The Future of Orthopaedic Surgery (British Orthopaedic Assoc)
As the 21st century comes of age and the global burden of disease shifts increasingly towards musculoskeletal conditions, orthopaedic surgeons will be called upon to rise to the challenge.
Orthopaedic surgery is on a path towards less invasive and more precise operations, with a greater proportion of outpatient and overnight procedures1 . This trajectory is likely to continue and will be further facilitated by new technologies, making surgery more selective and the orthopaedic surgeon an increasingly proactive specialist in the management of injuries and conditions.
As the saying goes: “Predictions are difficult, especially about the future.” It would be remiss to presume too much about how orthopaedic surgery will look tomorrow, but there are a few key trends that are becoming apparent. This is occurring against a backdrop of increasing demand for orthopaedic services worldwide and the rising threat of antibiotic resistance2,3,4. Clinical expertise and experience will be needed to inform appropriate responses.
Technology is reshaping the world and, with it, orthopaedic surgery. Whilst many recent advances have occurred inside the operating theatre, much of what is set to change will take place outside of the hospital, beyond the clinic room, in the time before and after surgery.
Measuring quality: Tomorrow’s questions
As new tools and techniques enter orthopaedic practice, accurate and comparable approaches to assess quality of care and outcomes will be paramount. The future success of orthopaedic surgery will be assessed using digitally enhanced Patient-Reported Outcome Measures (PROMs). By applying Item Response Theory and Computer Adaptive Testing (CAT), which shapes remaining survey questions based on those already answered, patients can be asked more relevant questions whilst giving fewer responses.
CAT can make patients’ survey responses more efficient, of higher quality and more easily comparable. Cambridge University’s open-source adaptive testing platform Concerto (concertoplatform.com) and the Patient-Reported Outcomes Measurement Information System (PROMIS) (www.healthmeasures. net) are leading exponents of this approach, with the latter comprising the world’s largest item bank of CAT measures currently being translated, implemented and validated across the word. PROMIS surveys measure generic, commonly relevant outcomes such as pain and physical function that can be used and correlated across and within different patient populations. Increasingly, orthopaedic patients have more than one condition and combining generic scores with disease or procedure-specific measures provides opportunities for more comprehensive assessments with relevance across different groups5 . PROMIS CAT surveys can also avoid the ceiling effects seen with other musculoskeletal function scores6 .
Beyond surveys: Smartphones and sensors
As existing models of measuring pre-intervention function, treatment progress and outcomes are being refined, smartphones, wearables and sensors are adding new layers of objective, real-world data, informing a deeper and more nuanced understanding of musculoskeletal treatments and results. Specialised sensors able to provide continuous, real-time information will increasingly enhance decision-making before, during and after surgery.
Smartphones are rapidly becoming ubiquitous across the world and, with their in-built recording of steps and activity, offer a convenient and scalable means of measuring the physical activity of both individuals and large populations7 . Automatically collected patient-specific data will reveal new insights into recovery patterns and enhance pre- and post-intervention planning. Research using smartphone data in orthopaedics is in its infancy, yet its use has been demonstrated in predicting outcomes including Parkinson’s-related gait progression and recovery from shoulder injuries8,9. Improved tools to estimate recovery progress against activity-related baselines and procedure-specific points of reference may also aid conversations with patients about treatment goals and expectations.
Remote support and day-case surgery
Improved capabilities for accurate remote monitoring and self-care will further enable day-case surgery. Retrospective activity data with clear baselines and tools to estimate outcomes will help to identify patients appropriate for outpatient procedures. Patients will be able to take more active roles in their treatment and improved capabilities for remote support can help to ensure that the potential savings of shorter hospital stays are not offset by increased follow-up appointments or readmissions10.
Machine Learning and Artificial Intelligence: Making sense of more information
Arguably, the uptake of robotic surgery may not have been as rapid as expected, yet its transformative potential is clear. Robotic surgery and Artificial Intelligence, as with any powerful force, must be handled with respect. As costs fall and evidence builds, robotic assisted approaches will become increasingly common across the orthopaedic subspecialties. Rather than replacing clinical skills, however, these new technologies will assist and enhance decision-making intraoperatively, as they will do too in the planning and recovery stages. In time, computer-assistance is likely to also enable new techniques and procedures11.
