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Scottsdale Institute 2017 Business Analytics Fall Summit: Constructing an Analytics Strategy

December 22, 2017
by Janice Wurz and Dan Golder, Impact Advisors
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Experts collaborated in Chicago to share best practices and discuss challenges as they march forward in their data analytics journeys

The Scottsdale Institute convened data, analytics and information executives from across the country for the 2017 SI Business Analytics Fall Summit in Chicago on October 4-5, 2017. Attendees—representing large academic medical centers, multi-regional health systems, rural hospitals and clinics—gathered to share strategies, concerns, insights and lessons learned on the journey towards an “analytics utopia” with specific focus on the governance, staffing, and management of data and analytics in an ever-changing healthcare environment.

Analytics Fall Summit Participants

Stephen Ameen, IT director of revenue cycle systems, Houston Methodist; Rick Howard, vice president, data & insights, and chief data officer, Ascension Information Services; Ben Isenhour, regional chief information officer/ vice president of advanced analytics and architecture, Eastern Maine Healthcare Systems; Brett MacLaren, vice president, enterprise analytics, Sharp HealthCare; Julia Swanson, vice president, performance analytics & improvement, Henry Ford Health System; Yohan Vetteth, chief analytics officer, Stanford Health Care; Michael Wall, Pharm.D., chief analytics officer, University of Chicago Medicine; Glenn Wasson, Ph.D., administrator of analytics and performance measurement, University of Virginia; Christine Watts, (former) chief enterprise architect, University of Chicago Medicine; Kerri Webster, (former) director information technology, Centura Health

Organizer: Scottsdale Institute; Sponsor: Impact Advisors; Moderator: Impact Advisors (Janice Wurz)

Current State & Data Delivery: Data Rich, Information Poor

The Summit kicked off with participants sharing their insights regarding current state and data delivery methodologies. All feel reasonably successful in assembling and acquiring data, yet providing meaningful data continued to prove elusive. As expressed by Stephen Ameen, IT director of revenue cycle systems, Houston Methodist, “We find ourselves ‘data rich’ yet ‘information poor.’ We are not getting the intended value from our data.” Yet there was agreement that this quandary also represents significant opportunity. Participants viewed their organizations as ready to leverage data to assist with decision making—and believed they are “data-ready” if not yet “data-driven.”

Does Your Organization Trust Your Data?

Level of trust is dependent upon the available data, its stakeholders, the problem itself, and who is asking the question. Business and financial users are more comfortable with data; clinicians (particularly physicians) are more likely to question validity. The primary challenge with clinical data is that it is less structured for data collection. For example, data elements such as blood pressure are documented in numerous, different places in the medical record making standardization difficult.

“Trust is also contextual,” Rick Howard, vice president, data & insights & chief data officer, Ascension Information Services, commented. “Many times data may be slightly wrong, but it is the same ‘wrong’ for everyone, therefore it can still be directionally correct” and can help foster better business decisions. Yohan Vetteth expanded on that line of thinking, saying, “You can gain incrementally more value from improving the data standardization process, however, it is not always necessary to wait for data to be completely accurate to make a valid and useful decision.”

Engaging users as “co-owners” of data remains critical to improving trust. Trust gets established during stakeholder conversations when data is being assembled and metrics are being developed. “Creators and consumers of data should work together to define the needed data definitions,” noted Christine Watts, (former) chief enterprise architect, University of Chicago Medicine. Documenting and communicating data sources also fosters trust.

Ownership vs. Stewardship: Data Governance

All agreed that collaboration among operational and technical stakeholders is required for data analytics to be successful. Yet there was some misalignment in defining the roles of data “steward” vs. data “owner.” Some organizations use the terms interchangeably; others align them to IT and operations. Those differentiating the two felt business owners, who understand the challenges the particular data are supposed to resolve, are best defined as data owners, while data stewards would be those accountable for the data definition and appropriate use of the data by the organization, and usually affiliated with IT. The group observed that distinguishing between these two roles reflects evolving views toward data governance—looking beyond the traditional centralized governance model to more hybrid federated models.

Glenn Wasson, Ph.D., administrator of analytics and performance measurement, University of Virginia, expressed that progress can often be encumbered when business units are not standardized, and services not unified. Finding a reasonable way to ensure everyone is using the same data, and same data definitions, poses a significant challenge. This cascades to ensuring that data standards and data governance become foundational structures as organizations evolve their analytics capabilities.


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