Ilsa Webeck, Managing Director & Founder, MedTech Strategies05.21.24
By now, everyone with access to the news has seen some impact of artificial intelligence (AI) and machine learning (ML) on the world. Everything from legal briefs to pop hits is being created using AI tools, which leaves many wondering about the near-term impact on healthcare (Table 1). Work is being done to address the use of these technologies, such as President Biden’s “Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence”1 and FDA’s white paper titled, “Artificial Intelligence & Medical Products: How CBER, CDER, CDRH, and OCP are Working Together.”2 Documents like these are helping developers take some simple first steps on a long road.
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Table 1: Four areas of focus regarding the development and use of AI across the medical product lifecycle per the FDA.2
FDA has seen a huge increase in the rate of AI/ML submissions, with a more than 39% rise in submissions from 2019 to 2020.3 While data indicates the submission rate is slowing, FDA has predicted the new submissions will still reach a growth rate over 30%.3
Some of these tools have already started to be a part of the administrative side of healthcare4 but it is still unknown how quickly AI and ML tools will be a regular part of the day-to-day clinical environment, supporting diagnosis and treatment. Work completed by MedTech Strategies indicates clinicians are excited about the real-world use of AI in their clinics, suites, and operating rooms but are still cautious about workflow and reimbursement coverage. Concerns regarding AI causing more work—time needed to double-check the outputs or add “clicks” to their software applications, for example—will be with us as these new technologies are adopted.
Of the recent set of new AI/ML devices cleared (i.e., Jan. 1 through July 31, 2023), there was a large representation in radiology with 79% of submissions in this area,3 which makes sense given the clear connection of imaging data to software applications (Table 2), but what does this mean for orthopedics? As of Oct. 19, 2023, FDA published an update to the AI/ML-Enabled Medical Devices list.3 This list included 692 devices submitted, however, only one of the devices listed was reviewed by an orthopedic panel—NuVasive Inc.’s Pulse System. Many companies are looking at AI applications for a wide range of uses in orthopedic applications.
![](https://images.rodpub.com/images/306/837_main.jpg)
Table 2: Number of AI submissions to the FDA3
AI-assisted review of implanted devices before a revision procedure is seeing promise. Data published in the journal Arthroplasty indicated that a deep learning model was able to predict the type of unique knee arthroplasty implants with 99% accuracy, which could result in significant time savings for pre-op planning and efficiency during the procedure.5
Additionally, the predictive capability of AI is on its way. Utilizing predictive models to help surgeons identify clues, signals, patient histories, clinical conditions, co-morbidities, etc. to understand the risk factors and, therefore, likelihood of procedural success will have a dramatic impact on the orthopedic industry. Using ML, researchers at several leading U.S. academic institutions demonstrated the potential to “calculate patient-specific risks for complications to adjust perioperative care and site of surgery” for total shoulder arthroplasty.6 Knowing this information will allow surgeons to be more informed when planning and executing surgeries, hoping for a better clinical outcome and improved patient experience.
That being said, an article published in 2022 reviewed several AI and deep learning algorithms in orthopedic radiography (Table 3). The authors found “although AI in medicine is a rapidly growing field that shows promising results, clinical implementation is still lacking,”7 which indicates there is still a way to go for radiology evaluations in orthopedics.
![](https://images.rodpub.com/images/306/838_main.jpg)
Table 3: Percentage of recent (i.e., Jan. 1 through July 31, 2023) submissions to FDA by specialty type3
References
Ilsa Webeck has over 25 years of work experience assessing commercial and market viability in the medtech space. After founding MedTech Strategies in 2014, she has worked with a wide range of organizations focused on assessing commercial fit and identifying product and service value propositions, as well as uncovering customer/user needs to understand a path to commercial success. Her past experiences include group product director at J&J’s DePuy Spine, leading the strategic marketing and upstream marketing team, and associate director for global commercial strategy in the MS Franchise at Biogen Idec. For more information, visit www.medtechstrategiesllc.com
![](https://images.rodpub.com/images/306/836_main.jpg)
Table 1: Four areas of focus regarding the development and use of AI across the medical product lifecycle per the FDA.2
Some of these tools have already started to be a part of the administrative side of healthcare4 but it is still unknown how quickly AI and ML tools will be a regular part of the day-to-day clinical environment, supporting diagnosis and treatment. Work completed by MedTech Strategies indicates clinicians are excited about the real-world use of AI in their clinics, suites, and operating rooms but are still cautious about workflow and reimbursement coverage. Concerns regarding AI causing more work—time needed to double-check the outputs or add “clicks” to their software applications, for example—will be with us as these new technologies are adopted.
Of the recent set of new AI/ML devices cleared (i.e., Jan. 1 through July 31, 2023), there was a large representation in radiology with 79% of submissions in this area,3 which makes sense given the clear connection of imaging data to software applications (Table 2), but what does this mean for orthopedics? As of Oct. 19, 2023, FDA published an update to the AI/ML-Enabled Medical Devices list.3 This list included 692 devices submitted, however, only one of the devices listed was reviewed by an orthopedic panel—NuVasive Inc.’s Pulse System. Many companies are looking at AI applications for a wide range of uses in orthopedic applications.
![](https://images.rodpub.com/images/306/837_main.jpg)
Table 2: Number of AI submissions to the FDA3
Additionally, the predictive capability of AI is on its way. Utilizing predictive models to help surgeons identify clues, signals, patient histories, clinical conditions, co-morbidities, etc. to understand the risk factors and, therefore, likelihood of procedural success will have a dramatic impact on the orthopedic industry. Using ML, researchers at several leading U.S. academic institutions demonstrated the potential to “calculate patient-specific risks for complications to adjust perioperative care and site of surgery” for total shoulder arthroplasty.6 Knowing this information will allow surgeons to be more informed when planning and executing surgeries, hoping for a better clinical outcome and improved patient experience.
That being said, an article published in 2022 reviewed several AI and deep learning algorithms in orthopedic radiography (Table 3). The authors found “although AI in medicine is a rapidly growing field that shows promising results, clinical implementation is still lacking,”7 which indicates there is still a way to go for radiology evaluations in orthopedics.
![](https://images.rodpub.com/images/306/838_main.jpg)
Table 3: Percentage of recent (i.e., Jan. 1 through July 31, 2023) submissions to FDA by specialty type3
MedTech Strategies’ Perspective
AI is still in its infancy when it comes to clinical applications in orthopedics. As the space grows, it will be critical to demonstrate focused application of AI tools and provide a clear value proposition with both a clinical and economic benefit.References
- tinyurl.com/mr9pnz2n
- tinyurl.com/mr46pzw2
- tinyurl.com/mt7b4snn
- tinyurl.com/bddx3hy5
- tinyurl.com/fu2aawky
- tinyurl.com/22adavue
- tinyurl.com/2fsr4zv5
Ilsa Webeck has over 25 years of work experience assessing commercial and market viability in the medtech space. After founding MedTech Strategies in 2014, she has worked with a wide range of organizations focused on assessing commercial fit and identifying product and service value propositions, as well as uncovering customer/user needs to understand a path to commercial success. Her past experiences include group product director at J&J’s DePuy Spine, leading the strategic marketing and upstream marketing team, and associate director for global commercial strategy in the MS Franchise at Biogen Idec. For more information, visit www.medtechstrategiesllc.com