- Core Functionality: Utilization management,Clinical workflow,Health and wellness management,Screening/ assessment tools
- Target Populations: Adolescents/ children,Elderly,Frequent emergency department users,Uninsured individuals,Medicaid beneficiaries
- Users: Family/ caregivers,Patients/ consumers,Medical providers,Peers and community health workers
Isabel Symptom Checker is based on Isabel’s curated machine learning and natural language processing artificial intelligence (AI) clinical engine — covering 6,000 conditions and all specialties.
Isabel Symptom Checker enables patients to enter symptoms in everyday language and helps them to both understand their symptoms and get appropriate care. Symptoms are then analyzed by the Isabel clinical engine and possible conditions are presented along with additional information so that patients can research their symptoms further. A ‘Where now?’ triage feature is also available to help patients decide where to seek care.
Isabel Symptom Checker can also be incorporated into a wide variety of workflows and contact points within health systems, Federally Qualified Health Centers, and critical access hospitals through either the native application or optional integration (e.g., built into public-facing websites, patient portals, personal health records, virtual e-visits, chatbots, etc.), to improve efficiency and the patient experience.
The Isabel clinical engine has been independently validated and vetted. Isabel has been found to increase both individual clinician’s and medical team’s diagnostic accuracy by as much as 33 percent. Additionally, in 10 percent of cases, Isabel notified clinicians of diagnoses not otherwise under consideration. Studies have also shown in 95 percent of cases that Isabel included the correct final diagnosis in its results based on the initial clinical features.
St Thomas Clinic, New Orleans; Copley Hospital; Relief International
Updated: July 2019
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