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Survey: Most Health Systems Lack Clear Data Analytics Strategies

September 15, 2015
by Rajiv Leventhal
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Fewer than half of health systems reported having a clear, integrated data analytics strategy, according to a survey of 50 health IT leaders conducted by the Deloitte Center for Health Solutions.

Conducted in 2015, the Deloitte survey targeted CIOs, CMIOs, and senior technology leaders in health systems, academic medical centers, and large (revenue greater than $500 million) individual hospitals. The survey’s intent was to understand these institutions’ analytics investments and priorities.

The survey shows that health system spending on analytics aligns with reported success in analytics and respondents agree that analytics investment is essential for value-based care (VBC). However, many organizations still lack a clear strategy, an effective data governance model, and effective budgeting models.

What’s more, health systems analytics adoption and investment is projected to grow, though perhaps not as dramatically or rapidly as some in the industry predict. Only five organizations reported that they expect their analytics spending to grow significantly in the next three years. Also, respondents at several organizations indicated they lack clarity on their current analytics spending, so it is difficult to determine their future spending. Explanations for this pattern may lie in challenges such as culture, operating models, and fragmented oversight. More than half of the respondents mentioned these factors as top barriers for analytics adoption. Other exacerbating factors may include lack of access to funding; numerous vendor product offerings, which may be confusing; and inconsistent industry definitions of analytics.

The survey found that, despite the proliferation of analytics offerings and many discussions about the need for analytics to support VBC payment and delivery models, health systems are still defining their enterprise-level analytics strategies and investments. According to more than 75 percent of survey respondents, clinical outcomes, population health, and cost efficiencies are top drivers of analytics investments today. Respondents expect this trend to continue over the next three years. Respondents also expect future drivers of analytics investment to include supporting new payment models, pursuing revenue growth, driving innovation, and improving the consumer experience.

Further, many surveyed organizations already have reporting capabilities in multiple business functions. Top capabilities that organizations plan to add in the coming three years and that they are targeting for additional investments include business intelligence and advanced analytics. Academic medical centers and separately health systems with revenues above $2 billion, reported that they are more likely to have advanced analytics capabilities today, although the medical centers based on survey results, appear weaker in forecasting capabilities and market intelligence areas.

What’s more, 15 of 50 surveyed organizations report they do not track their overall spending on analytics, indicating potentially fragmented coordination of analytics capabilities. Seven organizations state that their analytics budget is currently zero percent of the enterprise operating budget; this could be due, in part, to a broad range of analytics definitions, the researchers concluded. There are some indications of spending  growth: five surveyed organizations with analytics budgets of one-to-five percent of the enterprise operating budget expect their analytics budgets to increase to six-to-10 percent in the next three years.

Twenty-one of 50 respondents report that they do not have a formal enterprise-level data governance process and only six have a chief analytics officer. However, three out of four organizations have a department dedicated to delivering analytics to the enterprise. Nearly half of respondent organizations lack centralized oversight of analytics tasks and functions.

Finally, culture, fragmented ownership, and access to skilled resources are the top challenges health systems face with analytics adoption. Access to data is the least-influential barrier, although data quality is a barrier reported by almost half of the survey respondents. For smaller organizations (those with revenues of $500 million to $1 billion), access to skilled resources and access to funding for enterprise analytics continue to be significant barriers.

The researchers concluded, “The need for mature analytics capabilities is expected to grow as the healthcare industry moves to increased digitization, and health systems participate in VBC arrangements that require insights to support more effective decision-making. Organizations will need more sophisticated tools and capabilities to be able to integrate, analyze, and leverage their data.”

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