Healthcare Business Intelligence: What Your Strategy Needs

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reporting and improve its efficiency in three ways:

1. Enabling a More Efficient, Scalable Reporting Process

Typically, hospital or group practice executives meet to determine the categories of healthcare data they need to track progress toward strategic goals. They may already have a process in place for getting financial data. But now, with new value-based purchasing pressures requiring clinical and financial data, organizations suddenly are tasked with getting more data than ever before. Questions may arise, such as:

  • Where do I start?
  • Who do I approach for the data?
  • Where is the data stored?
  • How do I get at the data after I’ve found it?
  • How do I compile and make sense of it?

Locating the right people with the right data – whether it’s a single person who updates an Excel document or a team overseeing a database – is a time-consuming, manual process. Staff spends a lot of time setting up this process to gather and compile data to keep executives up to date.

A healthcare EDW streamlines and scales this process. It integrates disparate data from a wide variety of sources, including billing, financial, patient satisfaction and clinical sources. Executives can access the information in the same place every month. And with the tools the healthcare EDW delivers, staff can analyze and interpret the data, running visualizations and reports, and gain insights into new and better ways to achieve quality and cost goals.

Texas Children’s Hospital in Houston, the nation’s largest children’s hospital, has significantly improved efficiencies with EDW information delivery. On average, each EDW report costs 70 percent less to build than an EHR report. And, because the EDW visualizations enable end-users to quickly and easily drill down into the data, one visualization replaces 10 static EHR-generated reports.

2. Ensuring Consistent Data That Everyone Can Trust

Too often during meetings, people will present conflicting data or diametrically opposed trends in the organization’s performance. Why does one team member’s data show a different trend in net income than another’s? Why does one clinical leader show that length of stay (LOS) is going down while another clinician’s shows the opposite?”

When people throughout an organization access information in many different ways and from many sources, variability is common. The question is: Which data can the organization trust?

A healthcare EDW establishes a single source of truth and enables healthcare analytics. When data definitions and tools are consistent, as in a healthcare EDW, everyone – from frontlines to leadership – can rely on the accuracy of the information used to drive critical decisions. An EDW also serves as a foundation for developing and maintaining a data governance program. With such a program, data owners and experts can identify data issues within the organization, resolve them, determine who needs to use the data and define the best access path to the data.

3. Enabling Meaningful, Targeted Quality Improvement

On an ongoing basis, multi-disciplinary teams from across clinical, technical, financial, quality and performance excellence departments can use the EDW to identify opportunities for improvement. The organization then can develop and deploy highly targeted, specific interventions to promote those improvements in care, whether it’s lowering the rate of septicemia or eliminating unnecessary X-rays.

Consider this real-world example. When North Memorial Health Care adopted its EDW, the first order of business was to use it to identify areas of potential improvement. The organization landed on elective, pre-39-week deliveries as its first project. Jon Nielsen, M.D., medical director of women’s and newborns service at North Memorial, noted at the time, “We wanted a project that we could get up and running quickly. Reducing deliveries before 39 weeks was an excellent launch point because there is significant peer-reviewed research in that area. And if we solved the problem, the scale of the services would allow us to significantly improve care as well as reduce costs quickly.”

North Memorial established a service-line guidance team of OB/Gyms, primary care physicians, nurses, data architects and outcomes analysts who standardized the workflow and created improved processes including, among other things, a checklist of requirements to determine if a specific early-term delivery was a medical necessity before it was scheduled.

The efforts paid off with the results showing a 75-percent reduction in elective, pre-39-week deliveries in just six moths. The win had another nice effect, too: it resulted in more requests for projects. That single source of truth, the EDW, continues to enable improvements to the hospital’s cost and quality of care delivery.

Getting the Best Clinical Data Warehouse for Healthcare

The traditional approach to EDW architecture can be described as “early-binding.” Prevalent in industries such as retailing that adopted data warehousing decades ago, early-binding data warehouses extract data from source systems and “bind” those data to business rules. In doing so, the data warehouse optimizes data for analysis and retrieval. This platform architecture applies business rules or data-cleansing routines very early in the data warehouse development lifecycle.

