application of AI in healthcare isn’t without hurdles. These challenges range from dealing with the overwhelming amount of healthcare data available (often plagued with poor formatting, inconsistent protocols, and lack of access among some personnel), to coping with the vast amount of irrelevant, unstructured, and/or unreliable data (known as data ‘noise’). Other challenges include integrating AI solutions seamlessly into existing systems and workflows and managing them with limited resources.
However, these obstacles should not deter healthcare leaders from leveraging the potential of AI. An effective AI strategy can streamline the adoption and management process. The strategy should revolve around selecting the correct AI platform, one that facilitates organizational growth and creates a strong governance framework. Also, it should involve scrutinizing the AI partnership, with questions focusing on FDA-approved algorithms, the support for all AI algorithms (including those not created by the partner), the run protocol of the algorithms, safeguards for clinician involvement in decision-making, and the 24/7 monitoring of AI’s performance and data drift.
In conclusion, while AI’s ability to revolutionize healthcare is undoubtably promising, it requires a thoughtful, strategic, and comprehensive approach to make it a reality. Focusing on scalability rather than isolated applications, integrating the technology seamlessly into the current workflows, managing it prudently, and selecting the right platform and partners are all critical steps to harness AI’s substantial transformative power.
