Implementing business intelligence and analytics projects within a Healthcare Organization (HCO) are challenging due to regulatory and financial pressures facing healthcare, the complexity of data involved, the multitude of stakeholders, and relative newness of BI technologies to healthcare. Below are some strategies that can help your HCO implement BI and analytics projects that become integral to healthcare improvement and innovation efforts.

1.   Get all stakeholders involved early and frequently. The IT specialists, program analysts, and clinical subject mater experts (SMEs) may be worlds apart in terms of aptitude, skills, and knowledge, but must work closely to ensure a successful BI implementation. Ensure key stakeholders (such as program leadership, project sponsors, clinicians, analysts, and technical specialists) are engaged early and communicated-with well throughout the project.

2.   Understand the needs of the users. The variety of ways in which information is utilized within an HCO can make it challenging to meet everyone’s needs. Develop a data utilization strategy in collaboration with end-users that outlines what information is required, how often it is required, what format it’s required in, and how they will access the information.

3.   Focus on comprehensive documentation. Not having clear, concise, and comprehensive documentation of available data will hinder ongoing maintenance and development of the analytics tools.  Mappings to source systems and associated workflows provide the necessary context to the information. Furthermore, as workflows and source systems change, they need to be documented and communicated to all stakeholders. This will ensure a consistent understanding and interpretation of information derived from the analytics tools.

4.     Keep the data relevant to the end-users. Strategic or executive dashboards are undoubtedly the “sexy” BI application. Healthcare professionals involved in quality improvement projects, however, will require detailed data based on metrics relevant to the processes being changed and evaluated. Many current process improvement methodologies used in Healthcare (such as Lean and Six Sigma) rely on frequent performance audits and detailed performance data to coach staff on new workflows and processes. The sooner issues can be spotted and brought to the attention of process owners, the easier it is to provide coaching and to manage overall process performance. Likewise, once a process has stabilized, quality teams will move on to other issues, and the analytics need to be  flexible to support these changes in focus.

5.   Set realistic expectations. Expectations naturally run very high after a BI implementation. It is important that all end-users understand that the analytics and BI tools will not result in an immediate resolution to all their information and/or quality improvement needs. Keep end-users informed as to the capabilities of the tools, including: what reports, dashboards, and other information tools are in-scope (and out-of-scope), what data is available for ad-hoc reporting, and what expected turn-around times are for new development and ad-hoc data requests.

Summary
Implementation of healthcare BI projects can be complex. These strategies will help set up a project for success, and more importantly, help healthcare organizations realize the quality and process improvement benefits that well-implemented BI systems can support.

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The number of healthcare analytics options are increasing.

Some HCOs have the benefit of a large Business Intelligence (BI) or analytics platform. These stand-alone BI systems are somewhat general-purpose in nature, and operate in many industries other than healthcare. Many of these platforms are powerful indeed, with many analytics functions and features available.

In addition to the traditional BI platforms, there are some special-purpose healthcare analytics tools; these boutique tools tend to combine standard BI and analytics functionality with healthcare-specific context built-in.

Finally, there is a growing trend for Healthcare Information Technology (HIT) vendors to offer a set of analytics tools as part of, or in addition to, their main-stream” clinical systems such as electronic patient record (EPR) systems.

Success factors for healthcare improvement analytics

Despite what vender literature might claim, the ability to do meaningful analytics work that can truly impact healthcare improvement does not necessarily depend on having extensive (and expensive) analytic and business intelligence platforms.The critical factors for successfully applying analytics to healthcare improvement projects are:

  • well defined and relevant performance indicators,
  • timely performance data,
  • appropriate analysis, and
  • dissemination of results to pertinent stakeholders.

Note that these success factors do not depend on having large BI/analytics platforms available. A common phrase in Lean Transformation initiatives is “creativity over capital”. Healthcare improvement initiatives with the benefit of extensive technology support (i.e., big BI, flashy dashboards, etc) can still fail whereas initiatives with more “modest” but innovative analytics approaches and tools can be likely to succeed. The difference, of course, is not which analytic tools where utilized (and how expensive they were), but how they were utilized, how well analytics were integrated into the initiative, and whether the results were acted upon.

Note: The above article is a sample from our special report, Overcome Common Barriers to Effective Implementation of Healthcare Analytics, available for download in the resources section.

 

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