Saving Lives Worldwide

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Gidi Stein
Co-Founder and CEO

MedAware

“Every catastrophic error we identify is a patient saved”

MedAware was founded owing to a tragic event when a nine-year-old boy died solely because his primary care physician accidentally selected the wrong drug by error on his electronic prescribing pull-down list. This mistake was not owing to bad judgment on the side of the physician, but rather simple human transgression, that unfortunately proved to be fatal. With the knowledge that legacy decision-support solutions failed to save this boy, a seasoned crew of physician-scientists and machine learning algorithm, experts discovered MedAware to ensure the highest level of security for providers and their patients.

Every year, hundreds of thousands of Americans are injured or fatally crippled by adverse drug events (ADE) and erroneous prescriptions. MedAware’s medication surveillance technology recognizes ADEs and eradicates catastrophic medication mistakes by applying advanced machine-learning algorithms and outlier discovery mechanisms similar to fraud detection solutions in control by financial institutions worldwide.

By continuously mining data accumulated via millions of electronic health records, the software can correctly flag potentially life-threatening prescriptions that struggle with the profile of the patient, physician, or institution.  Besides, MedAware actively observes each patient to identify and warn of situations in which differences in a patient’s diagnostic results renders one of his/her active medicines a dangerous outlier.

These difficult or nearly impossible to predict errors would otherwise go undetected by current rule-based answers.  The company’s unique, real-time approach to identifying ADEs and checking medication errors saves lives, improves patient safety and consequences, and significantly reduces avoidable risks and expenses.

MedAware’s platform recognizes and prevents medication-related errors and risks by applying exceptional machine learning algorithms and outlier detection mechanisms related to fraud detection solutions in use by financial institutions worldwide. By constantly analyzing and harnessing the practice models of thousands of physicians treating millions of patients around the world, the software accurately flags medications that conflict with the profile of the subject, physician, or institution.

MedAware’s patent-pending technology applies big data analytics and machine learning algorithms to analyze large scale data of electronic medical records, and determine automatically how physicians treat patients in real-life scenarios. Prescriptions generally deviating from standard treatment patterns are flagged as possible errors with high specificity and profound “alert fatigue.”

MedTech Innovator is the industry’s nonprofit global engagement and accelerator for medical tools, digital health, and diagnostic companies. The company’s mission is to improve the experiences of patients by accelerating the growth of businesses that are transforming the healthcare system. Medicine errors, where a patient has prescribed the wrong medication, are regrettably common. According to AHRQ, 5 percent of patients will encounter an antagonistic drug event, and roughly half of these are preventable ADEs that arise from prescription error. MedAware continuously monitors electronic health records to recognize these errors, which show up as outliers in the models of prescribing behavior.

“MedAware was purpose-built about our commitment to patient safety,” says CEO Gidi Stein. “Every catastrophic mistake we identify is a patient saved. Through this round of Series A funding, we will be able to create on the successes we’ve accomplished to date and scale our approach to protect physicians and their cases all over the world.” The company compares its approach to the algorithms banks apply to detect and prevent credit card fraud and identity theft. In both cases, immediately spotting an aberration in a design can safeguard against adverse outcomes before they occur.

The technology has already provided some encouraging efficacy data. In a study printed in January in the Journal of American Medical Informatics Association, researchers studied at five years of EHR-provided clinical data for 747,985 lives at the Brigham and Women’s Hospital and the Center for Patient Safety and Practice, plus retrospective data from Partners HealthCare BWH and Massachusetts General Hospital.