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Essential innovation lessons in healthcare – Part 2

Essential innovation lessons in healthcare – Part 2

“Part of me thinks that innovation, real innovation in health care delivery, needs to happen from the bottom to the top.”

Malcolm Gladwell, author

As we discussed last week, it is more obvious than ever before that innovations in healthcare are needed, and artificial intelligence is an important part of that innovation ecosystem. There is a valuable dividend in intertwining artificial intelligence and healthcare innovation with projects, agendas, and publications on a day-to-day basis.

Innovation can be defined as [innovation = invention x value], with the value either as commercialization with revenue or as lives saved or improved. Innovation is not invention nor research. The ideal innovation, then, is an invention or new idea that brings high value.

We discussed a few useful tenets of innovation last week, and here are several more for a list of ten of my favorite tenets:

Do not be afraid of failure
In medicine, failure is rarely tolerated. In innovation, the mindset needs to be very different, in that a “failure” is acceptable as part of the innovation process to have a minimal viable product (MVP). The important strategy in innovation is to accept failure as a lesson learned and pivot to get back to a trajectory to success.

Borrow existing solutions from other domains
Innovation can be about borrowing ideas from other domains and applying these ideas to problems in your own setting. An example is the use of deep learning experience from ImageNet for medical images, and another case is applying the digital twin concept from manufacturing to be used for healthcare.

Use design thinking as a start of an innovation
Too many ideas in innovation are not rooted in identifying the problem first. This is especially true with devices and apps – as well as AI ideas in healthcare – where often the technology does not serve a true identifiable need for caretakers and/or patients. It is often difficult to achieve adoption if the innovation does not address a problem.

Convene a multidisciplinary or even transdisciplinary team
The Medici Effect, as coined by Frans Johansson, is when diverse disciplines and cultures, as well as concepts and perspectives, intersect and inspire innovation. This multidisciplinary approach can even advance to a transdisciplinary one that includes patients as this perspective is often underleveraged for a healthcare innovation.

To innovate, sometimes one has to “unlearn”
It is sometimes difficult to innovate in an ecosystem or situation without undoing or unlearning what is already in place. Rather than reengineering an existing solution in healthcare, sometimes introducing a relatively disruptive innovation that has little or no resemblance to any existing solution to the problem is a good approach (think iPhone).

Avoid escalating commitment to an innovation unlikely to succeed
Many innovative products and services have owners who are very reluctant to pivot and/or forgo their ideas in the face of obvious failure or lack of progress. It is good to have a diversity of opinions about one’s innovation, including naysayers, to improve and mature the innovation idea early in the process.

Appreciate the importance of timing
Even more important than a team and dynamics or an idea and its relevance, according to Bill Gross the entrepreneur, is timing of the innovation entry in the market. In addition, sometimes it is more favorable to be the second entry into the market rather than the first, as one can “slipstream” behind the frontrunner and learn from its mistakes.

There are obviously many more tenets of innovation, and it is good to have such a list as a reminder. It is also of great benefit to read and learn about innovation concepts from a diverse group of experts and domains.

Dr. Anthony Chang’s book is available on Amazon now! 

Intelligence-Based Cardiology and Cardiac Surgery Intelligence-Based Cardiology and Cardiac Surgery: Artificial Intelligence and Human Cognition in Cardiovascular Medicine (Intelligence-Based Medicine: Subspecialty Series) Data Science, Artificial

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Written by Dr. Anthony Chang, the Medical Intelligence Compendium and Glossary provides a comprehensive oversight into the terms and concepts that are crucial to the growing field of Artificial Intelligence in healthcare. Subscribe for a free copy today!

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