Health Information Exchanges (HIE)

Deliver data and insights your participants can trust

Leverage a solution that fills gaps, improves consistency, and adds specificity for robust, reliable clinical patient data.

EHR integration

IMO Precision solutions leverage our deep expertise with point-of-care documentation to standardize inconsistent clinical data from diverse systems into consistent, structured, clinically validated terminology with the specificity required to identify cohorts and enable analytics.

Challenge

Exchanging accurate, complete patient data is crucial to your business

Whether your HIE supports patient alerts, assists in public health reporting efforts, or has plans to further expand your services, data is the foundation of all you do.  

But, when patient information is extracted from the EHR and moves throughout the ecosystem, it is not uncommon for data to be highly variable, full of gaps, and missing key components. This leads to more staff time spent manually filling those gaps, adding an unnecessary drain on clinical resources.

How we help

Meaningful insights start with quality data 

Rely on IMO’s industry-leading clinical terminology, used in 80% of EHRs

Reduce the manual burden on your team and accelerate your time to analytics with precise matching and data validation

Reapply missing standard codes and add other metadata, like secondary codes, for deeper insights 

Ensure consistency in diagnosis, procedure, medication, and lab data extracted from multiple systems and sources 

Ready for more reliable data and insights? Let’s talk.

Our team is eager to learn about your organization and ready to discuss how IMO can help.

Latest Ideas

Enhancing data quality initiatives across the health IT ecosystem

Getting all of your own medical information in one place can be a tough task. Now imagine gathering the data for a whole hospital, or even an entire state. Then, for good measure, throw in the fact that meaningful healthcare data analytics require that all these records be standardized before they can be useful. That’s where a normalization solution with a built-in clinical terminology layer can help.

Read More