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J Knee Surg 2023; 36(12): 1209-1217
DOI: 10.1055/s-0042-1756503
Original Article

Identifying Trends and Quantifying Growth for Technological Innovation in Knee Arthroplasty: An Analysis of a Patent Database (1990 to 2020)

Pedro J. Rullán
1   Department of Orthopaedic Surgery, Cleveland Clinic Foundation, Cleveland, Ohio
,
Daniel Grits
1   Department of Orthopaedic Surgery, Cleveland Clinic Foundation, Cleveland, Ohio
,
Ajay Potluri
2   School of Medicine, Case Western Reserve University, Cleveland, Ohio
,
Ahmed K. Emara
1   Department of Orthopaedic Surgery, Cleveland Clinic Foundation, Cleveland, Ohio
,
Alison K. Klika
1   Department of Orthopaedic Surgery, Cleveland Clinic Foundation, Cleveland, Ohio
,
Michael A. Mont
3   Center for Joint Preservation and Replacement, Rubin Institute for Advanced Orthopedics, Sinai Hospital of Baltimore, Baltimore, Maryland
,
Nicolas S. Piuzzi 
1   Department of Orthopaedic Surgery, Cleveland Clinic Foundation, Cleveland, Ohio
› Author Affiliations Funding None.
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Abstract

Technological innovation is the key for surgical progress in knee arthroplasty and improvement in patient outcomes. Exploring patented technologies can help elucidate trends and growth for numerous innovative technologies. However, patent databases, which contain millions of patents, remain underused in arthroplasty research. Therefore, the present study aimed to: (1) quantify patent activity; (2) group patents related to similar technologies into well-defined clusters; and (3) compare growth between technologies in the field of knee arthroplasty over a 30-year period. An open-source international patent database was queried from January 1990 to January 2020 for all patents related to knee arthroplasty A search strategy identified 70,154 patents, of which 24,425 were unique and included analysis. Patents were grouped into 14 independent technology clusters using Cooperative Patent Classification (CPC) codes. Patent activity was normalized via a validated formula adjusting for exponential growth. Compound annual growth rates (CAGR) were calculated (5-year, 10-year, and 30-year CAGR) and compared for each cluster. Overall yearly patent activity increased by 2,023%, from 104 patents in 1990 to 2,208 patents in 2020. The largest technology clusters were “drugs” (n = 5,347; 23.8%), “components” (n = 4,343; 19.0%), “instruments” (n = 3,130; 13.7%), and “materials” (n = 2,378; 10.4%). The fastest growing technologies with their 5-year CAGR were: “user interfaces for surgical systems” (58.1%); “robotics” (28.6%); “modularity” (21.1%); “navigation” (15.7%); and “computer modeling” (12.5%). Since 1990, overall patent growth rate has been greatest for “computer modeling” (8.4%), “robotics” (8.0%), “navigation” (7.9%), and “patient-specific instrumentation” (6.4%). Most patents in knee arthroplasty for the last 30 years have focused on drugs, components, instruments, and materials. Recent exponential growth was mainly observed for user interfaces for surgical systems, robotics, modularity, navigation, and computer-assisted technologies. Innovation theory would suggest that these rapidly growing technologies are experiencing high innovation output, increased resource investments, growing adoption by providers, and significant clinical impact. Periodic monitoring of technological innovation via patent databases can be useful to establish trends and future directions in the field of knee arthroplasty.

Keywords

technological innovation - patents - knee arthroplasty - knee - orthopaedics - research - technology


Publication History

Received: 04 June 2022

Accepted: 26 July 2022

Article published online:
22 September 2022

© 2022. Thieme. All rights reserved.

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333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

 

