A framework for improving healthcare data analytics

All healthcare organizations collect data at some level, but are their analytics progressing to a mature and usable state or stalling out? This model can help move the dial.
healthcare data analytics

When IMO’s Chief Strategy Officer, Dale Sanders, originally published the  Healthcare Analytics Adoption Model a decade ago, one of the key goals was to provide a framework to progress healthcare data analytics and improve medical decision-making. 

As an early adopter of the use of data warehouses in healthcare, it was important that he create a model that was easily digestible and put his many years of lessons, mistakes, and successes to good use. And in 2012, the Healthcare Information and Management Systems Society (HIMSS) took notice, implementing an amended version of the model for use as an international standard.

The Healthcare Analytics Adoption Model consists of nine levels (starting at zero) for organizations to progress through, with level 8 being the most mature:

Level 0 Fragmented Point Solutions
Level 1 Enterprise Operating System
Level 2 Standardized Vocabulary and Patient Registries
Level 3 Automated Internal Reporting
Level 4 Automated External Reporting
Level 5 Waste Care Variability Reduction
Level 6 Population Health Management and Predictive Analytics
Level 7 Personalized Medicine & Prescriptive Analytics
Level 8 Direct-to-Patient Analytics and Artificial Intelligence

Take a closer look at each level of the framework in our on-demand webinar, The Healthcare Analytics Adoption Model: Updates for today’s health IT challenges, and learn why comprehensive clinical terminology is integral to improving the intent of your analytics.

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