Wal-Mart and the Birth of the Data Warehouse
managers quickly notified all store managers to display the computer in a similar fashion, highlighting the combination of a computer and printer for one low price. By the end of the day, sales in other stores had reached the levels of the original store. The integration of data from disparate sources enabled new understanding of business processes. The culture of Wal-Mart to quickly leverage this new understanding and adjust their business processes in real-time, underscored the power of combining analytic technology with a data-driven culture.
The Healthcare EDW Value Equation
The fundamental business or clinical purpose of a healthcare data warehouse is to enable behavioral change that drives continuous quality improvement (CQI) – that is, greater clinical effectiveness, efficiency and cost reduction. To achieve those goals, it’s not enough to design and deploy an advanced technology platform like the Health Catalyst late-binding TM data warehouse. Technology alone is not enough. The objective remains: Measure > Understand > Change behavior > Improve quality. If your EDW isn’t partnered with a culture of continuous quality improvement that engages the people in the organization who can implement behavioral change, the EDW technology will be branded a failure. For this reason, it is critical that the leadership of an EDW project also take an active role in ensuring that the technology is used in a meaningful way. Data warehouses have their own form of meaningful use, very similar in concept to the Meaningful Use of Electronic Health Records.
Making Your Data Work for You
At Health Catalyst, we address that problem head-on by empowering our clients to become data-driven organizations that meld data with action. We combine over 20 years of experience in healthcare continuous quality improvement with an adaptable, agile analytic technology platform. Analytic results from the EDW are delivered to clinicians and analysts in reports and graphical formats, with eye-catching charts and graphs that help them prioritize the areas of care that represent the largest opportunities for improving outcomes, and highlight specific measures for improvement. The care processes examined include not only the chronic diseases typically targeted by hospitals for outcomes improvement programs but also procedure-specific clinical processes.
On an ongoing basis, multi-disciplinary teams from across the clinical, technical, financial, quality and performance excellence departments meet to evaluate the organization’s quality measures and use the EDW to identify opportunities for improvement. We then co-develop and deploy highly targeted, specific interventions to promote those improvements in care, whether it’s reducing early-term deliveries, lowering the rate of septicemia, or eliminating unnecessary X-rays.
The history of data warehousing is littered with failures, especially in healthcare. Many of the early attempts at building data warehouses were motivated by improving access to data—reducing the labor associated with retrieving and loading historical tapes– without much regard for improving decision support in the organization. The Wal-Mart data warehouse evolved, quite literally, without any top down requirements analysis, without any attempt to calculate its prospective ROI, without a data governance structure, and without formal business sponsorship. It grew from the bottom-up and organized itself, from the roots of the organization.
At Health Catalyst, our team is comprised of the deepest talent for analytics in healthcare and would rival that in any industry. In our careers, we’ve had great successes—and great failures. And in that combination lays a solution for today’s healthcare market that is unparalleled. We are not your typical vendor in healthcare IT. Our clients are living proof of that truth, every day. The rate of change in the healthcare industry doesn’t allow for failures of any significance anymore, especially in analytics and data warehousing. For Health Catalyst and our clients, failure is not an option. Success is all we do.
How do you define a healthcare data warehouse?