Man + Machine: Made for Each Other

Matthew Wickesberg

The Robots Are Coming … to Simplify Your Workflow

Right now, there’s some fear around data-driven solutions. I often hear customers wondering: Are computer algorithms going to take over the role of people?

The answer is simple: Nope. The reason is simple, too: Data is going to augment these roles, not obliterate them.

I predict that clinicians and computer analytics will work well together, with data-driven insight leading the way to more efficient workflow. In my area of expertise, radiology, I foresee radiologists identifying and interpreting the unique complexities of a patient’s situation that algorithms can’t see, to make sure each patient gets the best care on a personal level.

Analytics will simply uncover more opportunities for radiologists to make this care happen more quickly. The key to living in harmony with data-driven solutions is developing algorithms that help clinicians make smarter decisions in fewer steps. And it starts at the workflow level.

The technical capabilities of today’s imaging systems, EMRs and more can crunch a lot of information and give you some interesting insight. But if you can’t inject that intelligence into the day-to-day operations of your healthcare system, you’re missing the real opportunity.

Because it’s all about outcomes, right? To get great outcomes, you need to take action and solve real problems. Analytics need to be geared toward a specific daily workflow, or it won’t help you do that.

If you gear your analytics toward a workflow, with a specific outcome and set of insights in mind, then using that analytics solution becomes a habit – and the data can deliver real-time insight to solve a specific problem.

For example, an analytics solution that focuses on the daily workflow in the X-ray department will find common patterns that highlight inefficiencies. The data can then be applied to improve the workflow. Let’s say you zero in on a trend of X-ray imaging errors that are causing a need for repeat imaging. When you frame your analytics within a workflow, you can filter data and drill down into it until you discover a set of images that you can use – say, to help train technologists and reduce retakes.

What makes these workflow-level solutions successful is integration. An analytics solution should seamlessly integrate information from all IT devices involved in care so clinicians don’t have to jump from tool to tool or dashboard to dashboard to improve the clinical and operational experience in the X-ray department.

One of our customers built what they call a “Wall of Analytics” around operational efficiency – specifically, how patients flow through their hospital system. It’s like a command center or a heads-up display in a fighter jet that guides them in the right direction. It gives them real-time information so they have the best insight into key metrics such as patient wait times, and it delivers recommendations on what to do next. The analytics solution helps them alleviate bottlenecks where patients wait too long to see their doctor or get their tests, helping to improve operational efficiency throughout the entire hospital system.

In the next five to 10 years, I expect that integrated data-driven solutions like this will become the norm. In my experience, focusing on day-to-day operations makes analytics apps and the people they support more valuable by solving real problems and delivering real results.

And there’s nothing to fear about that!

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