Misdiagnosis of a disease and its conditions can have life-threatening consequences. Each year, approximately 12 million Americans experience some form of diagnostics mistakes while seeking outpatient services. A study by the Institute of Medicine (IOM) found that diagnostic errors and other inefficiencies cost the US economy a staggering $750 billion each year.
The early and accurate diagnosis results in a potentially significant reduction in patient cost burden and improves the ability of the HCPs to provide better treatment and improve patient prognosis.
Axtria brought its deep expertise in the predictive analytics and applied Machine Learning models in identifying misdiagnosed patients and helped the client onboard its patients on drug treatment much earlier, improving the health outcomes.
A high degree of accuracy in predicting the likelihood
of misdiagnosis using innovative Machine Learning techniques
Identified several key indicators that help recognize the
misdiagnosis disease states
Recommended a target HCPs list who diagnosed the predicted misdiagnosed patients
Improved the commercial opportunity with the
future analysis recommendations
Read this illustration to know how Axtria enabled accurate and early diagnosis and treatment of patients using machine learning (ML) modeling.
Download the free case study here.
Contact us at firstname.lastname@example.org with any questions.
Axtria’s solutions and services are tailored