The Best Healthcare Analytics Application for Prioritizing Improvement Programs By Bobbi Brown

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1 Insights The Best Healthcare Analytics Application for Prioritizing Improvement Programs By Bobbi Brown As the industry moves to value-based purchasing, the transformation will be equally dramatic. Having the right applications in place can make all the Healthcare analytics is a big buzzword in today s marketplace. Health systems have tons of data at their fingertips. The difficult question is this: where do you start? How can you identify the areas for clinical improvement? It helps to eliminate the guesswork in addressing this question. At Health Catalyst, we ve found a way to pinpoint the areas an organization needs to focus on to achieve cost and quality goals. As a finance executive, that s something that gets me very excited. Let me tell you how we do it. THE HEALTHCARE ENTERPRISE DATA WAREHOUSE FOUNDATION The first step is to establish a healthcare enterprise data warehouse (EDW). The vital importance of this step is something we ve discussed in several other commentaries ( aids_transition_to_value-based_care/). Here is the short explanation for why an EDW is necessary. The healthcare EDW organizes a health system s clinical, financial, patient satisfaction, and administrative data into a single source of truth that serves as a foundation for data-driven improvement. Once you have the data in the EDW, you can identify areas in your organization that will yield the greatest improvements. THE HEALTH CATALYST KEY PROCESS A IDENTIFYING YOUR IMPROVEMENT PRIORITIES PA APPLICATION: Pareto analysis is a technique used in statistics and decision-making that identifies the limited number of input factors that will produce the most significant impact on output. At Health Catalyst, we apply Pareto analysis to each health system s data. The Health Catalyst KPA application analyzes data to determine which clinical care process families represent the greatest improvement opportunities for a healthcare organization. Specifically, our KPA tool identifies the clinical processes with highest variation and highest resource consumption. The Health Catalyst KPA application analyzes combined clinical, billing, and costing data. 1

2 Based on ICD-9 codes and APR-DRGs, the tool 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 stratified in this manner and combined with financial data, you can see which clinical programs, families, and work processes have the greatest opportunity. You combine the analytical data with your knowledge of the organization. Does the work group have the right leadership to make change? What teams are formed and working successfully? Here is an example of a Pareto chart generated in the Health Catalyst KPA application. Pareto Chart 2

3 It shows that 10 clinical families account for 53 percent of the direct variable cost in that health system. We have found that variation in direct variable cost is a good surrogate for variation in quality of care. This valuable information gives health systems a starting point. You simply need to follow the data and focus on these 10 clinical families. Once you ve improved those families, you can move on to others. GAINING CONSENSUS Organizing information in this way also makes it much easier to bring your clinical teams on board with improvement efforts. Consider the following KPA application visualizations: 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. Clinical Work Process Chart for Total Variable Direct Cost 3

4 The visualization shown below displays the cost variation for a specific APR- DRG by 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. Clinical Work Process Chart for Variable Direct Cost by Provider Additional work with clinical teams can be performed to determine the root cause of variation. Sometimes variation is 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. 4

5 WHY IS THE HEALTH CATALYST KPA APPLICATION SO IMPORTANT? We are about to experience major 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. Read why IDC Health Insights calls Health Catalyst and the Health Catalyst KPA application a fresh approach to clinical analytics.( com/news/idc-health-insights-health-catalyst-a-fresh-approach-andarchitecture-for-clinical-analytics/) About the Author Bobbi Brown joined Health Catalyst in July 2012 as a Vice President, working on financial analysis. Prior to coming to Health Catalyst, Bobbi was a team lead working on the installation of planning software at Ascension Health in St. Louis. She has also worked for Kaiser Permanente and Sutter Health as a Vice President of Financial Planning. 5