Sahlgrenska University Hospital in Gothenburg, Sweden, is Northern Europes largest hospital. Daniel Stålhammar, an associate professor at at the neurosurgery clinic, works to find the optimal treatment for severe head injuries. He had been searching for a simple, easy-to-use tool to aid doctors in predicting complications from cranial surgery. Complications from brain inflammation cost the hospital approximately $1 million every year. More importantly, it costs lives.
Stålhammar is using QlikView to analyze a database of current patient status compared with prior outcomes to predict when intervention is necessary. Through the use of this tool, the hospital has been able to reduce the complication rate to zero, eliminate unnecessary tests and costs, and save patient lives.
Typically, we think of business intelligence software as a tool for driving revenue or improving profitability. Here, we find that BI software is used to make a hospital more efficient, improve the treatment of critically ill patients and save lives.
Introductory Overview
Sahlgrenska University Hospital has more than 2,700 beds divided into 165 wards and approximately 17,000 employees. The hospital is one of Swedens centers for critical cranial surgery. Cranial surgery is technically very difficult, and complications from surgery have a devastating effect on patient outcomes.
In particular, when brain surgery is performed after a severe head injury, there is a great risk of getting an inflammation in the brain (meningitis). This risk occurs because the standard procedure is to leave one or more tube in the brain to drain excess fluid. Any infection around the tube or blockage of the tube can result in the rapid onset of meningitis. Every year, there are about 20 people who get meningitis from this surgical procedure at Sahlgrenska hospital alone.
But doctors need support in knowing when to intervene and when the symptoms of the patient are simply a result of the invasive surgery. In the past, this support has been encoded in a complex set of patient protocols that were not only difficult to manage, but also did not reflect the most recent information. Stålhammar worked to reformat the procedures after surgery, based on analysis of data from prior outcomes. He also set in place a system whereby test results from current patients were fed into a database. This data was then read into QlikView for analysis.
The QlikView system provides a real-time decision-support system that doctors can use to see the most recent test results compared with patient records over time. The system also automates decision-support tasks. Doctors are alerted by e-mails from QlikView when indicators show an increased risk of getting meningitis.