Real time surgical analytics—e.g., anatomical graphic depiction of exactly what occurs during surgery, automatic translation of data into an intelligent, electronic operative report linking every detail including implant location, surgical techniques, product usage, and all clinical parameters—is now part of daily life for surgeons at Irvine, California-based Hoag Orthopedic Institute (HOI).
Real Time Surgical Analytics Lands at Hoag
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The supplier, ORHub, provides an entire suite of analytical tools for spinal, hip, knee, cardiovascular and neurological surgeries.
Why would a hospital buy into ORHub? The promise is that it will improve Hoag’s profitability.
According to ORHub’s CEO Colt Melby, “We have captured compliant data from over 4,000 surgical procedures to date. Our results indicate that the granularity of our data provides insights into areas including surgical procedural measures, surgical device usage and other key performance analytics that were previously unobtainable or convoluted. We are committed to changing the face of surgical healthcare and look forward to our partnership with HOI to drive hospital and surgical efficiencies across various indications.”
As for Hoag, the hospital’s executive medical director, board member and chair of the finance committee Alan Beyer, M.D. said, “The move from manual to automated surgical and hospital processes relies on the veracity of the data. Consistently, ORHub has provided trusted data with a robust platform that enables our team to evaluate our hospital and physician performance on a case to case basis across various indications. As a center of excellence, having real-time smart analytics is a powerful tool to drive clinical decision making, improve inventory management and create better efficiencies to provide the highest quality of patient care.”
ORHub’s suite of products provides a cloud-based software solution that captures information before, during and after surgery, filling a void in the current surgical information infrastructure and providing the first process to capture and measure the surgical process—evolving Big Data into Intelligent Digital Data.
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This is a fascinating development. In my practice we've seen similar outcomes with the revised protocol. The key differentiator seems to be patient selection criteria. Has anyone else noticed the correlation with BMI thresholds?
Great point. I'd push back slightly on the conclusion, the sample size in the cited study is too small to draw population-level inferences. That said, the directional signal is compelling and worth a larger RCT.
We implemented a similar approach last year. Early results are promising but we're still gathering 12-month follow-up data. Happy to share our protocol if anyone is interested.
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