Robotic total hip and knee arthroplasty: economic impact and workflow efficiency

Abstract

Robotic-assisted total joint arthroplasty (RA-TJA) is projected to account for 70% of all arthroplasties by 2030, yet its economic value and operational efficiency have yet to be thoroughly synthesized. While early literature emphasized technical precision, evolving payment models and implementation costs have shifted focus toward cost-effectiveness and workflow integration. To evaluate the economic and institutional viability of RA-TJA by synthesizing available evidence on capital costs, perioperative expenses, learning curves, throughput, and long-term adoption trends. This review also considers market competition, global uptake, and the need for standardized outcomes reporting. A narrative literature review of published cost analyses, real-world efficiency studies, and policy-relevant frameworks was conducted. Literature addressing per-case cost variability, bundled payments, and implementation strategies was analyzed. Emerging economic models and global diffusion patterns were incorporated to contextualize long-term feasibility. Robotic platforms consistently incur higher upfront and perioperative costs than manual or navigated arthroplasty. However, in both high- and low-volume institutions, these costs may be offset by reduced complications, shorter hospital stays, and improved discharge metrics. Efficiency gains are amplified through procedural clustering and experienced teams. Adoption is accelerating globally, facilitated by leasing models and market competition, yet value remains highly dependent on institutional context. A lack of standardized outcome reporting and platform heterogeneity limits cross-study comparisons. Ongoing, long-term, multicenter randomized trials are expected to address these evidence gaps. Robotic assistance can improve the efficiency and precision of arthroplasty procedures, with the potential for substantial cost-effectiveness when optimized. Institutions adopting this technology can expect improved outcomes by leveraging local surgical volume and infrastructure. Wider integration will be facilitated by robust long-term data, standardized outcome metrics, and continuous innovation that aligns with value-based care models.

Introduction

Robotic-assisted total hip and knee arthroplasty (RA-THA and RA-TKA) have gained increasing attention in recent years as potential tools to enhance surgical planning, execution, and consistency. Although the initial introduction of robotic systems was met with hesitancy primarily due to substantial capital costs, increased operative times, and training requirements, adoption rates have risen sharply. Between 2015 and 2020, RA-TKA volume increased more than sixfold, and recent projections suggest that robotic systems could be utilized in up to 70% of all TKA and THA procedures in the United States by 2030 [1–4].

Proponents of robotic platforms cite potential advantages including improved component alignment, more personalized preoperative planning, and reduced variability in surgical technique [5, 6]. Yet, definitive clinical superiority over manual approaches remains a subject of ongoing debate, with studies reporting mixed outcomes depending on the platform, procedure, and setting. As enthusiasm grows, it is essential to assess the value of RA-THA and RA-TKA through the perspectives of economics and efficiency, domains that are often decisive in shaping institutional decisions and policies.

This review explores the economic and workflow implications of robotic-assisted total joint arthroplasty (RA-TJA), including initial capital investment, cost-effectiveness across different practice settings, intraoperative efficiency, and institutional integration. We also consider broader economic frameworks such as Moore’s Law and economies of scale to contextualize how cost barriers may shift as technology matures. By synthesizing the current evidence and practical considerations, we aim to provide a balanced perspective on the evolving role of robotics in primary THA and TKA.

Economic overview of robotic arthroplasty

Upfront capital and maintenance costs

The upfront financial investment required for RA-TJA remains one of the most substantial barriers to widespread adoption. Reported purchase prices for robotic systems typically range from $500,000 to over $1 million per unit, depending on the platform, included instrumentation, and vendor-specific service contracts [7–9]. These capital costs are frequently accompanied by annual maintenance fees ranging from $40,000 to $150,000, which are essential for preserving hardware functionality, ensuring software updates, and maintaining system warranties [7, 10]. In addition to these fixed costs, robot-specific disposable items, including cutting guides, drapes, and burrs, add several hundred to over $1,000 per procedure, further increasing the per-case expense relative to manual or computer-navigated approaches [8, 9]. These additive costs contribute directly to the elevated index surgery charges associated with RA-TJA, even before accounting for downstream care or potential savings [3, 11, 12].

Despite these substantial initial costs, advocates of robotic technology emphasize potential long-term benefits, such as more consistent component positioning and improved preoperative planning, that may reduce complications, revisions, and associated downstream costs [7, 13, 14]. However, the current literature consistently shows that RA-THA and RA-TKA are associated with higher upfront and maintenance costs than manual or computer-navigated approaches [3, 8, 9, 15, 16].

