ai in healthcare

Will artificial intelligence deliver on its promise in the healthcare sector?

Undoubtedly, the healthcare sector is under pressure. So much pressure that there’s little or no room in the operational process to test and implement innovative techniques or ideas. And this, despite the fact that logistics and facilities processes would actually benefit greatly from some process optimization. With the sizeable challenges that the industry has to face nowadays, how can we make the most out of it?

AI doesn’t signal the end of the human factor in healthcare

It’s safe to say that in healthcare everyone is a bit tired of pilot projects. Especially in the field of artificial intelligence, pilots are often well-intentioned, but are realized based on a technology push or as a stand-alone project. As many as 40% of all initiatives fail because they are implemented outside the context of the actual processes. When looking for solutions that really make problems disappear into the background, the reasoning must be based on the value created for the target group.

We are convinced – supported by our experience in this field – that AI actually adds value for staff in the healthcare sector. And we’re not talking about replacing people with machines, because that is absolutely out of the question. Healthcare staff possess creativity, compassion and empathy, things that robots wont replace!

Healthcare logistics and process optimization are, however, areas where AI can be applied very effectively. Planners and logistics staff can be relieved of routine tasks, freeing up time for other work. While, health systems can leverage machine learning and predictive models to improve patient flow for different departments throughout the organization as well as improve clinical pathways. Improving hospital patient flow results in reduced patient wait times, reduced staff overtime, improved patient outcomes, and improved patient and clinician satisfaction among other things.

Examples from practice

In this video (recording of the webinar we held earlier this year in collaboration with Quint) Rob van Zoest takes you into the world of artificial intelligence in healthcare. It’s a video in which real-life examples are discussed, not complex theory. Will artificial intelligence deliver on its promise? Or will we have an endless sequence of trial and error?

We examine the first successful applications of AI in healthcare with, for the time being, the focus on the following two examples:

  1. Optimizing the machines that produce medication rolls. How do you optimally configure such a machine? How do you raise the current level of optimization and how can you increase the percentage of automatically-handled prescriptions to save costs?
  2. Optimizing the supply chain at a company that provides medical devices and pharmaceuticals. How can we use deep learning to predict demand based on historical data or even based on comparisons with other products and trends? How do we ensure that an AI model is built in such a way that it gives output that end users can both understand and use?

What is the next step for AI?

In addition to healthcare logistics and process optimization, in the years ahead, AI could be the solution to staff shortages in the healthcare sector. Models can be developed for intelligent rostering which would result in a better match between (the level of) healthcare demand and healthcare provision. This would enable healthcare departments or organizations to create room in staffing levels, resulting in more breathing space. Another opportunity in healthcare is to optimize or regulate fully (or partially) plannable environments, such as bed occupancy, OR occupancy, and MRI occupancy.

Artificial intelligence comes into its own in point solutions. A model can be used in a very targeted way by tackling a small, specific problem. In this way, you create added value where it’s needed, which is much more efficient and feasible than optimizing a very broad process with AI.

By solving a specific problem, people see the added value in their own work process, and it’s expected that this will accelerate adoption on the work floor as well. At some point, people will start thinking more broadly about more or different AI applications, so a point solution can thus act as a catalyst for even more innovation.

Why this video on AI in healthcare?

It’s essential for healthcare organizations to embrace artificial intelligence. We don’t have time to develop and implement at our leisure – the issue is urgent! AI is no longer a vague theoretical formula, but a hands-on application. A way to take your process further and benefit from the successes this brings. We are currently in a phase in which we can offer certainty: certainty in the process and certainty on the work floor.

There is no random implementation of a data platform or analysis of data, instead we have a concrete solution for a defined problem on the work floor. After all, you want to benefit from the data that already exists; is your data good enough to train an AI model on? We only take action when all the signals are green and it looks like implementation will be successful.

And, best of all: it’s easy to win over skeptics who are wondering if it will work. We can create a “digital twin” where you can experience (in a simulation) exactly how value is added within your organization.

Would you like to know how you can optimize your healthcare organization, healthcare department or logistics process?

Check out the full Webinar or meet with us by scheduling an appointment right away.

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