Maria C S Inacio1, Stephen E Graves2, Nicole L Pratt3, Elizabeth E Roughead3, Szilard Nemes4. 1. School of Pharmacy and Medical Sciences, Medicine and Device Surveillance Centre of Research Excellence, Sansom Institute, University of South Australia, GPO Box 2471, Adelaide, 5001, SA, Australia. maria.inacio@unisa.edu.au. 2. Australian Orthopaedic Association National Total Joint Replacement Registry, South Australian Health and Medical Research Institute, Adelaide, Australia. 3. School of Pharmacy and Medical Sciences, Medicine and Device Surveillance Centre of Research Excellence, Sansom Institute, University of South Australia, GPO Box 2471, Adelaide, 5001, SA, Australia. 4. Swedish Hip Arthroplasty Register, Gothenburg, Sweden.
Abstract
BACKGROUND: The incidence of joint arthroplasty is increasing worldwide. International estimates of future demand for joint arthroplasty have used models that propose either an exponential future increase, despite obvious system constraints, or static increases, which do not account for past trends. Country-specific projection estimates that address limitations of past projections are necessary. In Australia, a high-income country with the 7th highest incidence of TKA and 15th highest incidence of THA of the Organization for Economic Cooperation and Development (OECD) countries, the volume of TKAs and THAs increased 198% between 1994 and 2014. QUESTIONS/ PURPOSE: To determine the projected incidence and volume of primary TKAs and THAs from 2014 to 2046 in the Australian population older than 40 years. METHODS: Australian State and Territory Health Department data were used to identify TKAs and THAs performed between 1994 and 1995 and 2013 and 2014. The Australian Bureau of Statistics was the source of the population estimates for the same periods and population-projected estimates until 2046. The incidence rate (IR), 95% CI, and prediction interval (PI) of TKAs and THAs per 100,000 Australian citizens older than 40 years were calculated. Future IRs were estimated using a logistic model, and volume was calculated from projected IR and population. The logistic growth model assumes the existence of an upper limit of the TKA and THA incidences and a growth rate directly related to this incidence. At the beginning, when the observed incidence is much lower than the asymptote, the increase is exponential, but it decreases as it approaches the upper limit. RESULTS: A 66% increase in the IR of primary THAs between 2013 and 2046 is projected for Australia (2013: IR = 307 per 100,000, [95% CI, 262-329 per 100,000] compared with 2046: IR= 510 per 100,000, [95% PI, 98-567 per 100,000]), which translates to a 219% increase in the volume during this period. For TKAs the IR is expected to increase by 26% by 2046 (IR = 575 per 100,000; 95% PI, 402-717 per 100,000) compared with 2013 (IR = 437 per 100,000; 95% CI, 397-479 per 100,000) and the volume to increase by 142%. CONCLUSION: A large increase in the volume of arthroplasties is expected using a conservative projection model that accounts for past surgical trends and future population changes in Australia. These findings have international implications, as they show that using country- specific, conservative projection approaches, a substantial increase in the number of these procedures is expected. This increase in joint arthroplasty volume will require appropriate workforce planning, resource allocation, and budget planning so that demand can be met. LEVEL OF EVIDENCE: Level II, economic and decision analysis.