Perioperative and episode-of-care costs

While much attention has been given to the capital acquisition and maintenance costs of robotic systems, their financial impacts across the entire episode of care must be considered. Several studies suggest that downstream savings, including as shorter length of stay, reduced post-acute care utilization, and lower complication rates, may partially or fully offset higher index costs, particularly in high-volume institutions [8, 10, 15, 17]. For instance, in a national Medicare analysis of over 198,000 patients undergoing TKA, Shah et al. found that for TKA, particularly in high-volume institutions, 90-day episode-of-care spending was $587 lower for patients who underwent RA-TKA compared to conventional TKA ($13,676 vs $14,263; 95% CI: -$798 to -$375) [17]. This reduction in total cost was driven by several key factors: patients in the RA-TKA group had a shorter mean length of stay (1.9 vs 2.3 days), fewer complications (2.7% vs 3.3%), and were nearly twice as likely to be discharged directly home rather than to a post-acute care facility (16.8% vs 32.4%) [17]. Similar trends have been observed for RA-THA: robotic procedures incur higher initial costs than manual techniques but may offer advantages in terms of reduced dislocations, shorter length of stay, and potential reductions in reoperations [3, 8, 18].

In summary, while RA-TJA is associated with greater perioperative and episode-of-care costs than manual and computer-navigated approaches, these costs may be offset in high-volume centers through reduced complications, shorter hospital stays, and improved long-term outcomes. As bundled care models continue to evolve, institutional volume and care standardization will likely remain key determinants of cost-effectiveness.

Site of care delivery

The site of care delivery is an important determinant of episode-of-care costs for RA-TJA. Across both Medicare and international health systems, ambulatory surgical centers (ASCs) consistently demonstrate lower overall costs compared with inpatient hospital admissions and hospital outpatient departments (HOPDs), while maintaining equivalent safety and clinical outcomes in appropriately selected patients. Recent analyses of Medicare Part A and B claims estimate annual savings of approximately $235 million when TJA is performed in ASCs rather than inpatient hospitals, and $137 million compared to HOPDs, with adjusted costs for primary total hip and knee arthroplasty averaging roughly $8,500 per case in the ASC setting [19]. Similar trends are observed in Canadian data, where outpatient arthroplasty, including robotic and manual, achieves perioperative and long-term savings of $3,800–$7,000 per case over a three-year period without increased adverse events [20].

While robotic-assisted techniques incur initially higher supply and capital costs relative to manual approaches, these differences are attenuated when accounting for patient factors, comorbidity burden, and facility efficiencies. In ASCs, RA-TKA and RA-THA have demonstrated safety profiles comparable to both conventional ASC procedures and hospital-based RA-TJA, with no increase in complication or readmission rates [21, 22]. Overall, shifting RA-TJA to the ASC environment can magnify the cost advantages inherent to outpatient care, provided that patient selection criteria, perioperative protocols, and facility resources are optimized. However, the incremental cost of robotic technology may offset some of these savings, underscoring the importance of aligning case selection, surgeon experience, and reimbursement structures to realize the full economic benefit [23].

Value in high- vs. low-volume centers

One of the most influential determinants of cost-effectiveness in RA-TJA is institutional case volume. High-volume centers are positioned to extract greater value from robotic platforms by amortizing the substantial upfront capital and recurring maintenance costs across a larger number of procedures, while lower volume settings can still observe benefits of robotic implementation via reductions in episode-of-care costs.

Cost modeling studies have identified case thresholds of 24 to 50 RA-TKA procedures annually as the minimum required to achieve financial neutrality, meaning the point at which robotic assistance becomes economically comparable to manual techniques. Above this threshold, the economic benefits increase markedly. In centers performing more than 100–200 RA-TKA procedures per year, per-case costs can decline to approximately $3,900–$7,500, and incremental cost-effectiveness ratios (ICERs) as low as $2,331 per quality-adjusted life year (QALY) have been reported- well below standard willingness-to-pay benchmarks [10, 15, 17]. In these settings, RA-TJA may be not only cost-effective, but even cost-saving, especially when potential reductions in revision rates and long-term complications are considered [10, 15]. Importantly, high-volume centers also demonstrate superior clinical outcomes in arthroplasty overall, including lower complication rates, shorter length of stay, and reduced total charges, further enhancing the value proposition of robotic platforms [24]. These benefits, in combination with favorable economic indicators, reinforce the notion that robotic technology is best deployed in settings with the infrastructure and case throughput to optimize its potential.

While high-volume centers are more likely to recoup the upfront costs of robotic platforms through surgical throughput, emerging evidence suggests that RA-TJA may also offer economic advantages in lower-volume settings by reducing the incidence and downstream costs of perioperative complications. Multiple studies have demonstrated that RA-TJA is associated with lower rates of mechanical complications, infections, thromboembolic events, and transfusions compared to manual surgery, all of which are key drivers of episode-of-care costs [3, 8, 25–28]. Cotter et al. reported that even in a moderate-volume, single-surgeon practice, the higher intraoperative costs of RA-TKA were offset by significantly lower 90-day costs due to shorter length of stay and decreased post-acute care utilization, driven largely by reduced complication rates [8]. Similar findings were reported by Constantinescu et al. and Aggarwal et al., who observed fewer perioperative complications and shorter hospitalizations following RA-TKA [25, 27]. Thus, even in smaller programs, robotic systems may provide value by mitigating the costly burden of complications commonly associated with conventional instrumentation.

