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Here’s a thought experiment, I think what Einstein called a “gedankenexperiment”, and that is, what if … Take a time machine back ten years ago. What if we had started automating workflow instead of data? What an absurd idea. I mean, how is that possible? Don’t we have to have all this data? Well, in fact, I’ve done some consulting internationally, and there are a lot of companies that have watched what has happened in the United States over the last couple of decades, and they’ve kind of, just like in the model of you skip the telephone poles, and go directly to satellite phones? Some of them are saying, “You know what? What we need to do is understand the workflows first, and then only gather the data we need to accomplish the workflows.”
Today, we have all of this data and all of these databases, basically, EHRs are kind of databases with UIs slapped on them. We have this data, and people are saying, “I don’t want all this data, I want actionable data.” Whenever you hear the word actionable data, think workflow technology.
This is consistent with the famous advice from Covey, 1989, “Begin with the end in mind.” This is exactly the way industrial engineers are trained. You go into the factory, you figure out, “Here is the product, in the box, that’s being sent to someone. Now we work backwards.”
Down at the bottom here we have data, which is a very important resource. It costs money to obtain it, it costs money to stick it into the workflow. On the right, here, we have goals and benefits. That’s the end in mind. We’re trying to lay down, across all of this data, a whole bunch of workflows, to take advantage of it.
If we had done it differently, we would have done it this way. We would have started with the end in mind, we would have said, “What is the penultimate step, before the end, and what is the data that we need?” Then you say, “What is the step before that, and what is the data we need?” Then you finally get to where you are, or where you typically would be.
Instead, what we have is this situation. We’ve got all of these databases out there, we’re collecting all of this data at the point of care, and we’re trying to lay down on top of it a set of workflows to take advantage of it. It’s a lot harder to lay down all this patchwork workflow, kind of whole cloth, without following that end to start model.
What order makes sense? I’d argue adding data to workflow, but we’re kind of stuck, right now, with adding workflow to data. That means we need extremely flexible workflow technology to adapt, to lay down, to compensate for and take advantage of all of this existing data investment. This is an excellent argument for structured messaging, for example as a platform. A platform is a set of constraints and resources that you can just count on, when you’re building some other system on top, and that is the workflow platform that, I believe, in the next five years, we’re going to see dramatic investments in a variety of workflow platforms, kind of laid down on top of the data systems we have in place, and structured messaging is one of them.
Take me to the next post in this series: Workflow Engineering Patient Experience & Engagement.