How to close the doctor-data scientist-bioengineer divide
Medical Intelligence 10 (MI10)
Physician-led healthcare artificial intelligence strategy and education advisors
This past year has shown the world how vital technology is to society and there’s no looking back. We’ve seen some impressive innovation in healthtech and ensuring that adoption continues to accelerate is paramount to improving medical care for all, but that will require education. While technology is becoming commonplace in some areas, it’s still an add-on in others and there needs to be greater thinking about how technology can be introduced earlier.
The digital transformation strategists are telling us that it requires cultural change, process improvement, technology, and workforce upskilling. But, more importantly, digital transformation, particularly in applications of artificial intelligence in sick care, requires close collaboration between multiple clinical and technology stakeholders including not just computer scientist but bioengineers too.
Why?
But sick care technologists are from Venus and doctors are from Mars. How do we get them to rotate around the same sun and increase the centripal forces between them? How do we close this part of the digital divide?
I recently received this note:
"I'm extremely interested in healthcare & tech. Can you give me advice on how to best set myself up to combine both & create impact as I am in the beginning stages of this path?"
Here's how we can close the divide:
17. Make it easier for clinicians to connect with data scientists at universities, professional societies, local and regional ecosystems and social media.
18. Include clinical subject matter experts in bootcamp or product development teams
19. Intregrate bioengineers and data scientists into care teams
20. Improve knowledge transfer programs via sabbaticals, co-ops, internships and apprenticeships
In the case of bioengineering-clinician gaps, opportunities for improvement include:
1. Integration of clinicians into the project teams
2. Biomedical engineering curriculum reform to include technology commercialization and data science
3. Creating objective measures of pain
4. Rethinking the mission of biomedical engineering specialty societies to encourage more transdisciplinary education and training
5. Updated information about the outcomes of bioengineering undergraduates applying to medical schools (about a one-quarter to one third of graduates)
6. Better non-invasive, non-opioid treatments for chronic pain
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7. Improving results of treatment of back pain, particularly in those patients who have had multiple back operations.(failed back surgery syndrome)
8. Educational exit ramps
9. Better knowledge transfer programs between academia and industry
10. Destroy innovation silos
11. Remote monitoring and management of pain
12. Better clinical decision support software and treatment guidelines and monitoring
13. Biosocial and behavioral care management platforms
14, Decentralization of care to address inequitable access to scarce and maldistributed pain management expertise
15. Primary care and patient education and training
Here is my data science-doctor collaboration wish list:
1. Start by being a problem seeker, not a problem solver
6. Stop frying doctors with your products and eliminate their burnout impact factor.
9. Create a whole product physician non-clinical career platform
The core of closing the divide will be interprofessional education and training, an organizational culture of innovation and digital transformation, and experience working as teams based on trust.
Hope is not a strategy. Technology alone will not get us out of the sick care mess or the global warming mess. People will; but only if they play nice with each other.
Arlen Meyers, MD, MBA is the President and CEO of the Society of Physician Entrepreneurs on Substack and Editor of Digital Health Entrepreneurship