Charting the future of healthcare with ambient AI
Ambient AI is reshaping clinical documentation, streamlining workflows, and has the potential to facilitate downstream use cases and accelerate innovation.
IMO data quality management solutions leverage our deep expertise in 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.
The goal of the CDC’s Data Modernization Initiative (DMI) is to make patient information more readily available through electronic case reporting (eCRs) and file standardization. But many providers rely on outdated, manual methods of capturing data, including pen, paper, and fax to report cases. These systems result in delays, underreporting, and incomplete data. Additionally, varied documentation at the point of care further complicates the task of effectively normalizing data for integration into a unified public health data system.
Leverage IMO’s industry-leading clinical terminology and comprehensive code mappings, used in 80% of EHRs and comply with evolving eCR standards
Reduce the burden of manual updates through automated standardization of terms and codes such as ICD-10-CM, SNOMED CT®, RxNorm®, and LOINC®
Ensure consistency in diagnosis, procedure, medication, SDOH, and lab data extracted from disparate systems and sources
Reapply missing standard codes and add other metadata, like secondary codes, for deeper insights
