Infographic - Clinical Suite

Features


Best-in-Class NLP Engine


  • Understands the complexities of clinical language -- including grammar, syntax, context, and intent
  • Applies proprietary algorithms and logic to identify a set of patients or features that align to the model’s purpose, like uncovering patients with diagnosis gaps or documentation that lacks specificity, at cascading degrees of confidence
  • Provides the greatest depth and breadth of industry standard terminology support, including SNOMED, ICD-10, RxNorm, and LOINC
  • Creates a universal clinical source of truth via a comprehensive patient profile that unites structured data elements to the newfound clinical information

Convert unstructured data - like physician notes entered in an EHR - into a structured extraction of clinically meaningful intelligence that can be systematically processed by machine to derive predictive insights.


Point-of-Care


  • Uncover up to 35% verified codes over retrospective passes for more effective care plans inclusive of all comorbidities
  • Impact all risk adjustable populations at the point –of care, freeing physicians from excess administrative time through documentation support within the EHR
  • Generate patient and provider insights that drive performance, population health, condition targeting, patient outreach, and more
  • AI-powered, risk focused chart preparation support that refocuses risk adjustment around the patient, changing a traditionally actuarial processes to a real, clinical utility

Surface highly likely risk adjustable conditions directly at the point-of-care, equipping providers with a new patient care tool within the EHR.


Post-Encounter Review


  • Perform in-depth, NLP supported reviews of codes prior to submission, enabling Medicaid and ACA RAF capture in all 50 states
  • Shorten A/R cycles and forecasting from years to months with increased confidence due to faster and more accurate payment turnaround
  • Shift any coding burdens off providers and back into the hands of coding experts

Ensure that missing diagnoses and incomplete documentation are corrected prior to claim submission by administrative staff (i.e., coding or billing staff) at physician practices.


Pre-Visit Planning


  • Go beyond claims-based reconfirmation and add net-new conditions identified from unstructured data
  • Submit with confidence knowing each new condition is clinically validated during encounter processing
  • Improve care and reduce emergent visit costs with NLP supported chart preparation and patient targeting
  • Net fuller, more accurate value-based care payments by ensuring that risk scores, an assessment of disease burden and a deciding factor in funding, are routinely evaluated

Flag suspected risk adjustable conditions for review within the care delivery workflow, allowing outpatient practices to quickly evaluate and route diagnosis gaps for closure to facilitate a more thorough level of care.