  • References

  • 1 Baig MN, Kearns SR, Shannon FJ, Devitt A. Ten inventions that shaped modern orthopedics. Cureus 2021; 13 (01) e12819
    PubMedGoogle Scholar
  • 2 Sloan M, Premkumar A, Sheth NP. Projected volume of primary total joint arthroplasty in the U.S., 2014 to 2030. J Bone Joint Surg Am 2018; 100 (17) 1455-1460
    CrossrefPubMedGoogle Scholar
  • 3 Batailler C, Parratte S. Assistive technologies in knee arthroplasty: fashion or evolution? Rate of publications and national registries prove the Scott Parabola wrong. Arch Orthop Trauma Surg 2021; 141 (12) 2027-2034
    CrossrefPubMedGoogle Scholar
  • 4 Noble PC, Conditt MA, Cook KF, Mathis KB. The John Insall Award: patient expectations affect satisfaction with total knee arthroplasty. Clin Orthop Relat Res 2006; 452 (452) 35-43
    CrossrefPubMedGoogle Scholar
  • 5 Choi Y-J, Ra HJ. Patient satisfaction after total knee arthroplasty. Knee Surg Relat Res 2016; 28 (01) 1-15
    CrossrefPubMedGoogle Scholar
  • 6 Kahlenberg CA, Nwachukwu BU, McLawhorn AS, Cross MB, Cornell CN, Padgett DE. patient satisfaction after total knee replacement: a systematic review. HSS J 2018; 14 (02) 192-201
    CrossrefPubMedGoogle Scholar
  • 7 Gunaratne R, Pratt DN, Banda J, Fick DP, Khan RJK, Robertson BW. Patient dissatisfaction following total knee arthroplasty: a systematic review of the literature. J Arthroplasty 2017; 32 (12) 3854-3860
    CrossrefPubMedGoogle Scholar
  • 8 Keeney JA. Innovations in total knee arthroplasty: improved technical precision, but unclear clinical benefits. Orthopedics 2016; 39 (04) 217-220
    CrossrefPubMedGoogle Scholar
  • 9 Siddiqi A, Horan T, Molloy RMRM, Bloomfield MRMR, Patel PDPD, Piuzzi NSNS. A clinical review of robotic navigation in total knee arthroplasty: historical systems to modern design. EFORT Open Rev 2021; 6 (04) 252-269
    CrossrefPubMedGoogle Scholar
  • 10 Haglin JM, Eltorai AEM, Gil JA, Marcaccio SE, Botero-Hincapie J, Daniels AH. Patient-specific orthopaedic implants. Orthop Surg 2016; 8 (04) 417-424
    CrossrefPubMedGoogle Scholar
  • 11 Brinkmann EJ, Fitz W. Custom total knee: understanding the indication and process. Arch Orthop Trauma Surg 2021; 141 (12) 2205-2216
    CrossrefPubMedGoogle Scholar
  • 12 Picard F, Deep K, Jenny JY. Current state of the art in total knee arthroplasty computer navigation. Knee Surg Sports Traumatol Arthrosc 2016; 24 (11) 3565-3574
    CrossrefPubMedGoogle Scholar
  • 13 Siddiqi A, Smith T, McPhilemy JJ, Ranawat AS, Sculco PK, Chen AF. Soft-tissue balancing technology for total knee arthroplasty. JBJS Rev 2020; 8 (01) e0050-e0050
    CrossrefPubMedGoogle Scholar
  • 14 Picard F, Deakin AH, Riches PE, Deep K, Baines J. Computer assisted orthopaedic surgery: past, present and future. Med Eng Phys 2019; 72: 55-65
    CrossrefPubMedGoogle Scholar
  • 15 Riskin DJ, Longaker MT, Gertner M, Krummel TM. Innovation in surgery: a historical perspective. Ann Surg 2006; 244 (05) 686-693
    CrossrefPubMedGoogle Scholar
  • 16 Hughes-Hallett A, Mayer EK, Marcus HJ. et al. Quantifying innovation in surgery. Ann Surg 2014; 260 (02) 205-211
    CrossrefPubMedGoogle Scholar
  • 17 Glossary USPTO. . Published 2022. Accessed January 17, 2022 at: https://www.uspto.gov/learning-and-resources/glossary
    PubMed
  • 18 Hughes-Hallett A, Mayer EK, Pratt PJ, Vale JA, Darzi AW. Quantitative analysis of technological innovation in minimally invasive surgery. Br J Surg 2015; 102 (02) e151-e157
    CrossrefPubMedGoogle Scholar
  • 19 Bhatt NR, Davis NF, Dalton DM. et al. Quantitative analysis of technological innovation in urology. Urology 2018; 111: 230-237
    CrossrefPubMedGoogle Scholar
