Transforming Healthcare Data into Insight with Tableau Visual Analytics
According to Tom Dewar, Head of Information at St. George’s Healthcare NHS Trust in London, data analysis is helping the hospital convert information into insight and improve patient outcomes. “Tableau cements anecdotally-held truths and busts myths,” he says. Immensely popular across the hospital—based on its ease of use and ability to instantly answer questions—the Tableau visual analytics solution is helping St. George’s to deliver outstanding patient care and meet the challenges of cost reduction, resource allocation, and compliance regulations.
Optimizing clinical outcomes
With more than 6,000 staff caring for patients around the clock, St. George’s Healthcare NHS Trust is the largest healthcare provider in southwest London. Data from the hospital’s electronic health records and other applications creates an unprecedented opportunity for the Trust to accelerate decision making, optimize clinical outcomes, and improve operational performance.
However, reliance on manual reporting systems—such as spreadsheets, slide decks, and pivot tables—made preparing reports time-consuming. Information was often out of date—up to three months old—by the time it reached the clinical directors and other decision makers. A lack of reporting consistency between departments also prevented teams being compared against one another.
Tom Dewar, Head of Information at St. George’s Healthcare NHS Trust, experienced the problem first-hand. “We were gluing together siloed information with our bare hands,” he says. “We compile scorecards on issues such as number of patients in Accident and Emergency, waiting times, and patient readmissions. So much time was spent gathering the data, it was often too old to be acted upon. We needed to be more proactive.”
Accelerating data-driven healthcare decision making
Dewar cites an example of this in action. “Our chief executive was recently talking to hospital commissioners about the pressure of coping with increased volumes of patients during the winter months. Using Tableau, it took me just 30 minutes to create a visual interpretation of why we are so busy.
This included an ‘Arrivals’ dashboard displaying patient arrival metrics by date, by specialty and other criteria. When he asked what was behind the demand, it took me only five minutes more to create a visual showing stroke activity to be one of the primary causes,” says Dewar. “Being able to quickly uncover important patterns and trends like these are essential to data-driven decision making. In the past, I would have struggled to get an answer back the same day,” he says.
The aim is to eventually move towards self-service analytics for key areas of the hospital, with Dewar’s team concentrating on in-depth analytical work and statistical analysis. “Tableau is so easy to use, we want consultants, divisional heads, managers, and other staff to answer questions themselves like, ‘how many heart patients did we see last year?’, or ‘how many patents are delivered to Accident and Emergency by ambulance, versus walk-in cases?’ By answering questions like these more quickly, St. George’s will be able to increase patient flow, improve outcomes, and ensure every touch-point with the patient and their family is executed flawlessly.
“Everyone who sees Tableau instantly falls in love with it,” he adds. “It allows them to gain insight into their business like they’ve never had before. Our over-riding aim is to deliver outstanding patient care against a backdrop of unrelenting pressure to reduce costs, maximize resource allocation, and meet compliance considerations. Tableau will take St. George’s a long way towards achieving those goals.”
Healthcare Analytics at the University of Michigan Health System – a Cinderellesque story
The Fast Analytics Team, within Revenue Cycle Management at the University of Michigan Health System, set out to improve their reporting and analytics with Tableau. Over the course of their experiment, the team developed tools and processes that eliminated 8000+ annual work hours from revenue cycle metrics, charge estimation, cash reconciliation, and other areas.
Michigan Medicine optimizes workforce with Tableau, saving 5,000 analyst hours in a year
Michigan Medicine is home to one of the largest health care complexes in the world, with three hospitals, 40 outpatient hospitals, and more than 140 clinics. Michigan Medicine’s Fast Analytics team serves the data needs of over 30 internal groups. With Tableau, the health system was able to automate 85 – 95% of reconciliation and provide a baseline to quickly reconcile the remaining portion – which wasn’t possible before. They were also able to create a charge estimate dashboard, shifting a 4.5-hour process to a 4.5 second query.
Optimizing the revenue cycle
While data analysis is nothing new in healthcare, the game is quickly changing. Now organizations must have sophisticated interplay between IT and finance systems that ensures close analysis of the organization’s entire claims data universe. Learn about the strategies organizations are using to develop comprehensive dashboards and sophisticated trending analyses that prevent millions of dollars in claims denials and hundreds of hours of lost labor.