Mpirik: Leveraging AI to Deliver Superior Cardiac Care at Scale

In spite of large-scale deployment of integrated healthcare systems in the U.S and around the world, many patients with heart disease continue to experience significant delay in treatment. Late treatment potentially compromises patient outcomes and leads to excessive cost. The root cause of this issue is not the slow adoption of new technology but the way in which patient healthcare data is screened for accurate and timely diagnosis. To this day, even though a patient’s health status is recorded digitally via an Electronic Medical Record (EMR), the process of screening the data is manual. This leads to inconsistency in the diagnosis of a patient, which often leads to delay and further complications. Addressing this challenge with its unique cloud-based and HIPAA-compliant platform is Wisconsin-based Mpirik. The company’s platform is designed to help clinicians leverage the consistency of a computer algorithm and objectively screen patients with cardiovascular disorders at scale. “Our platform screens the EMR and other sources for critical cardiovascular disease. We make this live data immediately actionable for disease experts. The result is timely treatment and 100% accountability for all patients," says Dr. Daniel O’Hair, Chief Medical Officer at Mpirik.

As a practicing cardiovascular surgeon, Dr. O’Hair has firsthand experience in dealing with the inefficiencies of consolidating a patient’s health data from disparate healthcare systems. Mpirik’s Cardiac Intelligence™ platform is developed with the aim to eliminate the manual, cumbersome, and inefficient patient data screening processes and close the undertreatment gap to zero for heart valve disease. At the same time, to ensure a completely seamless experience for physicians, Mpirik’s platform is EMR-agnostic and compliant with the Health Level 7 (HL7) standards for the transfer of clinical and administrative data. Additionally, the platform leverages artificial intelligence (AI) and natural language processing (NLP) to analyze an echocardiogram and identify critical data points. Following this, the platform runs the data through its proprietary rule-based engines and issues a recommendation to the referring clinician to guide doctors to make decisions for treatment according to clinically validated guidelines.

In cases where a patient has a moderate cardiac condition, the platform keeps them under surveillance and notifies physicians if they miss a necessary follow-up consult or exam.