BACKGROUND: The incidence of joint arthroplasty is increasing worldwide. International estimates of future demand for joint arthroplasty have used models that propose either an exponential future increase, despite obvious system constraints, or static increases, which do not account for past trends. Country-specific projection estimates that address limitations of past projections are necessary. In Australia, a high-income country with the 7th highest incidence of TKA and 15th highest incidence of THA of the Organization for Economic Cooperation and Development (OECD) countries, the volume of TKAs and THAs increased 198% between 1994 and 2014. QUESTIONS/ PURPOSE: To determine the projected incidence and volume of primary TKAs and THAs from 2014 to 2046 in the Australian population older than 40 years. METHODS: Australian State and Territory Health Department data were used to identify TKAs and THAs performed between 1994 and 1995 and 2013 and 2014. The Australian Bureau of Statistics was the source of the population estimates for the same periods and population-projected estimates until 2046. The incidence rate (IR), 95% CI, and prediction interval (PI) of TKAs and THAs per 100,000 Australian citizens older than 40 years were calculated. Future IRs were estimated using a logistic model, and volume was calculated from projected IR and population. The logistic growth model assumes the existence of an upper limit of the TKA and THA incidences and a growth rate directly related to this incidence. At the beginning, when the observed incidence is much lower than the asymptote, the increase is exponential, but it decreases as it approaches the upper limit. RESULTS: A 66% increase in the IR of primary THAs between 2013 and 2046 is projected for Australia (2013: IR = 307 per 100,000, [95% CI, 262-329 per 100,000] compared with 2046: IR= 510 per 100,000, [95% PI, 98-567 per 100,000]), which translates to a 219% increase in the volume during this period. For TKAs the IR is expected to increase by 26% by 2046 (IR = 575 per 100,000; 95% PI, 402-717 per 100,000) compared with 2013 (IR = 437 per 100,000; 95% CI, 397-479 per 100,000) and the volume to increase by 142%. CONCLUSION: A large increase in the volume of arthroplasties is expected using a conservative projection model that accounts for past surgical trends and future population changes in Australia. These findings have international implications, as they show that using country- specific, conservative projection approaches, a substantial increase in the number of these procedures is expected. This increase in joint arthroplasty volume will require appropriate workforce planning, resource allocation, and budget planning so that demand can be met. LEVEL OF EVIDENCE: Level II, economic and decision analysis.
Authors: Monti Khatod; Maria Inacio; Elizabeth W Paxton; Stefano A Bini; Robert S Namba; Raoul J Burchette; Donald C Fithian Journal: Acta Orthop Date: 2008-12 Impact factor: 3.717
Authors: Steven M Kurtz; Kevin L Ong; Edmund Lau; Marcel Widmer; Milka Maravic; Enrique Gómez-Barrena; Maria de Fátima de Pina; Valerio Manno; Marina Torre; William L Walter; Richard de Steiger; Rudolph G T Geesink; Mikko Peltola; Christoph Röder Journal: Int Orthop Date: 2011-03-15 Impact factor: 3.075
Authors: Helen L Walls; Dianna J Magliano; Christopher E Stevenson; Kathryn Backholer; Haider R Mannan; Jonathan E Shaw; Anna Peeters Journal: Obesity (Silver Spring) Date: 2011-01-13 Impact factor: 5.002
Authors: Szilárd Nemes; Ola Rolfson; Annette W-Dahl; Göran Garellick; Martin Sundberg; Johan Kärrholm; Otto Robertsson Journal: Acta Orthop Date: 2015-03-25 Impact factor: 3.717
Authors: Meghan M Moran; Brittany M Wilson; Jun Li; Phillip A Engen; Ankur Naqib; Stefan J Green; Amarjit S Virdi; Anna Plaas; Christopher B Forsyth; Ali Keshavarzian; Dale R Sumner Journal: FASEB J Date: 2020-09-15 Impact factor: 5.191
Authors: Jorge A Padilla; Afshin A Anoushiravani; James E Feng; Ran Schwarzkopf; James Slover; Scott Marwin Journal: Eur J Orthop Surg Traumatol Date: 2018-12-06
Authors: Manuel Weißenberger; Alexander Klug; Yves Gramlich; Maximilian Rudert; Philipp Drees; Reinhard Hoffmann; Karl Philipp Kutzner Journal: Knee Surg Sports Traumatol Arthrosc Date: 2020-07-15 Impact factor: 4.342
Authors: Nipun Sodhi; Hiba K Anis; Rushabh M Vakharia; Alexander J Acuña; Peter A Gold; Luke J Garbarino; Bilal M Mahmood; Nicholas R Arnold; Joseph O Ehiorobo; Eric L Grossman; Michael A Mont; Martin W Roche Journal: Clin Orthop Relat Res Date: 2020-08 Impact factor: 4.755