The rise of value-based care is placing additional economic pressure on surgeons to deliver the highest standard of treatment for less. Medicrea is focusing its efforts on integrating predictive analytics into a system that actively drives preoperative planning, intraoperative confirmation and postoperative analysis.
This content is sponsored by Medicrea.
Becker’s Spine Review had the opportunity to interview Medicrea’s Chief Scientific Officer Thomas Mosnier to better understand how his team of biomedical engineers and data scientists work to apply personalized medicine in spine care, and how Medicrea’s Adaptive Spine Intelligence (UNiD ASI) has the potential to improve the standard of care.
Question: What was the genesis of the company’s efforts in developing and integrating predictive modeling and analytics into spine care?
Thomas Mosnier: We began re-inventing Medicrea’s approach. First came the development of the world’s first personalized spinal rods in 2013, and a year later the world’s first spinal fusion surgery using 3-D printed personalized spine cages. From here, we moved into a collaborative model with surgeons, providing preoperative planning, intraoperative support and postoperative analytical services.
Q: How does predictive analytics work?
TM: Through this new data-heavy service workflow, we developed our own proprietary software platform to capture the iterative feedback loop of clinical data to improve future surgical plans and build our predictive models. Knowledge of scientific publications can help to define surgical strategy, such as the curvature of the spinal rods, but huge amounts of data must be considered to reach surgical objectives. Predictive analytics can amalgamate and channel this data set with great efficiency through specially constructed machine learning algorithms to craft an optimized strategy for each surgery.
Q: How come information technology solutions have not been done before within the spinal industry?
TM: Traditionally, a device manufacturer’s workflow centers on delivering solutions exclusively for the operating room. However, because Medicrea was the first to develop patient-specific implant solutions, we saw a need for innovation beyond this one area of the surgical continuum. We also recognized our unique position to do so, which is what led us to pioneer the integration of intelligent information technology with our next-generation manufacturing capabilities, including in-house 3-D printing. We now have over four years of collecting and analyzing pre- and post-operative data to develop a model that benefits surgeons, patients and healthcare systems.
Q: What do you see are the benefits of introducing a more holistic service?
TM: Our primary ambition has been to improve clinical outcomes and efficiencies in spine surgery by generating optimized surgical plans and personalizing implants. As an example, a recent study examining rod fracture rates found when patients were treated with patient specific UNiD Rods fracture rates dropped to 2.2 percent, compared to the industry average of 14.9 percent.1,2 Surgeons also have access to global data and advanced analytics to determine more specifically what works and what needs to be changed.
Q: Were there any challenges with building a predictive model for spinal surgery?
TM: Building a predictive model is all about the data. It is not as simple as just gathering information and putting it into a database; engineers need to be accurate about the measurements and descriptions of the patient X-rays, imaging, clinical notes, etc. With new data science experts and a talented engineering team in place, building the predictive models for spinal surgery was an exciting task with multifaceted questions to consider. We put in place the algorithms capable of answering these questions.
Q: What do surgeons have to look forward to as you continue to innovate personalized spine?
TM: As surgeons continue to come back to us expressing positive feedback and future desires of this technology, we have plenty of ideas where we are going next with the technology. Like reaching adequate sagittal alignment, prevention of proximal junctional kyphosis failure is also an important topic for spine surgeons. Based on UNiD user feedback, we believe this is another critical area of spinal surgery where we can improve outcomes and efficiencies with our machine learning technology.
Q: How can one learn more about what predictive analytics can bring to their practice?
TM: Our team of trained biomedical engineers known as the UNiD LAB is available for contact 24/7 through the UNiD HUB platform’s software and able to provide personalized demonstrations with case samples and discussions around surgical strategy.
Anyone wanting to learn more can directly reach out to a local Medicrea representative, through our website (www.medicrea.com) or email (info@medicrea.com) to gain more insight on the company’s disruptive approach to spinal surgery focused on personalized spinal implants and services.
1 Hamilton DK, Buza JA, Passias PG, et al. The Fate of Adult Spinal Deformity (ASD) Patients Incurring Rod Fracture After Thoracolumbar Fusion. World Neurosurgery. 2017
2 V. Fiere, S. Fuentes, E. Burger, T. Raabe, P. Passias, et al. Patient-Specific Rods show a reduction in rod breakage incidence. Medicrea Whitepaper. October 2017.