Early-binding approaches using enterprise data models are appropriate for business rules or vocabularies that change infrequently or in cases where the organization needs to “lock down” data for consistent analytics. It works great in industries including manufacturing and retail where products and/or components are well known and easily defined. In healthcare, however, the decision to bind early can have a huge, often negative impact on the success of data warehousing projects, particularly when early data binding removes key components of the data that would have been beneficial in later analysis.

Renowned healthcare organizations including Allina Health, Children’s Hospital of Wisconsin, Crystal Run Healthcare, Indiana University Health, Kaiser Permanente, Memorial Hospital at Gulfport, MultiCare Health System, North Memorial Health Care, Providence Health & Services, and Texas Children’s Hospital are opting to bind their data later using a different EDW architecture: a Late-Binding™ data warehouse.

The Late-Binding™ platform architecture delays the application of business rules (such as data cleansing, normalization and aggregation) to data for as long as possible, so clinicians have time to review and revise data, form hypotheses, and determine optimal analytic uses. Late binding is especially ideal for what-if scenario analysis and best suited to ever-changing healthcare data.

The Late-Binding™ model accelerates time-to-value. Instead of spending months and even years to bring up a data warehouse, many customers have launched in weeks. Indiana University Health, with 18 hospitals, 3,300 beds and 3,700 physicians, brought their Late-Binding™ Data Warehouse live in 90 days, including 14 billion rows of data representing over 10 years of clinical, financial, and patient satisfaction information.

Late-Binding™ data warehouses are also more scalable and adaptable to the problems healthcare organizations are trying to solve. Healthcare is undergoing changes to business rules and vocabulary at an unprecedented rate. A Late-Binding™ data warehouse provides not only faster time to value, but also the agility necessary to meet today’s healthcare analytics demands.

A data warehouse developed with a late-binding architecture is the right platform for the healthcare industry because it has proven successful in numerous implementations by health systems across the country. This architecture has a track record of rapid time to value and the ability to address the demands of accountable care organizations. You can read a more detailed explanation of the Late-Binding ™ architecture here.

 Conclusion

Organizations and their leaders can harness the power of an EDW to streamline and scale reporting processes, maintain a single source of truth that everyone can trust, and drive meaningful, targeted quality improvement. By delivering analytics to clinicians and analysts on the frontlines of care — as well as to executives in the boardroom — healthcare organizations can critically evaluate care processes and aggressively pursue the best opportunities for improving outcomes. In doing so, healthcare organizations will be rewarded with clinical and financial success in a rapidly evolving healthcare landscape.

How do we get there? Gartner’s 2014 report may sum it up best: “Integrating business/financial and clinical data into an effective EDW is the top new IT initiative for CIOs once a generation 3 EHR system is deployed. …The value of the integrated EDW is high for organizations whose leaders grab hold of it with both hands.”6

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Endnotes

  1. Shaffer, Vi and Mark A. Byer, “Top Actions for Healthcare Delivery Organization CIOs, 2014; Avoid 25 Years of Mistakes in Enterprise Data Warehousing,” https://www.gartner.com/doc/2664433/top-actions-healthcare-delivery-organization, Gartner, Inc., February 10, 2014.
  2. Frost & Sullivan, “Drowning in Big Data? Reducing Information Technology Complexities and Costs for Healthcare Organizations,” July 14, 2011.
  3. HIT Consultant, “Big Ways Big Data Could Add Value to Healthcare,” http://www.hitconsultant.net/2013/05/29/big-ways-big-data-could-add-value-to-healthcare/, May 29, 2013.
  4. Shaffer, Vi, “Hype Cycle for Healthcare Provider Applications, Analytics and Systems, 2013,” https://www.gartner.com/doc/2568915/hype-cycle-healthcare-provider-applications, Gartner, Inc., July 31, 2013.
  5. American College of Healthcare Executives, “American College of Healthcare Executives Announces Top Issues Confronting Hospitals: 2012,” http://www.ache.org/Pubs/Releases/2013/Top-Issues-Confronting-Hospitals-2012.cfm, Jan. 7, 2013.
  6. Shaffer and Byer, 2014.
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