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Customer Experience and Design

How Do You Find the Time to Make Business Intelligence Work?

I read a recent commentary, How Mature Is Your Hospital Business Intelligence System?, which caused me to wonder, is maturity of business intelligence truly feasible? Don’t get me wrong, there is absolutely a demand, or more so a mandate, to have a highly functioning business intelligence system. However, is there an understanding of what is needed to make this actually happen?

As noted in the commentary, The Advisory Board has provided good insight as to the cultural readiness for healthcare business intelligence (HBI). Although financial business_intelligenceincentives play a key driving force toward successful use of HBI, the time constraints from regulated incentives do not allow for hospitals to do the clinical and analytical transformations that are required. Analytic reports, predictive modeling and financial incentives are only as good as the data coming from the electronic health record.

What has Meaningful Use done to help? Hospitals should have already been able to successfully attest for Meaningful Use Stage 1 measures and should be moving towards upgrading to a certified Meaningful Use 2014 version for attestation and reporting in 2014. Even with the advancement of documentation, terminology and interoperability standards, there is still the need to manage both legacy and current data from multiple disparate sources.

If that isn’t enough to cause insomnia or a migraine, add in the challenges and duplication of abstracting critical data elements from unstructured clinical data from paper, scanned images or dictation. As long as I am on the topic of unstructured data, it provides an opportunity to circle back to the topic of business intelligence “maturity” to ask another question. Is natural language processing at a practical state in underlying technology and cost efficiency, that it can provide value in both clinician workflow and at a business intelligence backend for data mining and analytics?

As if Meaningful Use and ICD-10 adoption weren’t enough to keep hospitals busy through 2017 and beyond, add the complexity of the CMS rules and timelines for participating in an Accountable Care Organization or the Medicare Hospital Value-Based Purchasing Program. Beyond the reporting requirements, there is still an expectation that business intelligence can drive change in hospitals, as well as in ambulatory care, medical home and most importantly, the patient. The demands for data seem to be never-ending.

How does a hospital achieve not only mature business intelligence, but continue to grow and extend their infrastructure to an enterprise information management system with predictive modeling and tools to manage “big data”? While there are many helpful resources out there, such as Gartner’s Invest in Information and Analytics to Benefit from Big Data report, I think it is more useful to take a recommendation from Steven Covey’s The 7 Habits of Highly Effective People and begin with the end in mind.

Instead of just keeping up with regulatory and quality minimum requirements with fixed deadlines, is it possible to step back and look at the big picture of the current, but ever-evolving, future state? Despite the competing priorities that challenge the resources and day-to-day patient care activities, can hospitals get the needed time and resources to move ahead of the demand versus struggling to keep up? Let me know your thoughts!

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