Currently recognised as the best-in-class approach within AI, Machine Learning techniques combine computer science and mathematics to improve predictive accuracy and translate large datasets into useful insights12. Long before autonomously operating robots become credible competitors, AI systems will revolutionise orthopaedics by working in partnership with surgeons, applying their superior capacity of drawing conclusions from large datasets, to enable surgeons to do more, better. Recent successful examples include algorithms helping to organise operation lists, prioritise workflow and predict in-hospital mortality, unplanned readmissions and prolonged length of stay13,14. Indeed, an appealing vision of the future is one where emerging technologies increasingly shoulder administrative duties, meaning healthcare becomes safer and more efficient, whilst surgeons are freed up to spend more time on clinical work.
New tools of the trade
Biologic treatments comprise a wide field of techniques, including stem cell therapies and platelet-rich plasma injections, which aim to encourage regeneration and repair. Whilst the current evidence for these techniques is variable, biologic approaches hold great potential and will likely play a role in the future evolution of the orthopaedic surgeon as injected therapies 3D imaging, navigation and printing will enable surgeons to be increasingly precise and personalised. Implants themselves will become increasingly ‘smart’ with person specific design, dynamic materials and incorporated sensors providing further data and direct feedback on progress and performance. Smart implants will be able to highlight the need for further review and may even be self-protective by automatically responding to changes in the local environment17.
Virtual and augmented reality will enhance pre-operative planning, training and procedural precision, further supporting safer surgery18. Telemedicine tools are enabling surgeons to share expertise in real-time during cases, adding a new dimension of collaboration to surgical practice, which may evolve further as surgeons become increasingly able to virtually ‘scrub in’ and join cases remotely19.
As orthopaedic practice is changing, so too is the fabric of the profession, increasingly matching the diversity of its patients. The current and widely acclaimed online campaign #ILookLikeASurgeon is challenging the white, male surgeon stereotype and helping to redefine ideas about who surgeons are20.
The ability to share ideas and experience is a core promise of a more interconnected and informed world. As highlighted by The Lancet Commission on Global Surgery, five billion people are currently unable to benefit from surgical care and, whilst many new technologies are vying for a place in the orthopaedic toolkit, perhaps the most significant achievements of tomorrow will lie in replicating current successes and increasing access to high quality surgery.21 To echo the author William Gibson: “The future is already here –just not evenly distributed”22. Communities of orthopaedic surgeons are forming to discuss and define the changing landscape. To find out more and join these conversations, see the links below to Stefano Bini’s Digital Orthopaedic Conference in San Francisco; the upcoming Digital Orthopaedics meeting at The Royal Society of Medicine and, for more general discourse on the impact of AI in medicine, AIMed Europe.
Find out more:
AIMed Europe Shoreditch Town Hall, 11-13th Sep 2018 aimed.events/aimed-europe Digital Orthopaedics: Measuring quality in orthopaedic healthcare The Royal Society of Medicine, Monday 17th Sep 2018 tinyurl.com/rsmortho Digital Orthopaedics Conference San Francisco InterContinental San Francisco, Jan 5-6th 2019 www.docsf.health Axel Sylvan trained in surgery before co-founding the London-based orthopaedic start-up myrecovery.ai with fellow surgical trainee and patient Tom Harte. Aiming to improve patient experience and clinical insight, www. myrecovery.ai enables surgeons to create tailor-made treatment companion Apps and, with a growing team of software engineers and PhDs, is developing the next generation of AI-enabled digital tools for musculoskeletal care.
1. Crawford DC, Chuan SL, Sprague S, Bhandari M. Clinical and Cost Implications of Inpatient Versus Outpatient Orthopedic Surgeries: A Systematic Review of the Published Literature. Orthop Rev (Pavia) 2015 Dec 28; 7(4): 6177. Published online 2015 Dec 30. doi: 10.4081/or.2015.6177.
