Four Steps to Effective Opportunity Analysis

This report is based on a 2018 Healthcare Analytics Summit presentation given by Matthew Brown, Finance Manager, Allina Health, and Sarah Jenson, Director, Analytics, Health Catalyst at Allina Health, entitled, “Reducing Unwarranted Clinical Variation Saves Tens of Millions of Dollars.”

It’s well known within the healthcare industry that variation in clinical care indicates waste, and waste has negative impacts upon care quality and cost. According to the Advisory Board’s 2017 report,Standardizing Practice for a Tighter Grip on Cost and Quality, unwarranted clinical variation accounts for 42 percent of wasted spending in U.S. healthcare. As healthcare reimbursement moves to a value-based model, health systems are under greater pressure to reduce clinical variation and related costs while improving patient outcomes. That’s not an easy task, but, fortunately, savings opportunities exist within every healthcare organization. Several studies show that for every $1 billion of revenue a typical health system has, there are approximately$30 million of actionable savingsopportunities.

Slim margins and lack of resources in health systems require prioritizing improvement work, so some healthcare organizations are using data to identify opportunities and optimize improvement initiatives.

Data Informs Opportunity Analysis

知道变异是个问题是一回事;知道哪里存在最大的无端变化以及如何应对是另一回事。依靠传统的方法来收集数据，比如手工检查图表或账单记录，并不总是能带来有效的更改，因为这些方法效率低下，而且充满了人为错误。

Opportunity analysis is a systemwide process that uses data to identify opportunities for improvement and quantifies the value of proposed improvement initiatives in terms of optimized care, increased revenue, and decreased costs. It gives health systems a look at performance on a patient, clinician, and system level. Using data analytics tools, health systems can get a high-level look at opportunities for change and an in-depth look at how to improve outcomes and financials in a prioritized approach.

How Data Analysis Helps Identify Opportunities and Find Variation

Identifying clinical variation is a challenging process. It takes time and effort to look at data and assess where the opportunities to drive improvement lie. Standardizing the opportunity analysis process makes it more repeatable than an ad hoc analysis and prioritizes actionable opportunities for cost savings and care improvements.

Opportunity Analysis Steps

Analysts recommend engaging in opportunity analysis every quarter. While organizations can customize their approach, an opportunity analysis process should involve four basic steps: kicking off the analysis, engaging with clinicians to identify opportunities, digging deeper into those opportunities, and presenting findings to the decision makers using standardized visualizations of the data.

Step 1: Kicking Off the Opportunity Analysis

开始机会分析涉及到让所有的分析人员聚集在一起选择和分配重点领域，这可能包括服务线路、设施、服务或事件的类型、文献综述，或一个特定的感兴趣的领域。这个步骤的第二部分是过滤那些重点领域以改进想法，并在与临床医生接触之前进行一些初步分析，以验证在最初分析中发现的想法。改进的想法可以来自任何地方——护士、临床医生、研究文章、经验等等。一旦构想出来，初步的数据分析就开始了。

Preliminary analysis requires analysts to get together, dig into the data, look at variation, and talk about methodologies to reduce variation. Doing this well requires trained analysts and the right data analysis tools. Preliminary analysis uncovers insights for possible improvements, which are invaluable when engaging with clinicians, the next step.

Step 2: Engaging with Clinicians

Clinician and executive backing are imperative for change initiatives. Providing actionable data to clinicians engages them in the quest for improvement. A compelling story that provides support for improvement initiatives shows them the value of a data analysis investment.

Engaging with clinicians also helps analysts understand which clinical processes identified might warrant variation. Working early on with clinicians to validate opportunities for improvement makes the data more actionable later in the process because the team won’t spend valuable time and resources working on, for example, reducing variation that is warranted.

Step 3: Digging Deeper into the Data

一旦团队决定了要调查的领域，就该让分析人员做他们最擅长的事情了。他们会考虑如何利用他们所学到的知识，并确定应该追求哪些具体的机会。

Opportunities for improvement within health systems abound, making it difficult for analysts to identify the best options to present to decision makers, but following these guidelines for approaching the data helps:

• Getting granular with the data– By drilling down to homogeneous patient populations by segmenting on severity, diagnosis, procedures, and more, populations become small enough for clinicians to confidently say that everyone in the population should reasonably be treated in the same way.
• Focusing on areas with both high cost and high variation-开始的焦点可以是垂直的，如临床服务线，或水平的，如跨组织的服务，如实验室，药物，再入院，或网络泄漏。(分析师应该记住，如果结果出色，有时高成本也无妨，所以将成本和变化结合起来很重要。)
• Looking for cost drivers– Searching for specific areas driving costs up is a good start. The areas may include room, supplies, OR, drugs, lab, radiology, respiratory, and other. From there, analysts can dig into deeper levels of detail.
• Examining variation-检查特定的设施或供应商的变化，可以洞察谁或什么导致了变化。上述顾问委员会的文章指出，大多数变异来自少数医生和设施(16%)。
• Analyzing the impact– Considering factors, such as length of stay, potentially preventable complications, or potentially preventable readmissions, helps analysts see the impact of variation.

