Ironically the prevailing attitude among clinicians remains; “healthcare does not consider itself a process or system industry” therefore, it is not one which would significantly benefit from leveraging technology to improve its processes. As a data science community within the healthcare industry, we must all push the envelope to demonstrate that Healthcare has a lot to gain by becoming more efficient and effective via process improvement technologies as it clearly has done by embracing clinical improvement technologies.
Dale Schroyer, a certified data scientist, and ProModel’s leading healthcare simulation expert overheard these comments while attending an immersion workshop on RCA, or root cause analysis, at the NPSF Patient Safety Congress earlier this year.
This program looked at what hospitals do when an adverse event occurs. According to the workshop instructors, Dr. James P. Bagian and Mr. Joseph M. DeRosier, “Usually, such events occur because of system faults or failures, not necessarily human error. The challenge is determining what the faults in the system are, how they can be fixed and instituting actions to fix them and measure those fixes.”
Schroyer found it a fascinating topic because of the similarities to what is done in the aerospace industry in which he started his career. One of the instructors was also from the aerospace industry. Both instructors teach at the University of Michigan which is also Schroyer’s alma mater.
From listening and interacting with conference attendees, most of whom were nurses and doctors, Schroyer observed that healthcare does not consider itself a process industry. However, the mere fact that doctors and nurses were having the conversation is a considerable step in the right direction.
Many in attendance wanted to know what techniques would best serve them in convincing their coworkers back home that the system approach is a good and necessary one for the healthcare industry that can benefit patients, hospitals, nurses and physicians. Using a predictive/prescriptive analytic tool such as discrete event simulation (DES) is one possible approach.
Schroyer spoke with the instructors, as well as other attendees, about simulation as a tool to improve patient flow and other hospital system shortfalls. They mentioned that the barriers to simulation are many such as a long, cumbersome learning curve.
ProModel and others are now developing DES and machine learning based tools with easier user interfaces, and with the DES and algorithms embedded and custom configured into the software for each hospital so that the end user no longer needs to be a programmer to be successful.
The aerospace and airline industries have been using predictive and prescriptive analytics for years, which was the source of inspiration for the following infographic. The airline industry is a “high reliability” industry, as is healthcare. Systems providing both predictive and prescriptive technologies provide operational insights and deliver specific action plans to enhance patient outcomes, lower costs and drive additional revenues.