2. Briggs AM et al. Reducing the global burden of musculoskeletal conditions. Bulletin of the World Health Organization 2018; 96:366-368.
3. Briggs AM, Chan M, Slater H. Models of Care for musculoskeletal health: Moving towards meaningful implementation and evaluation across conditions and care settings. Best Pract Res Clin Rheumatol. 2016 06; 30(3):359–74.
4. Arias CA, Murray BE Antibiotic-Resistant Bugs in the 21st Century — A Clinical Super-Challenge. N Engl J Med 2009; 360:439-443.
5. Barnett K et al. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study Lancet 2012; 380:37-43.
6. Hung M, Ami S, Higgins T, Saltzman C, Kubiak E. Computerized Adaptive Testing Using the PROMIS Physical Function Item Bank Reduces Test Burden With Less Ceiling Effects Compared With the Short Musculoskeletal Function Assessment in Orthopaedic Trauma Patients. Journal of Orthopaedic Trauma: August 2014 – Volume 28 – Issue 8 – p 439–443.
7. Anthes, E. Mental health: there’s an app for that. Nature 532, 20–23 (2016).
8. Healthcare Information and Management Systems Society http://www.himss.org/library/artificial-intelligence-prosdevelop-tools-identify-patterns-and-predict-outcomes (Accessed: 06/07/2018).
9. Zhan A., Mohan S., Tarolli C. et.al. Using smartphones and machine learning to quantify Parkinson’s disease severity. JAMA Neurol. (not yet in press).
10. Edwards PK, Levine M, Cullinan K, Newbern G, Barnes L. Avoiding Readmissions—Support Systems Required After Discharge to Continue Rapid Recovery? The Journal of Arthroplasty (2014), doi.org/10.1016/j.arth.2014.12.029.
11. Zheng G and Nolte LP. Computer-Assisted Orthopedic Surgery: Current State and Future Perspective. Front. Surg. 2005 2:66. doi: 10.3389/fsurg.2015.00066.
12. Dhar V. Data science and prediction. Communications of the ACM. 2013; 56: 64–73.
13. Rajkomar A., Oren E., et.al. Scalable and accurate deep learning with electronic health records. Digital Medicine 1(18).
14. Bini SA. Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: what do these terms mean and how will they impact health care? The Journal of Arthroplasty (2018), doi: 10.1016/j.arth.2018.02.067.
15. LaPrade RF, Dragoo JL, Koh J, IR Murray, Geeslin AG, Chu CR. AAOS Research Symposium Updates and Consensus: Biologic Treatment of Orthopaedic Injuries. J Am Acad Orthop Surg 2016; 0:1-17.
16. Isabel Andia, Mikel Sánchez & Nicola Maffulli (2011) Platelet rich plasma therapies for sports muscle injuries: any evidence behind clinical practice? Expert Opinion on Biological Therapy, 11:4, 509-518.
17. Javad Parvizi, Valentin Antoci, Noreen J Hickok & Irving M Shapiro (2007) Selfprotective smart orthopedic implants, Expert Review of Medical Devices, 4:1, 55-64, DOI: 10.1586/17434418.104.22.168.
18. Pessaux, P., Diana, M., Soler, L. et al. Langenbecks Arch Surg (2015) 400: 381. https://doi.org/10.1007/s00423-014- 1256-9.
19. Bhattacharya S, Rawat D. Comparative study of remote surgery techniques. Global Humanitarian Technology Conference (GHTC) 2015 doi:10.1109/GHTC.2015.7344004.
20. Logghe H, Jones C, McCoubrey A, Fitzgerald A. #ILookLikeASurgeon: embracing diversity to improve patient outcomes. BMJ 2017; 359:j4653.
21. Ng-Kamstra JS, Greenberg SLM, Abdullah F, et al. Global Surgery 2030: a roadmap for high income country actors. BMJ Global Health 2016;1:e000011. doi:10.1136/bmj