Business and Clinical Intelligence Programs in Large Integrated Delivery Networks

DATA ANALYTICS HAS moved front and center onto the healthcare stage. But we are only at the beginning of our journey in using data analytics to improve healthcare quality and efficiency and to move the needle with respect to improving population health. Carolinas Healthcare System and Sentara Healthcare, the two organizations featured in this issue, are at the leading edge of this effort to become data-driven cultures.Commonalities of DataDriven OrganizationsAs executive vice president of HIMSS Analytics in Chicago, I have worked with leading organizations that are similar to Carolinas Healthcare System and Sentara Healthcare in their use of big data. The two organizations are also similar to each other in certain respects. Both have achieved the HIMSS Analytics Stage 7 designation on the Electronic Medical Record Adoption Model (EMRAM) because of their mature use of electronic health record (EHR) systems and deployment of data and processes to improve care quality, safety, and efficiency through information technology (IT). (The EMRAM consists of eight stages, ranging from Stage o [the organization has not installed all three key ancillary department systems] to Stage 7 [a paperless, intelligent, enterprise-wide EHR]. As of December 2015, 4.2 percent of US hospitals had achieved the Stage 7 designation.) As part of the Stage 7 validation process, in which I participate as one of several validators, applicant organizations must present three case studies that show how they have used analytics to improve quality, safety, and efficiency. I see some common themes across these organizations, but Carolinas Healthcare System and Sentara Healthcare also exhibit some leading-edge indicators.Data GovernanceClinically integrated networks and accountable care organizations need to use well-curated data to achieve continuity of care. Improving health and eliminating unnecessary consumption of healthcare services are the key goals of the electronically enabled care continuum across settings. Both Carolinas Healthcare System and Sentara Healthcare are using advanced analytics to achieve these goals, even though doing so is not easy. For example, as Kern, Reagin, and Reese explain, Sentara Healthcare had to integrate data from 73 practice management systems and 69 EHR systems. To ensure that data are compatible, an organization has to establish a true data governance process whereby every data element has an owner responsible for defining the data element and using it appropriately. Dozens of data sources mean thousands of data elements, and thus we begin to see the scope of the challenge facing these two organizations. However, creating a data governance process is absolutely necessary to ensure data compatibility and integrity and, thus, instill confidence in the resulting analysis.A Centralized, Multidisciplinary Analytics TeamBoth Carolinas Healthcare System and Sentara Healthcare have undergone the painful process of centralizing their analytics structure, an industry best practice that achieves several clear benefits but at some local costs. The benefits include building "bench strength" and increasing skills as team members learn from each other in a centralized group. All the major clinical disciplines need to be represented on the team along with a demographic specialist who understands the patient- and payerspecific data collected in the administrative systems. A corollary benefit is a unified budget for business intelligence, which allows potentially greater investments in technology and people skills. The painful side is that people are effectively pulled from their "home" and possibly from someone's pet project. Both organizations have passed that point and made great strides in creating an enterprise-wide, data-driven cultureUsing Data to Tell the StoryThe authors of both feature articles speak of the need for actionable data to improve outcomes and organizational behavior. …