Unwarranted clinical variation continues to drive excess costs in healthcare, giving the typical healthcare organization as much as $30M per $1B in revenue in savings opportunities.1 WakeMed recognized that it had the opportunity to decrease unwarranted clinical variation and improve patient outcomes, but without a clear planning structure, staff distrust in the data meant that it could not drive rapid cycle improvement.
The organization knew it had pockets of improvement but could not accurately measure the results. Improvement leaders had to spend 80 percent of their time attempting to obtain the data needed to understand the improvement opportunities and drive change.
While the organization had some data and analytics, it lacked high-value data and analytics, data governance, and standard processes for data validation or prioritization processes. The organization needed a solution that would support its efforts to transform care, ensuring care is evidence-based and minimizing unnecessary care variation.
To decrease unnecessary care variation and costs, and to improve quality and the patient experience, WakeMed established clinical transformation teams, implemented the Health Catalyst® data platform and a robust suite of analytics applications, gaining access to the high-value data and analytics the organization could trust. The organization redesigned processes to accelerate performance improvement.
WakeMed established clinical transformation as a strategic priority, aligning compensation structures for physicians and leaders to incentivize and reward improved performance. The organization’s clinical leaders, operational leaders, and financial leaders developed and defined the organizational methodology for measuring improvement. The organization now uses its data to deliberately measure and improve patient outcomes and quantify the impact on patients’ lives and financial performance.
WakedMed implemented data governance, prioritization processes, and a data quality and performance program, including standard processes for data validation. Leveraging the analytics platform, the organization integrates data from numerous sources, transforming it into standard, high-value, reusable data that are easily consumed by various applications. The analytics team engages with clinical and operational subject matter experts and end users to validate data, ensuring available data are accurate and can be used to support rapid cycle improvement.
WakeMed’s clinical transformation teams use the data and analytics to identify, understand, and quantify opportunities for improvement. Teams use rapid cycle process improvement to collaborate and standardize care, using the available evidence and expert consensus to streamline workflows, reduce cognitive load, and improve the consistency of care provided to all patient populations, improving health equity and care quality.
Clinical transformation teams implement “clinical excellence bundles” to improve care by utilizing. evidence-based practices. The teams then use data from the analytics platform to drive the adoption of the standards and clinical pathways.
The organization makes use of Healthcare.AI to accelerate the delivery of analytic insights. WakeMed can quickly and easily identify patterns, make comparisons for systemwide enhancement, and optimize performance to plan the most efficient improvement path.
WakeMed’s analytics-informed clinical transformation efforts are yielding the desired results. The organization has improved care processes for 23 distinct patient populations. In just one year, the organization achieved the following:
“The Health Catalyst analytics platform gives us the actionable data we need to support clinical transformation. We’ve saved more than $10M and positively impacted thousands of patient lives.”Neal Chawla, MD, FACEP, Chief Medical Information Officer, WakeMed Health & Hospitals
WakeMed will continue to advance the use of analytics across the organization and is integrating more health equity data into its applications, enabling it to identify and intervene where outcomes differ based on personal characteristics.