Digital technology in shoulder arthroplasty: what do surgeons want? What will industry offer? This well-done survey by Warner and colleagues asked 192 shoulder arthroplasty surgeons from three international organizations (ASES, SECEC, and the Codman Shoulder Society) what digital technologies they use and want, and asked six industry leaders about their development priorities.
The survey found that
(1) Ninety-six percent of respondents perform preoperative planning, 82% use digital tools for this, and about a quarter use navigation or mixed reality intraoperatively. Seventy-six percent of respondents perform more than 40 arthroplasties per year; the study did not reflect the usage or views of the low shoulder arthroplasty volume surgeons who perform the majority of these procedures. The technology adoption question looks very different for a surgeon doing 15 arthroplasties a year versus 100. Industry's implicit pitch is often that technology can compensate for lower surgical volume, but that claim is itself unproven and worth calling out directly.
(2) When asked what they wanted from industry, surgeons prioritized artificial intelligence / machine learning, navigation, and improved virtual reality planning. Industry respondents matched these preferences, ranking AI/ML and navigation as their top development priorities. Both groups felt that AI could reduce errors, generate data for best practices, and improve efficiency.
(3) Surgeons emphasized reliability and patient outcome tracking as priorities, which industry did not consider a key focus. In other words, surgeons want to know if their interventions are working for patients, but industry is more interested in the tools themselves than in measuring whether those tools make a difference.
Significantly, the survey did not ask whether surgeons have observed improved patient-reported outcomes (PROs) when using these technologies: “Has your adoption of digital technology resulted in measurably better patient outcomes?” See Navigation, where are we going?
The Discussion section states that preliminary literature shows improved accuracy of glenoid component positioning with navigation, patient-specific instrumentation, and augmented reality versus freehand techniques. The critical question is whether positioning precision within a narrow range translates into better function, less pain, greater durability, or fewer complications for patients. See: How much precision do we need to pay for in shoulder arthroplasty?
The cost question nobody wants to answer
One of the most revealing findings is that industry respondents could not, or would not, articulate a revenue model for these digital technologies. The paper notes that “no consistent business model for AI/ML emerged” and that companies “were not able, or not willing, to clarify revenue models for most digital technologies.”
This is significant. If companies cannot explain how these tools will be paid for, the cost will inevitably be bundled into implant pricing, passed to hospitals, and ultimately borne by patients and the healthcare system. For technologies without demonstrated clinical benefit, this raises serious questions about value.
There are other costs of which the surgeon needs to be aware: increased preoperative and OR time, increased space requirements for a robot, time for training in the use of the technology, learning how to detect when the technology is pointing toward a suboptimal procedure, knowing when and how to abort the use of the technology, and the influence the vendor of the technology may have over the choice of implants.
Warner and colleagues have provided a useful snapshot of surgeon and industry attitudes toward digital technology in shoulder arthroplasty. The data on current usage patterns and preferences are informative. They conclude that “further adoption of these technologies will likely be contingent on well done scientific study which demonstrates value.” Until we have rigorous evidence that these expensive digital tools produce measurably better patient outcomes, we should be cautious about the assumption that more technology equals better care.
The bottom line is that robotics, navigation, and virtual/augmented reality are all methods of transferring a plan made from a preoperative set of images to the patient, without knowing such key characteristics as condition of the soft tissues (that control mobility and stability) and the condition of the bone (that determines quality of fixation). Such factors loom large in the outcome realized by the patient and often require substantial modifications of the preoperative plan.
Helmuth von Moltke the Elder wrote: “Kein Operationsplan reicht mit einiger Sicherheit über das erste Zusammentreffen mit der feindlichen Hauptmacht hinaus.” i.e., “No battle plan survives contact with the enemy.”
This is not an argument against planning. It’s an argument for: Flexibility over rigidity. Preparation over prediction. Adaptation over perfection. Once real-world complexity hits (fog of war, friction, shoulder variability), reality diverges from the preconceived plan.
The goal isn’t to be precise/accurate to the preoperative plan.
The goal is to be ready to modify it.
See How to make good decisions in shoulder (and other) surgery : Bayesian Thinking - adjusting a prior plan in consideration of new information.
Not infrequently, plans need to be modified,
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Here are some videos that are of shoulder interest
Shoulder arthritis - what you need to know (see this link).
How to x-ray the shoulder (see this link).
The ream and run procedure (see this link).
The total shoulder arthroplasty (see this link).
The cuff tear arthropathy arthroplasty (see this link).
The reverse total shoulder arthroplasty (see this link).
The smooth and move procedure for irreparable rotator cuff tears (see this link)
Shoulder rehabilitation exercises (see this link).
