CLINICAL DECISION SUPPORT

Isabel

Physicians around the world use Isabel to help construct or broaden a differential diagnosis. By entering the information normally captured in a patient workup, Isabel provides physicians with a list of possible diagnoses to help them construct their thinking and make an accurate final diagnosis quickly and easily at the point of care.

The Premier Diagnosis Decision Support Tool

Isabel helps clinicians improve diagnosis quality, leading to more cost-effective care through:

  • More appropriate tests and referrals
  • More appropriate admissions
  • Reduced length of stay
  • Increased patient satisfaction
  • Reduced clinical risk
  • Ensuring the appropriateness of care
  • Reducing litigation risk
  • Supporting medical education and training
  • Encouraging review of the latest evidence via DynaMed

A Valuable Resource at the Point of Care 

Isabel can be deployed either as an integrated part of the electronic health record (EHR) system or as a standalone application. Isabel uses the information routinely captured during the patient workup—whether free text or structured data—and instantly provides a differential diagnosis checklist for review.

Isabel flags critical “don’t miss diagnoses” and diagnoses that could cause significant harm if not considered. When integrated into an EHR system, Isabel can provide one-click seamless diagnosis support with no additional data entry.

Seamless Integration with DynaMed

Experience powerful clinical decision support by combining the premier diagnosis technology of Isabel with the latest evidence-based clinical information from DynaMed. Isabel and DynaMed work together to give physicians the evidence-based information they need to provide the best care to their patients.

Clinicians can easily start their diagnosis journey from either platform by accessing Isabel differential diagnosis from the DynaMed homepage or linking directly to DynaMed topics from Isabel's list of potential diagnoses.

Peer-Review Validation

Isabel has set standards for the clinical testing of decision support systems in health care, having undergone a robust, peer-reviewed validation process to demonstrate its accuracy, effectiveness and value.

Dozens of articles, including independent clinical studies, multi-center collaborative studies and internal studies have appeared in prestigious peer-reviewed journals.