Take a second to think about the world’s greatest resources, what comes to mind? Your answers could range anywhere from oil to soil, though I’d venture to say that data never percolates to the top of that list. Within the next decade, our society will see a prolific changing of the guard, a change that will make data one of the most valuable resources on Earth. Why does this matter to you? More importantly, why does healthcare’s use of this data matter to you? Whether you choose to acknowledge it or not, every person on this planet is an employee in the field of healthcare; whether that be as a patient, provider, or associated third party, we all play a role.
As our healthcare model shifts from fee-for-service to value-based care, we’ve seen an increasing importance placed on the processes affecting patient safety and the steps that need to be taken to improve these processes. With that in mind, let’s take a step back and analyze the situation at hand: a rapidly growing database of patient information and clinical outcomes paired with an increasing need for process improvement. It’s at this point that we have a nexus of opportunity, one that’s just beginning to be exploited.
Intermountain Healthcare is a health system that can be considered the “gold standard” of data utilization, having implemented various digital data collection systems across their departments on top of an analytically mature framework. Within each department, there are “Data Teams” that consist of analysts whose sole job is to take their departments data and look for trends; these trends are then analyzed for areas of improvement and process changes are made. After two years of this analytical structure in place, the results are astounding:
- Cardiovascular Unit: When analyzing heart attack patients at Intermountain, their Data Analytics team were able to circulate the data within days and provide rapid process improvement. This led to Intermountain's door-to-balloon median time (the amount of time from the patient entering the door to the relief of a blocked artery) to be reduced from the national average of 90 minutes to a national leading 56 minutes, resulting in a 96% survival rate.
- Ear, Nose, and Throat Unit: The Data Analytics team took a look at two cauterization methods being utilized by ENT Specialists, one being much more expensive than the other. When asked why physicians preferred one over the other, the responses were “patients felt better after surgery” using the more expensive method. After analyzing patient outcomes, they presented physicians with the data showing that the cheaper method actually held a statistical edge in recovery times post-surgery; they have since begun a study to replace the more expensive method with a more economical option.
- Supply Chain: Coronary Surgeons had been using sutures that cost $750 over the standard $250 sutures provided by the hospital. The physicians were adamant on the perception that the more expensive suture led to less leakage post-surgery, presenting the Data Analytics team with another opportunity. When the data showed no difference in patient outcomes, Intermountain’s purchasing department went to the supplier and showed them this data; when faced with either dropping their prices or losing Intermountain as a client altogether, they dropped their prices and the Data Analytics Team saved Intermountain over $250,000 a year through their data analysis.
As we see with Intermountain Healthcare, when data collection is paired with analyses and action plans, transformational improvement is imminent. Data collection continues to come from different avenues with the daily additions of healthcare technology, compiling all of their patient data into a data lake that remains untouched by hospitals. It will be through a culture change towards analytical maturation in healthcare that allows this data to be utilized to it’s fullest potential; when that happens, we may see the trigger of the seismic shift in patient care that we are so tirelessly pursuing.
Ransbotham, S. (2015, August 9). When Healthcare Gets a Healthy Dose of Data. MIT Sloan Management Review. Retrieved from http://sloanreview.mit.edu/casestudy/whenhealthcaregetsahealthydoseofdata/
Senior Client Specialist, MyRounding
Dillon was born in Honolulu, HI but having grown up in a transient military family, he likes to consider Denver, CO to be his home. Currently employed at Huron as a Client Specialist with MyRounding Solutions, Dillon is in the pursuit of his MBA in Health Administration at CU-Denver. Prior to working with MyRounding Solutions, he worked at several Healthcare IT entities where he established his passion for the changing landscape of healthcare and the evolution of Healthcare IT.