Lean Thinking – Advancing Efficiencies in Healthcare

For the past decade, healthcare has been the focus of a spirited campaign of debate in America. Both sides of the argument have focused on how best our healthcare would be delivered. Today, the debate rages on, but the core problems that truly affect a system continue to hurt those in need. The true need in healthcare reform is to improve operational efficiencies. Neither side is looking at the core issues of wait times, capacity or cost. These three elements are what plague the system today. Spend some time in any healthcare facility in this country, and you will see the signs of our issues. Patients stack up in waiting rooms for hours to receive a service that takes 10 minutes to deliver.

Lean Innovation Partnership in Healthcare

Up to this point, we have traditional methods of improvement, such as Lean or Six Sigma and have achieved modest results, which are slow in coming. With today’s modern technologies, we are at a crossroads for massive innovation and real change — specifically, with digitized patient data, machine learning AI, IoT real time data, predictive analytics, cloud infrastructure and smartphones. These elements come together and present a unique opportunity, especially when combined with lean thinking. Healthcare is an environment of a complex network of interdependent units operating individually to deliver care. Understanding the true operational function of these units, then bringing them together as a functioning unit that operates at a maximum level of efficiency is the true path to improvement.

Focusing on using sophisticated lean methodologies, combined with data science, plus machine optimization can significantly improve the efficiency of our system. It will significantly improve efficiencies, reduce wait times and costs in a system that right now is not providing the absolutely the best and most innovative level of care possible.

Read more about healthcare improvement opportunities here along with a perspective on Lean healthcare here.