Sharp Healthcare’s proven method for using clinical analytics to reduce healthcare-acquired infections
Value-Based Payments Continue to Eclipse Fee-for-Service
The fundamental and continuing shift toward value-based payments has brought clinical analysis to the forefront of most healthcare systems. Federal and commercial payers are using both incentives and penalties to drive quality improvement and cost savings while improving patient outcomes and patient safety.
National goals for payment reform outlined under the Department of Health and Human Services’ Health Care Payment Learning & Action Network (LAN) shift the U.S. toward risk-based payment models including savings/shared risk, bundled payments, and population-based payments.
In 2017, one-third of all healthcare payments were classified as alternative payment models or population health models. Half of Medicare Advantage plan payments fall into those categories, as do 38% of traditional Medicare payments.
By analyzing clinical data, healthcare organizations can drill down into their medical data to gauge performance metrics and identify significant opportunities to improve patient care and outcomes. But what does clinical analysis actually look like in healthcare organizations today?
A Clinical Analytics Case Study
Sharp Healthcare, the largest health system in San Diego, uses Axiom Clinical Analytics to identify and target opportunities to improve clinical outcomes in its facilities. This e-book will outline Sharp Healthcare’s processes for examining healthcare-acquired infections (HAIs), identifying areas for improvement, and taking action to reduce HAIs.
Finding a Framework for Improvement
Having the right software to understand data is a critical component of any improvement effort, as is identifying and adopting a framework for improvement. Working in conjunction with Kaufman Hall, Sharp Healthcare adopted a hybrid performance methodology that’s partly based on “A Framework for the Continual Improvement of Health Care: Building and Applying Professional and Improvement Knowledge to Test Changes in Daily Work,” by Paul M. Batalden, M.D., and Patricia K. Stoltz, PAC.
Sharp Healthcare’s quality framework includes six key steps:
- Identify goals: What is the organization’s biggest pain point?
- Identify metrics: Which metrics/benchmarks will be used to assess the pain point?
- Develop the hypothesis: Who, what, why?
- Test the hypothesis: How is success defined?
- Identify the learnings pre-, during, and post-: How did the analysis take shape and what results were gathered?
- Take action based on results: What can the organization do with this information?
Step 1: Identify goals
Sharp Healthcare first used Axiom Clinical Analytics to examine its HAI rates and identify the target for the initial quality improvement project. After reviewing data, the health system decided to focus improvement efforts on surgical site infections after colon surgery (SSI-COLO).
Axiom Clinical Analytics helped Sharp Healthcare leaders see:
- At a facility level, costs for SSI-COLO patients are 16%-70% higher
- At the encounter level, SSI-COLO patients have costs over five times higher
- Median cost is almost double for SSI patients
- Costs for SSI patients have almost triple the variability (σ)
- Comparisons are statistically significant: p-value = .0003
- Length of stay is a median of seven days for colon procedures versus 13 days for SSI patients
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Step 2: Identify metrics
After recognizing room for significant improvement in SSI-COLO, the health system determined the most-appropriate metrics to track were:
- Infection rates
- Length of stay (LOS)
- Direct cost associated with HAIs*
*Note: HAIs are not only costly to treat, but incidents are publicly reported on CMS Hospital Compare, and included in external assessments (e.g. Leapfrog Hospital Safety Grade). Higher than expected infection rates can lead to financial penalties through the CMS Hospital Value-Based Purchasing Program and the Hospital-Acquired Condition Reduction Program.
Step 3: Develop the hypothesis
Leaders at Sharp Healthcare used Axiom Clinical Analytics to investigate the impact of SSI-COLO on cost and length of stay (LOS), after identifying surgical site infections as one of the organization’s largest contributors to infection-related costs.
Health system leaders hypothesized that SSI-COLO patients would experience longer length of stay and higher direct costs than colon procedure patients without an infection event. They also supposed that a pattern would emerge to suggest why some patients are more likely to experience SSI-COLO. Sharp Healthcare’s team wanted to quantify the difference between patients who did and didn’t experience an infection, and target actionable areas of opportunity for improvement initiatives.
Step 4: Test the hypothesis
Sharp Healthcare worked with a Kaufman Hall statistician to launch an investigation and intervention using the following steps:
- Identify patients suffering from SSI-COLO
- Gather data such as cost, charge, length of stay, patient safety events, and patient satisfaction for these individuals, and for colon surgery patients with no infections
- Compare the overall clinical outcomes for both populations to analyze the prevalence, burden, and cost of infections
- Look for patterns – such as a large proportion of infections coming from a small proportion of physicians – to identify variations in clinical care that may contribute to infections
Using this analysis, Sharp Healthcare discovered that one facility and three physicians were outliers in terms of greatest LOS/Cost opportunity.
Step 5: Identify the learnings pre-, during, and post-
Leaders at Sharp Healthcare made several important realizations throughout the course of this data-driven improvement initiative.
- Pre-learning: Working with the CDC’s National Healthcare Safety Network (NHSN) data, which is available in Axiom Clinical Analytics, they reviewed appropriate benchmarks
- There are encounter-level and unit-level data feeds from the hospital to NHSN
- During: Narrowing down a specific, helpful question to investigate
- As detailed above, the health system sees a high volume of colon procedures and chose to analyze the SSI-COLO HAI in particular
- Other HAIs had very low volume and/or patient populations were too broad for this purpose
- Post-learning: Analyze results and look for opportunities to improve
- Besides the expected higher cost and longer length of stay, colon procedure patients with an SSI-COLO event had drastically higher outcome variability than colon procedure patients without an infection. This variability can be challenging for department planning and frustrating for the patient, beyond the known increase in resource utilization for these patients
- The health system determined actionable opportunities for improvements by identifying specific facilities, departments, and/or physicians with particularly high infection rates
Step 6: Take action based on results
The transformative power of clinical analysis happens when healthcare leaders use data insights to drive action. At the time of printing, Sharp Healthcare is in this phase.
“We conducted the analysis using Axiom Clinical Analytics at the beginning of the year, and identified four activities to help improve clinical outcomes,” said Chris Tomac, Director of Clinical Analytics & Data Strategy at Sharp. Those activities were:
- Inform leadership to begin targeted improvement efforts
- Encourage financial teams and clinical teams to partner together on improvement initiatives
- Share clinical analytics information across teams to provide a sense of urgency
- Include SSI prevention metrics in physician incentive agreements
“We’re patiently waiting for enough time to pass to collect sufficient discharge data so we can measure changes in outcomes,” said Tomac. “It’s Sharp Healthcare’s mission to be the best place to receive care, and to do that we’ve decided that we need to be in the 90th percentile or above for some selected clinical quality measures. Preliminary figures suggest this improvement framework will bring our SSI-COLO rates into our target range.”
Learn More about Axiom Clinical Analytics
Axiom Clinical Analytics is the leading clinical analytics solution for U.S. hospitals and health systems. It provides a single source of truth, with multiple sources of data on one platform to provide robust, measure-centric data management.
The flexible and dynamic system allows users to build reports at many levels – system, hospital, service line, clinical unit, physician, and patient – with custom data views based on selected criteria. Users can identify best practices within the system for replication, quantify preventable complications, readmissions and safety events, and find the quickest path to identify unwarranted clinical variation.
“Axiom Clinical Analytics provides the risk-adjusted rates we need to gauge our performance against national benchmarks and the flexibility to run a variety of measures on our performance related to clinical quality of care,” says Tomac.