Balancing Innovation & Patient Safety
“Patient safety is non-negotiable, but stagnation is not an option either,” as the well-known adage goes. Incorporating AI in Healthcare requires the assembly of a cross-functional team composed of clinical, technology, and legal experts. This collective knowledge helps to create a framework for rolling out new technology responsibly.
“Coming together is a beginning, staying together is progress, and working together is success,” as Henry Ford wisely noted. Indeed, hospitals should actively join communities of like organizations to divide and conquer the challenges for experimentation in healthcare, following these three essential criteria:
- Abide by the law
- Set clear goals and guardrails
- Be prepared to pivot quickly if concerns arise
Overcoming Provider Resistance for Rapid Experimentation
Resistance to change is perhaps one of the most formidable obstacles when it comes to adopting new technology. The key to overcoming this resistance is to clearly articulate the “why” behind the change. How does this innovation benefit patients and providers alike? Transparency is vital in measuring and monitoring the progress of new initiatives. This speaks directly to the need for AI co-development companies to align their solutions with the real needs and goals of healthcare projects.
Data-Driven Decision Making
“What you plan, you can measure; what you measure, you can improve,” suggests Sheryl Sandberg, the COO of Facebook. In an industry where data is often both the challenge and the solution, how do you move projects forward? One must establish the method of calculating the problem at hand and have clear metrics to measure success. It’s crucial that the project is part of a strategic priority, as Healthcare AI Software Development will require cross-functional sponsorship and support. Having a committed sponsor can significantly impact overcoming any roadblocks that come your way.
Deciding What to Scale
Pilot projects often become long-term experiments that never reach fruition due to a lack of a well-defined process. Creating templated processes and having a deployment pipeline can accelerate the transition from research to production. Meeting compliance and guardrails ensures that a pilot can move beyond the experimental phase, unlocking Healthcare AI ideas that can genuinely change the landscape of healthcare delivery. Learn more about how we establish these processes at Sphere.
Learning from Failure
Thomas Edison once stated, “I have not failed. I’ve just found 10,000 ways that won’t work.” The sentiment rings true in healthcare, where rapid experimentation can often mean rapid failure. However, such failures are not the end but rather steppingstones to better solutions. On the flip side, prolonged failure without any adjustments can become detrimental.
Conclusion
Building a culture of rapid experimentation in healthcare is not a straightforward task. It requires a balanced approach to innovation, a strong resistance to provider concerns, robust data-driven decisions, and the courage to scale or pivot as needed. The key to unlocking this potential lies in collaboration—between cross-functional teams within a healthcare organization and with external experts.
If you’re looking to take the plunge into healthcare technology innovation, Sphere Partners is here to co-build and co-develop bespoke systems and digital solutions with innovative hospital partners. With our extensive experience and expertise, we can help you navigate the intricate landscape of healthcare technology responsibly and effectively.
