THANK YOU FOR SUBSCRIBING
This sample data visualization shows one way healthcare providers can leverage data to inform their workflow. Providers can drill down by time of day, wait time, and care score to see how the busy times may have affected patient experience.
Today’s healthcare providers face a tough challenge: work collaboratively to deliver the highest quality of care at the lowest cost.
For most healthcare organizations, the new standards of operation are understandably daunting. They must adapt best practices that align with the business objectives of their enterprise. They must also implement repeatable business processes across the organization— in operations, finance, supply chain management, and so on—to optimize efficiency at the enterprise level.
Electronic health records play an important role in connecting these disparate departments and helping organizations move the needle. But many of these systems aren’t up to the task. According to a recent IDC health insights report, 58 percent of healthcare providers are dissatisfied with their current EHR system due to its inadequate analytical capabilities. In short, organizations can’t easily explore their data and uncover insights that would help improve their efficiency and outcome.
Data has long been a pain point for healthcare providers. For years, hospitals and clinics have relied on IT departments to provide answers to data questions, creating a never-ending cycle of long wait times and inflexible results. IT has faced the inverse challenge. IT Teams have spent dozens of hours churning out reports and responding to requests that often fall short of what the requester needs to know.
And because most healthcare workers lack the time and skills to see and understand data, they simply don’t use the analytics systems provided by their companies. As a result, many knowledge workers today rely on spreadsheets as their primary self-service analytical tool, which can be slow, inefficient, erroneous, and difficult to govern and scale.
An Analytics-Fueled Framework for Operational Excellence
Some healthcare providers are altering this status quo by empowering people throughout their organizations to explore data, enabling them to answer their own questions, act on their answers, and improve efficiency.
These organizations embrace a five-part framework: monitor, measure, analyze, resolve, and improve. Data plays a critical part in this model since, as the famous axiom goes, ‘you cannot fix what you can measure.’ And with self-service analytics, anyone across the organization, even non-analysts, can monitor, measure, and analyze their data to track progress.
This system empowers those who can maximize the impact of their data to explore their data at the speed of thought, uncover insights, and make data-driven decisions to improve outcomes. And healthcare leaders across the country are seeing great success with this simple, intuitive, and pragmatic approach.
This five-part framework for operational excellence is enabled by data and analytics.
‘We Are Really Saving Lives with Our Data’
At Piedmont Healthcare, data had become a problem. The Atlanta-based provider includes five hospitals, 400 medical staff members, and 1,200 affiliate physicians.
Before adopting self-service analytics, accurate and timely data was hard to come by. With no “single version of the truth,” there were scheduling problems that hindered operational excellence. Something needed to change.
After making the switch to self-service analytics, remarkable changes occurred, including a 23 percent improvement in efficiency and savings of almost $650,000. How? Piedmont used to rely on some 2,400 Excel spreadsheets that took nearly a month to deliver. Now, that same data is accessible via a single dashboard. This not only simplified access to data but also enabled people across the organization to always have access to the very latest, up-to-the-second data. With a stronger data ecosystem, Piedmont has more resources to pass on to patients.
Providence Health and Services faced similar problems. Providence is an enormous organization, the second largest healthcare provider in the US with 34 hospitals, 475 physician clinics, 22 long-term care facilities, 19 hospices, 693 supportive housing units, 436,000 members and 76,000 employees. All those people and facilities produced an avalanche of data that was impossible to use properly—until the organization embraced self-service analytics.
Like Piedmont, Providence was able to turn thousands of spreadsheets into a manageable number of interactive dashboards. And the switch has proven highly productive for healthcare providers who now have faster and easier access to their data.
Among other benefits, Piedmont saw gains in physician productivity and the quality of cancer-screen composites which improved 100percent in one year. “The data is having critical impact,” says Kim Womack, Clinical Administrator for Providence’s Swedish Medical Group. “The cancer screening metric and our patient detail reporting has enabled better patient care. We are really saving lives with our data.”
Optimizing the Supply Chain to Improve Care, Save Money
Barnes-Jewish (BJC) Healthcare was suffering from a chaotic supply chain. The system of 11 hospitals had no overall strategy, and inventory was hard to track. Since records were inaccurate, spending was sometimes wasteful. The goal was to reduce spending and develop a leaner, cleaner approach to the supply chain.
With self-service analytics, Barnes-Jewish (BJC) Healthcare managed to centralize purchasing and keep much closer tabs on spending with suppliers and supplies. The result: The organization saw numerous benefits, including saving $212 million on supply-chain spending over a four-year period. Barnes-Jewish (BJC) Healthcare was also recognized with the prestigious Gartner Supply Chain Innovator Award in 2015.
These savings directly translate to better care, says strategic supply chain manager Lynn Kersting: “Every 1 percent reduction in supply spending is equal to hiring 500 full-time equivalent caregivers.”
A sub-optimal supply chain also proved problematic for Seattle Children’s Hospital, which serves a larger region than any children’s hospital in the U.S. Orders didn’t match the hospital’s needs. Some supplies were overstocked while others often ran out. At the center of the problem was an outdated data ecosystem that was hard to navigate.
But the hospital’s data landscape changed when it adopted self-service analytics. People could finally access and make sense of the inventory data. Now, the hospital has a much firmer grip on every link in its supply chain. Interactive dashboards show exactly which materials are in stock and in what volume. Equipment can be tracked to ensure its going where it should.
In addition to better care, the hospital has seen many measurable benefits including saving millions on procurement costs and 40,000 clinical labor hours. When an organization can analyze wastefulness in ordering and staffing than resolving to improve the situation, the results are often remarkable.
Using New Tools to Accomplish Timeless Goals
All these healthcare facilities are finding success through the replicable process of monitoring, measuring, analyzing, resolving, and improving. And the engine enabling the five-part framework is a powerful business intelligence tool. These providers’ successes are a sign of the times. Healthcare is no longer just about the right doctor, the most current research, and the best medicine. It’s also about making data work for doctors and patients, and helping drive operational excellence. And with a healthier data ecosystem at healthcare organizations, we’re all in better shape.