macro-eyes began by solving clinical questions, built a multidimensional model of the patient and an approach for predicting outcomes, leveraged this technology to create a product for the predictive supply chain and is increasingly focused on the foundation of care, patient scheduling.
ACCESS TO CARE
Providers see more patients without adding hours to the day (increase margin)
Cut empty slots while reducing overbooking
Schedule becomes predictable (increase efficiency)
Prevent vaccine stockouts and cut waste through vastly improved forecasting, working to optimize supply.
Increase immunization coverage
Stabilize population health
Reduce vaccine wastage
Underpinning each macro-eyes product is a computational engine that detects and understands patterns in routinely collected data: patterns that are meaningful for personalizing the delivery and practice of care.
Patterns that are expressed multi-dimensionally are more predictive. The greater the number of clinical dimensions that are measured, the richer and more actionable the results.
Multidimensional queries allow providers to pinpoint the interventions or patient characteristic that consistently and uniquely lead to a specific outcome.
The machine learning at the core of macro-eyes products detects and analyzes the degrees of multidimensional similarity between patients and between events.
This engine allows macro-eyes to deliver deep insight on care pathways and patient risk, to determine the different medical devices that will bring optimal outcomes for different carefully defined cohorts of patients (patient phenotypes) and to predict with high accuracy the specific patients that will no-show for scheduled medical appointments.
The structure and scope of macro-eyes AI is informed by years of applied work with clinicians, data-scientists and administrators at health systems and leading academic medical centers in New York City and California.