Crouse Hospital improves patient outcomes with data-driven approach
Taking a data-driven approach to managing quality is expected, but how do you do it without hiring a team of programmers? Crouse Hospital uses SAS point-and-click health analytics solutions to manage multiple quality initiatives that reduce post-surgical infections, improve the discharge process and decrease readmission rates.
Crouse serves patients in a 15-county radius in upstate New York with 500 beds and room for 57 newborns. The hospital partners with DNV Healthcare to monitor and improve the quality and safety of patient care, and is a member of Partnership for Patients, a public-private partnership focused on quality, safety and affordability issues. Crouse has earned numerous accreditations and awards for its work.
"Our mission is to provide the best care," says Derrick Suehs, Chief Quality Officer. "To do that, you must be able to measure what you do and the outcomes you achieve. Over time, I’ve learned that what you pay attention to in an organization is what’s important. At Crouse, we believe the best care requires attention. Our metrics are part of our daily conversation, which is why we know how quality impacts the bottom line. SAS helps us know the facts about our performance and outcomes, and gives us confidence to know if our efforts are working."
When you can show data to the medical staff, we gain a lot of credibility. We can test notions and theories because we have the tools. Jennifer Watkins Director of Quality Improvement Crouse Hospital
Going beyond chart audits
"A lot of hospitals are stuck in the quality assurance model of doing chart audits and trying to find the bad apple," explains Jennifer Watkins, Director of Quality Improvement.
Some institutions can analyze data, but it’s an annual effort, with a program specifically written to look at one issue, or data sent to a consultant for a report.
Crouse wanted to take a broader approach, giving administrators, doctors and nurses a continual view of metrics on everything from post-surgical infections to length of stay. It also sought to help healthcare providers dig further into data to make improvements, sometimes using Six Sigma quality performance methods.
"Instead of just being able to do something one time, we're able to provide physicians with feedback monthly or quarterly," Watkins says.
Using data to improve patient outcomes
The hospital uses analytics to easily track quality initiatives and create models to help the most vulnerable patients receive the services they need to stay healthy. It also works with medical providers to create queries to address complex problems, such as why length of stay has crept up in certain units.
One example involves post-surgical infections. Studies suggest that one way to reduce post-surgical infections is to find out which patients have staph colonization before undergoing surgery. After Crouse began screening and treating patients for existing staph colonization prior to hip procedures, post-surgical site infections fell 60 percent. Seeing the results achieved by the orthopedic service has encouraged surgeons in other areas to adapt a similar protocol – and test its effectiveness.
On the ob-gyn floor, administrators noticed the length of stay for deliveries creeping up. The analysts initially expected to find this tied to one or two physician practices, but that wasn't the case.
As the ob-gyn chief began distributing the reports, the physicians started asking for different types of data analysis to pinpoint the problem. "We looked at length of stay by gender, thinking perhaps scheduling baby boys for circumcisions was delaying discharge. We concluded that wasn't an issue," says Crouse Quality Improvement Analyst Rachel Carey. Now analysts are looking at whether they are seeing a higher percentage of pregnant patients with pre-existing conditions that lead to complications.
Underpinning these efforts is access to quality data. With SAS, Crouse can work with all the data – not just samples pulled randomly from charts. This data-driven approach is critical to achieving physician and staff buy-in.
Crouse Hospital – Facts & Figures
provider of maternity care in New York
Pulling data together quickly and easily
Data is often located in multiple locations, so the first job for analysts like Rachel Carey and Lyn Johnson is to pull it all together.
"We have information that comes from several different databases," explains Watkins.
For a Center for Medicare & Medicaid Services report on complications in colon procedures and NYS Department of Health report on hip procedures, the analysts needed data on how long the patient was in the operating room, the patient's anesthesia complication rating, details about the surgeon, information on whether it was an emergency procedure and several other data points.
"We had to combine information from several different databases and run calculations," explains Watkins. "We know other sites are trying to do this by hand, but we’re able to use SAS to automate the job."
The hospital also created a database to track clinical quality improvement issues, such as readmission and complaints by physician. This is not only to help individual physicians improve, but also for accreditation purposes. "It's another project we would not have been able to do without SAS," Johnson says.
Interactive visual reporting and analysis without programming
Johnson used SAS in graduate school and at a previous employer. She was intrigued when she learned that SAS Analytics solutions now include SAS® Enterprise Guide®, a menu-and-wizard-driven tool enabling data analysis and results publishing with no programming required.
To explore these results even further, the hospital also uses SAS Visual Data Discovery, a point-and-click solution, that enhances advanced analytics and exploratory data analysis with interactive data visualization.
"We couldn’t do our jobs and learn to code simultaneously," explains Carey, who learned to use SAS Enterprise Guide after one online class. "SAS is point-and-click and the results are automatic," says Johnson.
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.