Five areas of focus for a healthcare business intelligence program

Defining healthcare business intelligence is the first step towards its use. A book on the subject has all of its definitions covered.

Depending on the background and experience of whom you ask, healthcare business intelligence can mean business oriented activities such as reporting and decision support all the way to more technical analysis of data warehouse content. Still other perspectives may be more encompassing and view business intelligence as a strategic information infrastructure to enable evidence-based business and clinical decision-making.

Business intelligence (BI) is a term that has different meanings to people within healthcare. The challenge for healthcare professionals to agree what BI is may make it difficult for healthcare organizations to establish an effective BI program of their own.

In her book Healthcare Business Intelligence: A Guide to Empowering Successful Data Reporting and Analytics, Laura Madsen states that healthcare BI is "the integration of data from clinical systems, financial systems, and other disparate data sources into a data warehouse that requires a set of validated data to address the concepts of clinical quality, effectiveness of care, and value for business usage."

Madsen's definition is important and immediately appealing because it encompasses healthcare BI from all the necessary angles. Her definition ranges to cover the technical to the cultural facets of healthcare organizations.

Madsen's five tenets of healthcare business intelligence

Madsen's five key tenets of healthcare BI include data quality, leadership and sponsorship, technology and architecture, value, and cultural change.

Data quality -- Having good data for analytics and quality improvement begins with the effective management of data. While growing volumes of data presents an exciting potential for use in quality and performance improvement activities, it is by no means a trivial task to ensure that this data is available -- and usable -- for such purposes. High data quality helps to drive trust in and user adoption of BI within healthcare.

Leadership and sponsorship -- The use of BI to support decision-making within healthcare may seem to be an obvious solution. Healthcare organizations, however, show amazing variation in their implementations. How well a healthcare organization supports the use of BI and analytics manifests in both the resource support of teams and the commitment of these organizations to use the technologies to enhance decision-making and improve outcomes. According to Madsen, "Long-term sponsorship requires full engagement and a knowledgeable staff."

Technology and architecture -- Madsen asserts correctly that BI is not an IT activity. It does, however, require the appropriate technical infrastructure and support activities. Given the siloed and somewhat discontinuous state of data in many healthcare organizations, Madsen writes that "investing in best practices associated with data modeling; extract, transformation, and load; and solid BI applications will ensure performance and scalability." In other words, without the proper technical and management structures in place, BI and analytics will be unable to provide the high-value insight that most healthcare organizations expect and require.

Value -- As part of improvement initiatives, many healthcare organizations consider value provided to patients during the course of care as an essential indicator of quality and performance. Healthcare organizations should similarly consider the value derived from their investment in BI. One way to achieve value from BI within healthcare is to focus its capabilities on problems and issues whose resolution would result in high-impact and high-value change.

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Cultural change -- The barriers to transformation in healthcare are rarely clinical, process, or technology-related, but stem from the fear, uncertainty, doubt and politics that result from change. BI professionals are often at the forefront of change within healthcare and need to collaborate effectively and diplomatically with many other professional groups -- including clinicians, administrators and IT professionals -- who may not understand how BI can benefit healthcare.

Collaboration, Madsen writes, is the glue that holds a good BI team together. This collaboration starts with a single encompassing definition of healthcare BI and an understanding of how BI can be leveraged within the organization. Building on the five aforementioned tenets, the many professionals from multiple disciplines working on healthcare improvement can begin to use the best evidence available and align improvement efforts and capabilities with the objective of achieving their stated clinical and business goals.

About the author:
Trevor Strome, M.S., PMP, leads the development of informatics and analytics tools that enable evidence-informed decision-making by clinicians and healthcare leaders. His experience spans public, private and startup-phase organizations. A popular speaker, author and blogger, Strome is the founder of HealthcareAnalytics.info, and his book, Healthcare Analytics for Quality and Performance Improvement, was recently published by John Wiley & Sons Inc.

This was first published in April 2014

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