Our Story

The magnitude of the patient no show problem - $150 billion lost each year - took our founding team, former Johns Hopkins Public Health data scientists, by surprise. And the financial impact is only a symptom of the underlying problem. Ultimately, no shows mean patients go without care and healthcare groups can't efficiently use their resources.

Digging into what others have done on this topic, we found numerous academic studies that explored the merits of predictive no show models, both in determining which patients are most at-risk of no showing and how to most effectively overbook. For some examples of the research that's been done, take a look here and here.

Given the localized success we were seeing in these studies, we wanted to bring this next wave of technology to healthcare groups across the country. Working alongside Dr. Don Erwin and Alexandria Fischer, two innovative leaders at St. Thomas CHC in New Orleans with key insights into the impact predictive analytics could bring to patient access, we developed a platform that allows groups to track and predict patient no shows in real-time.

Today, Streamline allows healthcare organizations across the country to track and predict patient no shows to increase patient access, decrease no show rates, and drive additional revenue.