When IMO Health’s, 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.