Step 4: Presenting Opportunity Analysis Findings Using Graphical Interpretations

The last step of the opportunity analysis is to present the findings to the stakeholders and clinicians. Before analysts make presentations to teams throughout the organization, it’s important they are on the same page so there is continuity in the messages. Presentations should be both consistent and digestible, which helps analysts explain what they found in the data and helps others understand those insights.

当展示机会分析的结果时，分析师应该使用标准的图形解释来说明数据的故事。When talking about clinical variation, several visualization types present data well:

Control charts– A control chart illustrates variation in overall care and the variation over time, highlighting areas out of control. For example, data points going above the upper control limit, as seen in Figure 1, indicate that care delivery is inconsistent and warrants closer examination. If something is out of control, it provides a starting point for analysis, and the chart is a good visualization to show leaders the variation and thus the opportunity for improvement.

Bubble graphs– Bubble graphs highlight volume, cost, and variation within each location or providers. They should be used in conjunction with control charts. On the bubble graph, the x axis represents cost and the y axis represents the coefficient of variation. The size of the bubble represents volume (the larger the bubble, the greater the volume). The upper right quadrant of the bubble graph shows providers with high cost and high variation; these are often the best providers to investigate for improvement opportunities. The lower right quadrant gives good information as well because the bubbles represent providers with consistently high cost. The left quadrants represent providers with lower cost. These may be the best practice providers who have good insights to share.

Box plots-方框图突出显示一个地点或供应商内的变化范围，以及整体百分比，便于在不同类别之间进行比较。For example, providers above the overall 75^th百分位数表示改进的机会。

Move from Opportunities to Action

After analysts present the opportunity analysis and the group agrees on improvement initiatives to further explore, the finance team should investigate these opportunities to understand the population and financial impact of any proposed action. Together, the finance team, the analysts, and care teams agree upon a set of assumptions based on a series of questions:

• How is the care model changing?To successfully reduce variation and improve outcomes, it’s important for clinicians understand any necessary changes to care models.
• 驱动结果需要哪些步骤?任何改进计划的第一部分都是确定需要更改的内容。第二部分是创建一个具体的计划，包括实现预期结果的具体步骤。
• How can the steps be tracked?Tracking actions and progress is key to understanding how and why a change initiative works (or doesn’t). Throughout the process, organizations should use a tracking system that records steps taken and the results of those steps.
• 对患者护理的改变将如何影响财务状况(积极或消极)?在权衡成本与收益时，重要的是组织要考虑到，有时护理改进会损害底线，但如果好处大于成本，这些改进措施仍应被考虑。
• 这个项目有资格获得绩效工资计划吗?Pay for performance (P4P) programs can help recoup costs of a costly care improvement initiative. Many payers offer financial rewards for outcome improvements, so organizations may want to engage with payers about the potential of P4P eligibility.

Finance takes these assumptions and creates a model to predict the impact to the bottom line. This prediction should consider four factors: revenue loss, increased bonus from payer (P4P), net gain, and improved outcomes.

Bringing It All Together

改善医疗服务和结果对所有卫生系统来说都是必须的，而进行季度机会分析可以突出那些可以说是性价比最高的领域。利用数据进行机会分析是一种有效的方法，可以开始根除和解决不合理的临床变异，从而在改善结果的同时节省资金。在设计机会分析流程时，分析师必须记住四个关键步骤:从初步分析开始，与临床医生会面以收集输入，深入挖掘数据以进行进一步分析，并向决策者展示。遵循这四个基本步骤，并以数据为指导，可以帮助分析师识别和优先考虑机会。通过有效的数据分析和临床医生的参与，组织可以找到改善措施的机会，减少差异，节省资金，改善护理——所有的成功都有利于患者。

Additional Reading

你想了解更多关于这个话题吗?Here are some articles we suggest:

1. Reducing Unwanted Variation in Healthcare Clears the Way for Outcomes Improvement
2. Four Essential Ways Control Charts Guide Healthcare Improvement
3. Opportunity Analysis Permits Successful Execution of At-Risk Contracts

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