Delivering Better Care at a Lower Cost: A Case Study

The power and cost-effectiveness of AI are calling into question many of our assumptions about healthcare.  The most important dichotomy proving to be false is that providing the latest and most thorough diagnostic technology to optimize clinical outcomes is more expensive.  When we use AI to more comprehensively analyze cases we benefit from Moore’s law rapidly and continuously reducing costs.  By contrast, hospital-based care, especially when in an intensive setting such as the NICU is continuously increasing in cost. It is not surprising that when more extensive testing produces clinically actionable results that actually decrease hospital days we can accomplish the holy grail — better care and less expensive simultaneously.  

An exciting example of this is the recent study published by our customer Rady Children’s Institute for Genomic Medicine proving, convincingly, that WGS reduced cost while improving the health of critically ill newborns.  Project Baby Bear was launched with $2 million dollars in state funding and provided WGS to 178 acutely sick newborns enrolled in Medi-Cal at intensive care units at five California hospitals: Children’s Hospital Orange County, Rady Children’s Hospital-San Diego, UC Davis Children’s Hospital in Sacramento, UCSF Benioff Children’s Hospital in Oakland, and Valley Children’s Hospital in Madera. Of the 178, 55 (31%) had their care changed based on the diagnosis. 

The net effect was that children in the program spent 513 fewer days in the hospital than babies who didn’t receive WGS. They also had 11 fewer major surgeries, as well as 16 fewer invasive diagnostic tests.  With an average savings of ~3 hospital days per child, it is easy to see how this can be a net saving since hospital days and major procedures are the primary drivers of healthcare costs.

Improving the diagnostic accuracy and increasing interpretation speed and efficiency is at the heart of this life-improving equation.  Sequencing costs have been decreasing dramatically for years but diagnosis rates were low and the process has been bottlenecked around interpretation.  Interpretation is notoriously difficult due to the rarity of the causative gene within the sheer magnitude of data to review.  Studies using Fabric’s AI software have shown doubled causative candidate identification rates and reduced the interpretation time by an order of magnitude compared with traditional methods.  Fabric Enterprise is the interpretation software of choice for Rady and was used for all 178 cases, helping to achieve the diagnoses that led to the clinical course changes.  Rady and Fabric have been partnering on bringing best in class care to the NICU – Fabric Enterprise was a critical technology in Rady’s achievement of the world record for fastest genomic diagnosis.

And while it is exciting that this life-changing testing is also economical – we never lose sight of the human impact which is incalculable.  Every one of the 513 hospital days saved is a day the families have their precious child where they want – in their home.  Not to mention the trauma averted of needless surgeries and invasive procedures.  This is truly the power of precision medicine and why this technology is so exciting to us. These children deserve the best possible care and thanks to their dedicated clinicians and advances such as Fabric’s AI for interpretation and NGS scalability this care is available and can even cost less.