Alexis is director of content at AIMed, with responsibility for the research, development and delivery of products across events, digital and publishing. A highly experienced events executive with a career focus on the intersection between healthcare and technology, he is also a school governor leading on teaching, learning, and quality of education.
“No journey is too long with the right company, the right mindset and the right determination to kill it till you win it.”
Nishant Bhat, artist
We discussed last week the steps of the journey towards a center of AI in a health system. Here are 5 additional considerations for such a center to become a long term reality:
Building an internal AI team with process for projects
For a successful AI in clinical medicine project, an internal team that consists of data engineers, data analysts, user interface and web application experts, data scientists, as well as clinicians with fundamental knowledge of informatics, digital medicine, and clinical research, are all essential members of a team. Too often, a single or small group of data scientists are consumed with tasks that are really much more efficiently managed by other members of this team.
Measuring outcomes of AI projects
The coalition of clinicians and data scientists who are interested in AI projects will need to contemplate how to measure the outcomes of these projects, including performance metrics as well as clinical impact, cost savings, and academic reputation. As there will be a range of focus and stakeholders, the outcomes will then need to reflect this heterogeneity of people and processes in AI projects.
Devising a business strategy and plan
The long term prospect of an AI center will depend on a robust revenue generation portfolio and astute budget management. Income sources can include philanthropic agencies, educational and training grants, business grants, meeting revenues, consultation fees, etc. as well as projected cost savings from AI-enabled processes in the health system. It is also possible that the AI center can be coupled to an accelerator to launch AI in medicine startups that can mature into companies.
Building regional and national/international presence
In order to establish a reputation for a nascent center of AI in medicine, it is essential to have a presence at a regional and even national or international level. This effort involves having champions at various meetings of AI in medicine, as well as having publications in the relevant journals – and especially ones with high impact factors. An additional means to achieve a good reputation is to be the progenitor of collaborative group AI projects.
Networking with other centers
There are very few such centers of AI in medicine around the world, with the existing ones having formed a coalition called the Alliance of Centers of AI in Medicine, or ACAIM. This group of over 40 centers from more than 10 countries meets once a month and the agenda includes an update from each center, as well as special topics that are particularly germane to this group. There is also a pediatric group called the Pediatric Centers of AI in Medicine, or PCAIM.
In addition to the center of artificial intelligence in healthcare discussion, many other topics will be discussed at our in-person AIMed Global Summit, taking place on May 24-26 of this year at the Westin St Francis in San Francisco. Representatives of many centers of AI in medicine will be participating at this meeting, in addition to the diverse attendees. Find more information here.
