Basics of medical AIntrepreneurship

So, you are a technologist, data scientist or health professional?who wants to be the founder of an AI company?i.e an AIntrepreneur?

Or, maybe you are a cross trained academic doctor-data scientist intrapreneur interested in leading the newly created AI department in your medical school, i.e an AI intrapreneur?

An AIntrepreneur is someone who pursues opportunities in healthcare AI under VUCA conditions?with the goal of creating user, stakeholder or shareholder defined value through the deployment of innovation using a?VAST business model with goal or achieving the quintuple aim.

The process can be from outside in i.e a vendor looking for customers in health service organizations, or, it can be an intrapreneurial process, started by employed physicians or other sickcare professionals, interested in creating value for their employers, and eventually, the patients they serve. As such, your go to market , business development, business model and dissemination and implementation strategies will vary depending on the roadmap.

1. Inside founder/ inside customers
2. Inside founder/outside customers
3. Outside founder/ inside customers
4. Outside founder/outside customers

Whichever box you are in, answer these questions.

Here's what medical AIntrepreneurs should know and know how to practice:

1. Regulatory affairs: ?While some startups are steeped in the regulatory terrain, achieving regulatory approval is not always straightforward or well-understood; a recent survey by the nonprofit Digital Medicine Society (DiME)?reported?that 25% of digital health developers didn't know whether their product should be regulated; of those who did know regulation was needed, 75% didn’t know the optimal pathway.
2. Intellectual property: Beyond the traditional practice of litigation, opinion work and proceeding before the U.S. Patent and Trademark Office, attorneys are more frequently being engaged by clients confronting the impact of artificial intelligence technology on businesses. Unlike many intellectual property issues that percolate up from the lab bench to the C-suite, interest in developing a strategy for addressing AI is being driven at the highest corporate levels. A panel at the 2017 World Economic Forum in Davos-Klosters, Switzerland, for instance, focused on AI as a disruptive technology that will drive productivity as it continues to make its way into enterprise systems and computing platforms.

Reimbursement : Viz.ai demonstrated to CMS a significant reduction in time to treatment and improved clinical outcomes in patients suffering a stroke. Viz LVO has been granted a New Technology Add on Payment of?up to?$1,040?per use in patients with suspected strokes.

1. Product and project management
2. Ethics and Law: To fully achieve the potential of AI in healthcare, four major ethical issues must be addressed: (1) informed consent to use data, (2) safety and transparency, (3) algorithmic fairness and biases, and (4) data privacy are all important factors to consider.
3. AIntrepreneurial finance: Raising capital is for many startups a necessary evil. Sometimes even a recurring one. It’s a lot of work and it takes your focus away from the actual task at hand – Building a successful business. Fundraising is difficult and even exhausting. If you are raising capital for an AI startup you might find the job even more difficult than usual.
4. Sales and marketing: While the basic structure of all marketing programs has similar foundational pillars, such as buyer personas,?content,?SEO, buyer’s journey, etc., marketers in the B2B healthcare space may face unique challenges.

Dissemination and implementation: Dissemination?refers to the distribution of an intervention or innovation to a specific audience. Manuals, presentations, and websites are examples of efforts to disseminate information about interventions.

More recently, there has been greater recognition that the broader context into which an innovation is introduced has a substantial influence on whether they are successfully integrated into routine care. This recognition has led to a shift in focus to?implementation, the integration of a new practice within a specific setting or context. Implementation involves the use of strategies to adopt and integrate evidence-based interventions and change practice patterns within specific settings.

1. Leaderpreneurship: After?studying?proven masters at fostering organizational innovation for over ten years, researchers have identified the heart of the difficulty. At the core of leading innovation lies a fundamental tension, or paradox, inherent in the leader’s role: leaders need to?unleash?individuals’ talents, yet also?harness?all those diverse talents to yield a useful and cohesive result.
2. Organizational change management:
3. The people part of AI
4. Problem seeking: Since sick care is a multi-sided market, you will have to satisfy the jobs, pains and gains of many customer segments including not just influencers, like doctors, but end users, payers and producers and policy makers as well.
5. Scaling your venture: People, strategy, execution, cash
6. Non-clinical careers
7. Exit strategies: Most startup founders and small business owners are well aware of some of the flashier ways to sell a business: the initial public offering (IPO) and the acquisition get a lot of attention. But those?aren’t the only business exit strategies, and they may not be good options for every entrepreneur.

But, when it comes to using artificial intelligence in sickcare, the process is even more complicated and involves not just?ideation?(problem seeking) and?invention?(problem solving) but?integration?in legacy IT systems and workflows and?implementation?by end users and staff.

Doing so means you will have to find the answers to these basic questions.

Good luck with your AI venture.

Arlen Meyers, MD, MBA is the President and CEO of the Society of Physician Entrepreneurs and an advisor at MI10 and ABAIM