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Improving physician workflow starts with asking the right questions

Before implementing a new workflow, take stock of where you are starting from so you can measure if there is true improvement in the future.
By admin
Mar 15, 2022, 8:00 AM

The use of predictive analytics in clinician workflow rose by 11% in 2021 for acute care organizations. With clinician workflow an essential part of patient care delivery, some systems focus on data to improve flow. Using EHR combined with analytics can help physicians make the best decisions on patient treatment and reduce workloads for burned-out doctorsr. However, knowing where your organization can benefit from system optimization is almost as important as the data itself. 

Bob Lindner, co-founder and CSO of Veda, has a Ph.D. in astrophysics but today uses his AI and machine learning knowledge to solve costly automation problems within the healthcare system. And the need for customized automation continues to grow as the pandemic takes its toll on healthcare workers. 

Related story: Sutter Health staying agile to improve patient experience with digital automation 

Specifically, since the start of COVID-19, Lindner has noticed a change in how healthcare systems view AI. While automation used to be viewed as a technology that helps take systems to the next level, it’s now seen as a foundational tool essential in making operations run. The vast amount of technology and services on the market challenge users to decide which automation tool suits their business.

“Companies need to take rigorous measurements and focus on outcomes,” Lindner said. “When looking at a workflow and trying to improve it, focus first on the problem you have and work backwards to a tool that is the best fit. Do not get fixated on which technology you want to implement.” 

Lindner recommends that a healthcare system first determine gaps in the workflow through measurement. Then, determine what the optimal outcome is. Lindner warns that you cannot know if there is actual improvement without measuring where you started. In fact, stumbling blocks for technology transformations often happen when a client reports, anecdotally, that a process is not working. For instance, they observe wait times for the doctor are getting longer.

But if the client can’t apply an accurate number or measurement to the statement, they will not be able to prove whether an implemented fix is working or not.

Lindner also warns that implementing new automation could uncover pain points in the current system that no one was aware were a problem. 

“Humans are flexible, but machines can’t match that flexibility. So, a messy data situation will make for a messy technology installation,” Lindner said. “AI will take your system and speed it up like crazy, but it will also find out any gaps you were not anticipating during installation.”

In addition, Lindner says that healthcare organizations don’t need to tackle a complete overhaul of their digital infrastructure all at once. Think of it like a plumbing situation: Instead of installing an entirely new piping system, just repair the piece that needs fixing.

Lindner offers one last piece of advice: “Keep an open mind. Sometimes the solution to your problem may be slightly unexpected—as long as it moves the number in the direction you want and to the amount you want it.”

Jacqueline Renfrow is a journalist with more than 20 years of experience reporting on and writing about the intersection of healthcare, education, and retail with technology. Living just outside of Washington, DC, she enjoys exploring all that the nation’s capital has to offer with her husband and three children in tow.

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