Good OM Reading: An MIT Case Study of Hospital Efficiency
American health care is undergoing a data-driven transformation. This MIT Sloan Management Review (June 25, 2015) case study examines the data and operations analysis culture at Intermountain Healthcare, a Utah-based company that runs 22 hospitals and 185 clinics. Data-driven decision making has improved patient outcomes in Intermountain’s cardiovascular medicine, endocrinology, surgery, obstetrics and care processes — while saving millions of dollars in its supply chain. Here are just two examples from this lengthy, but very readable study, one worth sharing with your class.
SURGERY: When data showed Intermountain’s chief of surgery that surgical infection rates at the hospital were in line with national norms, he presented the findings to the surgeons there. He said, “You think you’re great, but compared to other hospitals in the country, you’re not above average.” So a committee of clinicians spent a year developing a list of 30 possible causes, then whittled it down to 5 and made recommendations of changes. Doctors hated some, like having to give up bringing personal items into the operating room, including fleece jackets they would wear to keep warm. But in fact, after a 6 month trial, infection rates fell to half the national standard.
SUPPLY CHAIN: Supply costs will exceed hospitals’ top expense–labor–by 2020. The challenge is that a lack of price transparency and no system for sharing cost information with unaware doctors. So Intermountain started a supply chain organization–facing 12,000 vendors, $1.3 billion in expenses, and a culture that ceded much purchasing authority to doctors. One challenge was finding a way to reduce expenses for physician preference items (PPIs)–the devices that doctors request because they prefer them to comparable products. PPIs consume as much as 40% of a hospital’s supply budget. Intermountain launched a system designed to reduce costs by tracking its 50 highest-volume procedures and presenting information to surgeons on their supply options. One thing it found was that some coronary surgeons used sutures that cost $750, while others used sutures that cost $250. The analytics revealed no appreciable difference in patient outcomes. Doctors had no idea that the things they were using cost so much.