Proven systems engineering methods can cure complex healthcare challenges
Professor James Benneyan remarked he sometimes feels like the Maytag repairman, standing by with tools that can help fix healthcare’s problems. The differences between Benneyan and “Ol’ Lonely” are that the machine he’s working on is actually broken and while he’s actively helping numerous organizations, he wishes the phone would ring more.
As founding director of Northeastern’s Healthcare Systems Engineering Institute, Benneyan is a nationally recognized expert in solving complex healthcare challenges using systems engineering methods.
Benneyan addressed a room full of senior healthcare improvement leaders at a recent Northeastern workshop, illustrating how his three centers have used these tools and approaches to address high-leverage problems also facing Boston healthcare organizations. This approach scaled nationally, he estimated, might cut the annual nearly $3 trillion healthcare budget by one-third.
“While roughly 70 percent of healthcare problems can be fixed with simple front-line improvement approaches,” said Benneyan, “maybe another 20 percent need something a bit more. But the upper tail problems are fundamentally complex and in other industries would be solved with more advanced systems engineering methods.”
Benneyan has shown this same potential in individual health systems and now has funding from the Centers for Medicare and Medicaid to scale it across an entire healthcare community, here in Boston.
Simple improvement methods include things like reorganizing storage clinical closets so the most oft-used items are readily available. However, more advanced techniques usually are required to solve macro-level problems, such as identifying the best locations for new clinics, more efficient ambulance routing patterns, or optimized treatment schedules. For these sorts of challenges, Benneyan said, engineers turn to mathematical and computational modeling.
Benneyan gave an overview of the most common systems engineering models and several healthcare examples of each in order to stimulate group brainstorming of potential applications across Boston.
“Models are artificial representations of the real world, but useful for rapidly helping design better processes and systems,” he explained. For example, his team can create simulation models that mimic such things as patient flow throughout a hospital, and then test hundreds of potential improvement ideas in order to identify the best changes to put into actual practice.
The workshop was the second in an ongoing series to introduce Boston healthcare professionals to the types of problems systems engineering can solve and the methods for doing so. After Benneyan’s lecture, he led a group brainstorming discussion session to identify similar problems they could work on locally.