3 Steps to Prioritize Clinical Quality Improvement in Healthcare
There’s a lot of discussion in today’s marketplace about clinical quality improvement in healthcare. But with so much data from various systems, such as administrative, research, clinical, human resources, etc., how do you begin to identify which areas to focus on in your quality improvement efforts?
First, it’s important to eliminate the guesswork and use quality data to drive any improvement decisions. We’ve been able to do just that with our Analytics Adoption Model. By systematically advancing through the eight levels of this model, any health system can use their data to streamline their processes to consume fewer resources, discover cost savings, improve ROI, and most importantly, increase the quality of care.
As someone who has been a finance executive at several large healthcare organizations, the ability to improve the delivery and reduce the cost of healthcare is something that gets me very excited. Here’s how we do it.
Step 1 – Implement a Healthcare Enterprise Data Warehouse Foundation
A fundamental first step is to establish an enterprise-wide healthcare enterprise data warehouse (EDW). Your success depends on this EDW because it organizes all of your health system’s data into a single source of truth. With this single source of truth, you now have the foundation in place to drive clinical quality improvement initiatives because the EDW makes it possible to identify the areas in your organization that will yield the greatest improvements.
Step 2 — Identify Improvement Priorities by Using the 80—20 Rule
Like most health systems, you probably have limited resources and can’t tackle every area that needs improvement all at once. Instead, focus your scarce resources where they’ll be most effective by using the Key Process Analysis (KPA) application tool. The KPA tool uses the 80—20 rule to identify the 20 percent of your care processes that are being consumed by 80 percent of your resources.
Specifically, the KPA tool identifies the clinical processes with the highest variation and highest resource consumption. How? By combining clinical, billing, and costing data and linking ICD-9 codes and all patient refined diagnosis-related groups (APR-DRGs), the KPA application sorts each patient encounter into a three-tiered hierarchy:
- Clinical program (e.g., orthopedics)
- Clinical family (e.g., joint)
- Clinical work process (e.g., hips or knees)
With clinical data arranged this way and combined with financial data, you can see which clinical programs, families, and work processes present the greatest opportunity for quality improvement in healthcare. Then you can combine the analytical data with your knowledge of the organization to answer important questions like these:
- Does the work group have the right leadership to make change?
- What teams are formed and working successfully?
In the Pareto analysis above, you can view how the 10 most costly care process families account for 48 percent of the direct variable cost in that health system. By identifying the most costly areas of care and studying the variations, you now have potential areas to focus on. Variation in direct variable cost is a good surrogate for variation in quality of care.
Valuable information like this gives health systems a starting point. You simply need to follow the data and focus on the top clinical families. Once you’ve improved those care process families, you can move on to others.
Step 3 – Gain Consensus from Your Clinical Teams
Organizing information this way also makes it much easier to bring your clinical teams on board with improvement efforts. Not only can your teams now view overall data for the organization, but they can also view data specific to their specialty, which will help them define areas for improvement. The following two graphs are examples of the types of visualizations you can create by using the KPA application.
The first application visualization shown below plots Clinical Work Processes against two axes: the total variable direct cost for all cases for that work process on the x-axis versus severity-adjusted variation in variable cost on the y-axis. The bubble size represents the case count for that clinical work process. The upper right quadrant shows the work processes with highest variation and cost.
The visualization shown in the graph below displays the cost variation for a specific APR-DRG according to severity level. Each bubble represents a physician and the bubble size is the case count. The position on the x-axis is the average variable direct cost per case by physician. The y-axis represents severity. If we focus just on the inliers for each level, we can see there is wide variation.
Additional work with clinical teams can be performed to determine the root cause of the variations. Sometimes variations are caused by differences in documentation practices. Other times, physicians and nurses are actually delivering care in different ways for the same type of patient and condition.
Once you gain consensus on your priorities, the clinical teams can help determine the best ways to reduce variation while improving care at the same time.
Why is the KPA Application so important?
We are experiencing significant changes in how healthcare organizations do business. I started in healthcare finance when the industry moved to DRGs, and I haven’t forgotten the stresses of that transformation. As the industry moves to value-based purchasing, the transformation will be equally dramatic. Having the right applications in place can make all the difference in your clinical quality improvement efforts.
What tools and applications are you using to identify your most pressing priorities for clinical quality improvement at your hospital?
See the Results of Clinical Quality Improvement in Healthcare
Read about why North Memorial Health Care invested in an EDW from Health Catalyst and the goals they’ve achieved.