Valuing Ongoing Cost per Case Data to Realize Savings

Valuing Ongoing Cost per Case Data to Realize Savings

Clinicians speak in the language of patient outcomes, while those in the supply chain speak in terms of savings. The true value of ongoing case data gets lost in translation, often because it’s not presented at the granular level in a way that’s sustainable, accurate, and understood by everyone with a stake in the end result.

Supply chain, value analysis, and service line teams prefer to first tackle savings in robust, particularly costly categories. Savings realized from complex procedures result in the highest yield, because of the substantial total dollar spend. These complex categories often include total joint replacement, spine, cardiac rhythm management, and trauma treatment.

Current Challenges with Clinical Data Analysis

The way the majority of healthcare providers currently approach this case data process often proves too laborious and cost prohibitive to maintain. The in-depth procedural analysis gets shelved until the potential savings justifies resurrecting the project, and then starts all over.

The problem centers around the arduous process, and how data gets presented to clinicians. Relying on manual comparisons when trying to build the story behind high-level variance data – which can take hundreds, if not thousands, of hours – is an attempt to evaluate case data at a construct level by physician, procedure type, and vendor. This is often done using a sub-par classification system that fails to break down costs to the precise degree and at a regularity required to perform a quality case-data analysis clinicians can fully appreciate and consistently absorb.

Even with an exceptional understanding of physician variance through cost-accounting solutions, health systems must still manually rebuild constructs at a component level and research associated benchmarks in order to truly engage clinicians in the process. We commonly hear the complaint that, many times, after all of that hard work, there’s not a ton of confidence in the resulting data.

Clinical informatics specialists for health care networks and hospitals know there’s a more effective and efficient way to present ongoing case data in a language clinicians clearly comprehend. Utilization of case data at a construct and component level needs to happen monthly or quarterly, versus only addressing utilization during a major savings project. To make that transformational change possible requires implementing technology to easily facilitate accurate and ongoing cost analysis that’s delivered in the shared language of data.

Sharing Data Analyzed at Construct and Component Level

Annually, hospitals waste billions of dollars by failing to dive into supply chain case data and use clinical data analysis to realize efficiencies and savings. Hospitals could decrease supply chain expenses by an average of 17.7 percent – or $11 million annually per hospital – as reported in a healthcare supply chain analysis. That amounts to an annual cumulative savings opportunity of $25.4 billion.

The right approach to procedure analytics involves framing cost per case data as finding value versus assessing costs. When undertaking procedural clinical data analysis with clinicians, focus on establishing trust and utilizing dialogue to create transformational change.

Clinicians, prone to making data-based decisions, behave with patients’ best interests in mind. Bringing clinicians together to review case data builds confidence in the process, and ensures objectivity when presenting case data. Reviewing case data alongside clinicians also increases engagement and paves the path to improving ongoing conversations.

“When we approach clinicians with data that isn’t well-tuned, we can damage trust and the relationships that have taken a long time to build,” says Kelley Young, Clinical Informatics Consultant and former Supply Chain Clinical Informatics Director at Trinity Health. “As the person sharing data analytics, you’re not there to make decisions for clinicians, you are there to be objective and present information.”

Data, when analyzed at a construct and component level, becomes the universal language for communicating and establishing trust with clinicians. In the context of transformational change, regularly circulating and socializing clinical data analysis encourages increased buy-in. Engage clinicians by helping them understand the impact of their decisions and practice patterns on costs, and giving them some ownership in the supply chain data.

Standardizing and Monitoring Case Data for Gains

To attract and maintain clinicians’ involvement in the process requires rebuilding constructs at a component level, aligning the most unbiased associated benchmarks, as well as identifying and understanding physician cost variance to gain clinician confidence in the data.

Once securing physician buy-in and negotiating with vendors for improved pricing becomes ingrained, hospitals realize success by taking steps toward standardization. Giving clinicians options through construct and component-level data – detailed by procedure type or vendor – fits with how clinicians view their world, which makes the data easier for them to consume. When provided with detailed clinical data analytics that include multiple options and involved in decision making, clinicians often choose the most aggressive standardization.

After seeing gains in standardization, the work of compiling case data doesn’t end there. The conversation shifts to utilization, monitoring ongoing data, and looking for shifts in practice patterns. Utilization includes continually sharing clinical data analysis with clinicians to highlight gains and wins – without sacrificing profitability or letting savings get out of control – for a year or two before refining the process. Providers making gains in utilization savings are sharing this data with clinicians quarterly, if not monthly.

Circulating data helps clinicians recognize the impact on cost per case when they introduce a change in their practice pattern. Clinical data analysis informs them exactly how that change affects costs and, therefore, results in more informed decisions.

For example, with one Curvo customer, circulating physician utilization data helped clinicians become more aware of inconsistent application of bone cement, resulting in the average amount of bone cement used per case dropping from 2.5 units to 1.5 units. That one utilization change saves a healthcare system half a million dollars annually.

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