Photo: UConn Health
Dr. R. Dirk Stanley, chief medical information officer at UConn Health, a five-hospital health system based in Farmington, Connecticut, is not the only clinician to complain about workflow problems. But he’s one that’s been doing something about it.
In his role as CMIO, Stanley and his team have redesigned UConn’s clinical workflows to better serve its clinicians and their patients. And they’ve worked to reimagine electronic health records and deploy artificial intelligence and automation to ensure mission-critical IT is best supporting those new workflows.
We interviewed Stanley to understand the main problems with clinical workflow as he sees them. He offered his advice for clinical workflow design and perspective on how AI and automation can help streamline efficiency and improve the provider experience.
Q. What are the problems with clinical workflow today? And what part does health IT play?
A. The biggest challenge is that clinical workflow is complex, requires a great deal of attention to detail, and often is interdependent on the who, what, when, where and why of other workflows. So, getting them right usually takes more time and effort than most people plan for.
Fortunately, the national health IT community is responding by increasing the support for applied clinical informatics, and recognizing the importance that these “clinical architects” play in working with the frontline clinical staff and other billing and HIM stakeholders to design best practice workflows, and secure staff alignment and buy-in before beginning a configuration or build.
Q. What are your personal views on clinical workflow design? Where does one start? What are the best approaches?
A. Good design starts with good blueprints (#BlueprintsBeforeBuild), hence the need for clinical architects (applied clinical informaticists) to really understand the current state and needs of all stakeholders, and then design a solid, efficient and user-friendly future-state workflow that meets all of the clinical, legal and financial needs of the organization.
It starts with understanding the current state, and learning how to quickly document it so an elegant future-state becomes apparent and tangible, even before it’s built.
Q. How do you make healthcare information technology like EHRs and AI fit into the workflow design that you create?
A. Workflow drives everything, so I always begin with workflow. Once I know the current-state and future-state workflows, I know the tools needed to support it both inside and outside of the EHR. This is a common source of confusion, thinking it’s only about the tools inside the EHR.
Just as important are the tools outside of the EHR, so it’s about keeping them all in alignment and pointing them all to good patient care. AI is a new development that fits nicely into the general analysis and change management paradigms I use for examining technology and developing solutions, so AI just becomes another “role” in the procedures and swim lane-type diagrams of my workflows.
Q. Please offer an example of a bit of clinical workflow design that you have done at UConn Health and how it has helped clinicians. What has been the outcome of your work?
A. At UConn Health, I’ve helped to streamline workflows all across the organization, from our ED to the ICU and other inpatient areas, to perioperative areas and ambulatory clinics. Admission, rounding, discharge, visits, pre-procedure, post-procedure – I work on them all, using my blueprints to translate the needs of the end users into concrete deliverables, so they can visualize and agree to the future state before we begin to build it. It’s very satisfying work.
Some of my favorites are the complex, high-risk workflows. With a previous employer, I once streamlined unfractionated heparin titration, entirely from scratch. Unfractionated heparin titration is a very complex workflow, to say the least, so I was very satisfied when it was built and implemented and adopted across the entire health system as a best practice.
Ultimately, this design (clinical informatics) work helps to reduce clicks, reduce frustration, reduce variation, improve safety and improve patient care.
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