  • 20 Marcus HJ, Hughes-Hallett A, Kwasnicki RM, Darzi A, Yang G-Z, Nandi D. Technological innovation in neurosurgery: a quantitative study. J Neurosurg 2015; 123 (01) 174-181
    CrossrefPubMedGoogle Scholar
  • 21 Dalton DM, Burke TP, Kelly EG, Curtin PD. Quantitative analysis of technological innovation in knee arthroplasty: using patent and publication metrics to identify developments and trends. J Arthroplasty 2016; 31 (06) 1366-1372
    CrossrefPubMedGoogle Scholar
  • 22 Bonutti PM, Seyler TM, Bianco PD, Ulrich SD, Mont MA. Inventing in orthopaedics: from idea to marketed device. J Bone Joint Surg Am 2008; 90 (06) 1385-1392
    CrossrefPubMedGoogle Scholar
  • 23 Emara AK, Zhou G, Klika AK. et al. Robotic-arm-assisted knee arthroplasty associated with favorable in-hospital metrics and exponentially rising adoption compared with manual knee arthroplasty. J Am Acad Orthop Surg 2021; 29 (24) e1328-e1342
    CrossrefPubMedGoogle Scholar
  • 24 Tompkins GS, Sypher KS, Li H-F, Griffin TM, Duwelius PJ. Robotic versus manual total knee arthroplasty in high volume surgeons: a comparison of cost and quality metrics. J Arthroplasty 2022; 37 (8S): S782-S789
    CrossrefPubMedGoogle Scholar
  • 25 Rajan PV, Khlopas A, Klika A, Molloy R, Krebs V, Piuzzi NS. The cost-effectiveness of robotic-assisted versus manual total knee arthroplasty: a Markov model-based evaluation. J Am Acad Orthop Surg 2022; 30 (04) 168-176
    CrossrefPubMedGoogle Scholar
  • 26 The Lens - Free & Open Patent and Scholarly Search. 2022 . Published 2022. Accessed March 17 2022, at: https://www.lens.org/
    PubMed
  • 27 Patent Classification USPTO. . Published 2022. Accessed March 17, 2022 at: https://www.uspto.gov/patents/search/classification-standards-and-development
    PubMed
  • 28 Cooperative Patent Classification USPTO. . Published 2022. Accessed March 17, 2022 at: https://www.uspto.gov/web/offices/pac/mpep/s905.html
    PubMed
  • 29 Patent Classification Timeline. . Published 2022. Accessed March 17, 2022 at: https://www.uspto.gov/sites/default/files/documents/Timeline.pdf
    PubMed
  • 30 Patent Inspiration Database. . Accessed January 26, 2022, at: https://www.patentinspiration.com/
    PubMed
  • 31 Siddiqi A, Mont MA, Krebs VE, Piuzzi NS. Not all robotic-assisted total knee arthroplasty are the same. J Am Acad Orthop Surg 2021; 29 (02) 45-59
    CrossrefPubMedGoogle Scholar
  • 32 Doan GW, Courtis RP, Wyss JG, Green EW, Clary CW. Image-free robotic-assisted total knee arthroplasty improves implant alignment accuracy: a cadaveric study. J Arthroplasty 2022; 37 (04) 795-801
    CrossrefPubMedGoogle Scholar
  • 33 Batailler C, Fernandez A, Swan J. et al. MAKO CT-based robotic arm-assisted system is a reliable procedure for total knee arthroplasty: a systematic review. Knee Surg Sports Traumatol Arthrosc 2021; 29 (11) 3585-3598
    CrossrefPubMedGoogle Scholar
  • 34 Khlopas A, Sodhi N, Sultan AA, Chughtai M, Molloy RM, Mont MA. Robotic arm-assisted total knee arthroplasty. J Arthroplasty 2018; 33 (07) 2002-2006
    CrossrefPubMedGoogle Scholar
  • 35 Kayani B, Konan S, Ayuob A, Onochie E, Al-Jabri T, Haddad FS. Robotic technology in total knee arthroplasty: a systematic review. EFORT Open Rev 2019; 4 (10) 611-617
    CrossrefPubMedGoogle Scholar
  • 36 Hamilton DA, Ononuju U, Nowak C, Chen C, Darwiche H. Differences in immediate postoperative outcomes between robotic-assisted TKA and conventional TKA. Arthroplast Today 2021; 8: 57-62
    CrossrefPubMedGoogle Scholar
  • 37 Martinez WL. Graphical user interfaces. Wiley Interdiscip Rev Comput Stat 2011; 3 (02) 119-133
    CrossrefPubMedGoogle Scholar
