Jun 7, 2017
Business intelligence in healthcare can yield real benefits to both the clinical and business sides of an operation by providing historical data, current trends and predictive analytics that influence decision-making.
But many organizations run into trouble getting BI efforts up and running. There are various barriers to healthcare business intelligence adoption, and many practices and problems that can result in low BI ROI. Here are a few common barriers to successful healthcare BI implementation.
Diverse Data Types
Data is mined from more than just electronic health records. Physician visits, pharmacy, lab reports, claims, billing and more all generate information as well that must be gathered, organized and analyzed. Wearable health technology also is beginning to add to the mountain of data. The sheer amount of data generated can be overwhelming to collect, store and carefully consider. Plus, much of this data is funneled through proprietary data models and even in differing data formats, and many of these technologies cannot communicate with one another.
Having the right tools to do the job is just part of the process. Healthcare companies also must have trusted and experienced vendors to help implement BI technology and processes, and they must have appropriate technology, operations and clinical team members as part of the BI team.
Shifting to an enterprise data warehouse is a positive solution. An EDW can overcome silos by serving as a centralized data repository for the organization, simplifying access and providing a complete view of data across financial, clinical and operational areas of the business.
Unclear BI Vision
Without a clear vision for the program, it can be near impossible to secure buy-in from end users of the technology. It’s critical to include end users in the early phases of development so that needs are met long-term.
A robust healthcare BI roadmap will include a program governance charter and structure, identify team members and leaders, describe how the program will be situated within the organization, outline responsibilities, and define costs and expected ROI.
This roadmap also should cover data governance, both needs and challenges within the current system and technology, and analytics capabilities and infrastructure considerations. Data resources, staffing the program, stakeholders, and change management for implementation also should be considered during the roadmap-building phase.
Because healthcare business intelligence gathers data that impacts a wide range of stakeholders within an organization, internal politics and competing interests can come into play. A sponsoring, high-level executive may help navigate potential conflicts, but an outside expert can provide objective influence that sets politics aside and focuses instead on the end goals and results.
Learn more about the ins and outs of implementing healthcare BI in our white paper.