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Will healthcare business intelligence (BI) be the answer that hospitals are looking for as they move to data-driven healthcare improvements and cost reductions? Yes … provided it’s built on the foundation of a data warehouse. Here’s why.
Healthcare is changing rapidly and so is the industry’s need for analytics and business intelligence, which brings up a problem: what exactly IS healthcare business intelligence? The term itself has multiple meanings and can be difficult to define, which leaves organizations that know they need a solution wondering exactly where to turn.
The trouble stems from the overuse of the term “business intelligence.” Sometimes business intelligence refers to a broad category of analytics, data warehousing and visualization tools, all of which are must-haves for any long-term and sustainable analytics foundation. Other times, business intelligence tools are linked to the visualization layer only – those tools that take the data and return a visual representation of it. Vendors including Qlikview, Tableau, Business Objects and Powerpivot work primarily with tools like this.
The more precise way of for healthcare to look at business intelligence may instead be in terms of a strategy – what’s your business intelligence strategy? Regardless of your organization’s answer, that strategy has one common and critical element: the need for a fundamental and foundational clinical data warehouse.
Where Healthcare Business Intelligence and Analytics Stand Today
Independent research firm Gartner, Inc., notes in its 2014 report, Top Actions for Healthcare Delivery Organization CIOs, 2014: Avoid 25 Years of Mistakes in Enterprise Data Warehousing, that the lack of a BI strategy is one of “nine fatal flaws in business operations improvement (BOI)” in healthcare. “Most vendors working in healthcare and other industries observe that healthcare has the most-complex data of any industry (possibly excluding government intelligence efforts),” the report states. At the same time, organizations aren’t yet fully tackling their wealth of data. “The biggest flaw of all is the lack of a documented BI strategy, or the use of a poorly developed or socialized one.”1
How big is the disconnect between data created and data digested? In 2010, Frost & Sullivan estimated that nearly 1 billion terabytes of data were held by hospitals and medical centers2 – a number they project will grow to more than 40 times that amount by the end of the decade.3
Tackling the data paints a less rosy picture. Gartner’s Hype Cycle for Healthcare Provider Applications, Analytics and Systems, 20134 report found that enterprise data warehouse (EDW) market penetration was in the “very low end of the 5% to 20% category,” and “many health systems are still struggling to gain top executive commitment, justify the investment, build strong information governance and settle on an approach.”
The value of the best EDWs comes to this: U.S. healthcare is undergoing dramatic, unprecedented change. The industry is shifting from fee-for-service to fee-for-value, yet without the historical investment in analytics technology so common in other industries and so essential to success. With healthcare reform and emerging models of care delivery, hospitals and medical practices need EDW solutions to reliably answer mission-critical questions about performance – as-is versus “what-if scenarios” and as-is versus competitor performance. Harnessing the combined data of clinical, financial, quality, cost and patient experience sources, EDWs enable such complex analysis. These platforms can help produce, for example, a monthly summary of operational value, defined as “outcomes per dollar spent.”
Understanding the Clinical Data Warehouse and BI Tools
In terms of business intelligence, the essence of data warehousing is measurement that leads to understanding, insight and action. In general, a data warehouse is a centrally managed and easily accessible copy of data collected from the transactional information systems of a corporation or health system. These data are aggregated, organized, catalogued and structured to facilitate population-based queries, research and analysis. Such queries, research and analysis enable measurement, which in turn enables understanding and the most informed business and clinical decisions.
The data in a data warehouse come from multiple source systems. Source systems can be internal, such as electronic health records (EHR) systems, costing or financial systems, or patient satisfaction systems; or external, such as systems associated with a state or federal government (e.g., mortality data or cancer registries).
Think of a data warehouse as a very large, very specialized kind of library – a centralized, logical and physical collection of data and information that is used repeatedly to achieve greater understanding or make the most informed decisions. Like a well-stocked library, the utility of a well-designed EDW is nearly limitless.
Three Key Benefits That BI Realizes with a Clinical Data Warehouse
The American College of Healthcare Executive’s (ACHE) annual survey of the top concerns of hospitals found that financial performance topped the list for 2012, followed by patient safety, outcomes and healthcare reform implementation. 5 To address these concerns with the most informed decisions, management teams require reliable, comprehensive information spanning the enterprise.
In response, finance, quality, human resources and clinical departments at health systems and group practices scramble to compile data for their reports. Once departments complete this task, they must combine their reports so management can review progress on organizational goals. Management wants to see the big picture and draw valid conclusions about quality, satisfaction and cost performance across the organization.
While this is a challenging, time-consuming process, a healthcare EDW can ease management