  • 38 Karnuta JM, Luu BC, Roth AL. et al. Artificial intelligence to identify arthroplasty implants from radiographs of the knee. J Arthroplasty 2021; 36 (03) 935-940
    CrossrefPubMedGoogle Scholar
  • 39 Polce EM, Kunze KN, Dooley MS, Piuzzi NS, Boettner F, Sculco PK. Efficacy and applications of artificial intelligence and machine learning analyses in total joint arthroplasty: a call for improved reporting. J Bone Joint Surg Am 2022; 104 (09) 821-832
    CrossrefPubMedGoogle Scholar
  • 40 Hadad MJ, Orr MN, Emara AK, Klika AK, Johnson JK, Piuzzi NS. PLAN and AM-PAC “6-Clicks” scores to predict discharge disposition after primary total hip and knee arthroplasty. J Bone Joint Surg Am 2022; 104 (04) 326-335
    CrossrefPubMedGoogle Scholar
  • 41 Anis HK, Strnad GJ, Klika AK. et al; Cleveland Clinic OME Arthroplasty Group. Developing a personalized outcome prediction tool for knee arthroplasty. Bone Joint J 2020; 102-B (09) 1183-1193
    CrossrefPubMedGoogle Scholar
  • 42 Girbino KL, Klika AK, Barsoum WK. et al; Cleveland Clinic OME Arthroplasty Group. Understanding the main predictors of length of stay after total hip arthroplasty: patient-related or procedure-related risk factors?. J Arthroplasty 2021; 36 (05) 1663-1670.e4
    CrossrefPubMedGoogle Scholar
  • 43 Visperas AT, Greene KA, Krebs VE, Klika AK, Piuzzi NS, Higuera-Rueda CA. A web-based interactive patient-provider software platform does not increase patient satisfaction or decrease hospital resource utilization in total knee and hip arthroplasty patients in a single large hospital system. J Arthroplasty 2021; 36 (07) 2290-2296.e1
    CrossrefPubMedGoogle Scholar
  • 44 King D, Emara AK, Ng MK. et al. Transformation from a traditional model to a virtual model of care in orthopaedic surgery: COVID-19 experience and beyond. Bone Jt Open 2020; 1 (06) 272-280
    CrossrefPubMedGoogle Scholar
  • 45 Goh GS, Lohre R, Parvizi J, Goel DP. Virtual and augmented reality for surgical training and simulation in knee arthroplasty. Arch Orthop Trauma Surg 2021; 141 (12) 2303-2312
    CrossrefPubMedGoogle Scholar
  • 46 Alpaugh K, Ast MP, Haas SB. Immersive technologies for total knee arthroplasty surgical education. Arch Orthop Trauma Surg 2021; 141 (12) 2331-2335
    CrossrefPubMedGoogle Scholar
  • 47 Azar FM. Campbell's Operative Orthopaedics. 14th ed.. Elsevier; 2021
    Google Scholar
  • 48 Sheth NP, Bonadio MB, Demange MK. Bone loss in revision total knee arthroplasty: evaluation and management. J Am Acad Orthop Surg 2017; 25 (05) 348-357
    CrossrefPubMedGoogle Scholar
  • 49 Carender CN, An Q, Tetreault MW, De A, Brown TS, Bedard NA. Use of cementless metaphyseal fixation in revision total knee arthroplasty in the United States. J Arthroplasty 2022; 37 (03) 554-558
    CrossrefPubMedGoogle Scholar
  • 50 Siddiqi A, Chen AF, Piuzzi NS, Kelly MA. The use of metaphyseal cones and sleeves in revision total knee arthroplasty. J Am Acad Orthop Surg 2021; 29 (18) e904-e920
    CrossrefPubMedGoogle Scholar
  • 51 Makhdom AM, Parvizi J. Modular versus nonmodular tibial inserts in total knee arthroplasty: what are the differences?. Ann Transl Med 2017; 5 (10) 225-225
    CrossrefPubMedGoogle Scholar
  • 52 Lamba C, Denning K, Ouellette E, Kurtz S, Bullock M. An interesting case of osteolysis with accompanying metallosis in a primary total knee arthroplasty. Arthroplast Today 2021; 11: 81-87
    CrossrefPubMedGoogle Scholar
  • 53 Kendall J, Pelt CE, Yep P, Mullen K, Kagan R. Trends in polyethylene design and manufacturing characteristics for total knee arthroplasty: an analysis from the American Joint Replacement Registry. J Arthroplasty 2022; 37 (04) 659-667
    CrossrefPubMedGoogle Scholar