Medicare vs private payer implications

The cost-effectiveness of RA-TJA is not only shaped by institutional volume and system costs, but also by the type of payer and associated reimbursement structures. In particular, Medicare and private insurers differ substantially in how surgical episodes are reimbursed, which affects a hospital's ability to recover the upfront and perioperative costs associated with robotic platforms.

Within the Medicare system, reimbursement is fixed and standardized, which can constrain cost-effectiveness in lower-volume centers. However, high-volume institutions may achieve savings, particularly under value-based programs like the Bundled Payment for Care Improvement (BPCI) initiative. This is supported by numerous literature demonstrating that hospitals utilizing robotics for > 50% of their total arthroplasty volume have lower episode costs, shorter lengths of stay, and higher rates of discharge to home, all of which contribute to improved cost-effectiveness under bundled payment models [15, 17, 29, 30].

Yet, the broader financial trend of declining reimbursements in TJA complicates robotic viability in the Medicare population. A longitudinal study by Wang et al. revealed that from 2010 to 2018, Medicare surgeon reimbursements for TKA and THA declined significantly, falling 2 to 2.8 times faster than payments from commercial payers after adjusting for inflation [31]. On average, Medicare reimbursed 57% less than commercial payers for inpatient orthopedic surgeries, and Medicare payments per work relative value unit (wRVU) dropped notably for TKA (–0.83%) and THA (− 0.80%) over the study period [2]. These declining surgeon reimbursements may strain the financial feasibility of adopting high-cost technologies like robotic systems, particularly in practices with a large proportion of Medicare patients.

Both payer structure and payment trajectory play critical roles in determining the cost-effectiveness of robotic platforms. Medicare’s declining reimbursement rates and bundled payment pressures favor high-volume, highly efficient systems. As reimbursement for orthopedic procedures continues to decrease, particularly from Medicare, the bar for sustainable robotic adoption is likely to rise, reinforcing the importance of volume, care coordination, and outcome optimization.

Efficiency and workflow impact

Operative time and learning curve

A brief learning curve for RA-TJA is well documented in the literature. While robotic procedures are associated with slightly longer operative times of 12 to 25 min during early adoption, this modest increase is transient and typically normalizes after 6 to 20 cases, depending on the surgeon’s experience and the robotic system used [32–34]. In high-volume surgical environments, this early inefficiency has been shown to have negligible impact on patient outcomes or institutional costs [11, 16, 32, 35].

Importantly, the learning curve associated with robotic adoption is confined to operative efficiency and team coordination, not surgical precision. Multiple studies have demonstrated that implant positioning, limb alignment, and gap balancing remain consistently accurate from the first case onward, despite brief increases in operative time during early adoption [34, 36–38]. In a retrospective cohort study of 90 RA-TKAs and 30 conventional TKAs, Zhang et al. found greater limb alignment in the RA-TKA group, despite a brief learning curve [38]. A similar trend has been observed in robotic-assisted unicompartmental knee arthroplasty (RA-UKA). In a prospective study of 60 consecutive RA-UKA cases, Kayani et al. found that while operative times and surgical team anxiety levels followed a brief learning curve of approximately seven cases, RA-UKA demonstrated statistically superior accuracy in implant positioning and limb alignment [37]. These results highlight how robotic platforms can uphold surgical precision from the first case onward, offering immediate clinical value that complements broader institutional goals of consistency, quality, and long-term cost-effectiveness.

Operating room workflow and personnel considerations

The successful integration of RA-TJA into the operating room demands coordinated adjustments across the entire surgical team. The well-documented learning curve of surgeons during early stages of adoption is mirrored by operating room staff. In a rapid review on robotic systems, Martinello et al. found nursing staff experience notable challenges in growing acclimated to robotic surgical systems, particularly due to the novel set-up phase, expanded surgical duties, and longer operative time [39].

To support this transition, most manufacturers provide structured training programs to help reduce variability in team performance during early implementation [40]. Additionally, the involvement of a dedicated robotic technician, responsible for system setup, calibration, and real-time intraoperative support, significantly reduces the cognitive and technical burden on surgeons and operating room staff, enabling smoother transitions between cases and enhancing intraoperative flow. Fontalis et al. specifically note the critical role of the robotic technician in troubleshooting and workflow optimization [41]. Finally, it is crucial that support from the manufacturer is well-established during implementation to ensure optimal utilization of hardware and software after purchase [42].

In short, the adoption of RA-TJA requires a teamwide adjustment in workflow, equipment handling, and interprofessional coordination. Institutions that invest in comprehensive training, clearly defined team roles, and repeatable intraoperative protocols are best positioned to translate robotic precision into scalable clinical value (Table 1).

Table 1.

Factors contributing to cost of robotic utilization in total joint arthroplasty

Cost-Increasing Factors	Cost-Offsetting Factors
• Capital cost: $500 K–$1 M [7–9] • Annual maintenance: $40 K–150 K [7, 10] • Per-case disposables: $300–$1000 [8, 9] • Increased early operative time (12–25 min) [33–35] • Staff training + robotic technician costs [41]	• Shorter LOS [3, 8, 17, 18] • Lower 90-day complication rate [17, 25, 26] • Higher rate of home discharge [36, 43] • Lower readmission [26] • Higher alignment accuracy → fewer revisions (projected) [13, 37, 38]

LOS Length of Stay

Discharge timing and recovery

When assessing the economic value of RA-TJA, it is essential to look beyond the upfront costs of acquisition and operative time. The downstream recovery trajectory, including hospital LOS, discharge disposition, and time to functional independence plays a critical role in shaping total episode-of-care expenditures and patient quality of life.

RA-TKA has been consistently associated with improved early recovery, reduced hospital LOS, and higher rates of home discharge compared to conventional approaches. A multicenter analysis of 10,296 patients by Archer et al. demonstrated that nearly 48% of RA-TKA patients were discharged within one day, compared to 39% of manual TKA patients, with a significantly higher proportion discharged directly home without skilled care (91.3% vs. 87.4%, p < 0.0001) [43]. Additionally, a prospective cohort study by Kayani et al. demonstrated, less postoperative pain, faster achievement of functional milestones, and fewer physiotherapy sessions in the RA-TKA group compared to conventional jig-based TKA [36]. Similar improvements have been observed in patients undergoing RA-THA, with numerous literature supporting significant reductions in LOS and non-home discharge with robotic implementation.

The underlying explanation for improved early recovery with RA-TJA likely involves a combination of more precise component alignment, reduced iatrogenic soft tissue injury, and lower postoperative inflammation, ultimately translating to lower pain and greater early mobilization following surgery [44]. Ultimately, these factors translate into lower opioid requirements and faster achievement of mobility milestones in the early postoperative period.

The early advantages of RA-TJA, grounded in measurable physiological changes, may be a meaningful opportunity to capture value, as even modest gains in early recovery can enhance throughput, reduce inpatient resource utilization, and improve patient satisfaction. As healthcare shifts toward bundled payments and outcome-driven reimbursement models, the early postoperative phase may emerge as a key differentiator in the cost-effectiveness of robotic platforms.

Scheduling and throughput

Efficient scheduling is essential for integrating RA-TJA without compromising throughput. Scheduling multiple robotic procedures sequentially can minimize repeated setup and breakdown, a concept known as case clustering. This approach allows operating room teams to reduce idle time, which can ultimately match or even exceed the efficiency of manual arthroplasty [32, 45]. Meghpara et al. observed that early robotic cases performed in isolation showed no meaningful improvement in turnover times; however, once surgeons began clustering ≥ 3 robotic-assisted TKAs per day, a learning curve in turnover efficiency emerged, indicating that operational gains are closely tied to strategic scheduling [32]. While manual TKA generally requires less setup and transitions efficiently even when unclustered, the relative complexity of robotic workflows makes them particularly amenable to gains through repetition. In this context, RA-TJA can rival or surpass manual TKA throughput when case sequencing, team familiarity, and workflow standardization are optimized.

In addition to clustering, high-efficiency programs often rely on dedicated robotic teams, standardized checklists, and streamlined workflows to match the efficiency of manual arthroplasty [32, 46, 47]. These standardization tools help mitigate the learning curve and promote reproducibility across surgical teams and institutions. Multiple studies, including those by Putzer et al. and Shatrov et al., demonstrate that as teams gain experience, there is a significant reduction in robotic-specific setup and operative times, with improved efficiency and confidence among both surgeons and staff [46, 47]. The use of checklists and defined protocols is highlighted as a key factor in this process.

Long-term viability and technological maturation

Moore’s law and economies of scale

The trajectory of RA-TJA mirrors the technological pattern described by Moore’s Law, which posits that computing power doubles while costs halve over regular intervals. In the context of arthroplasty, the early adoption phase of robotics was marked by high capital costs, limited functionality, and restricted access. However, ongoing advances in hardware and software, increasing manufacturer competition, and greater market penetration have begun to drive down per-unit costs while improving the utility and precision of these systems, similar to the economic and technological maturation observed in early computing industries [48–50].

Furthermore, the diffusion of innovation framework helps contextualize the adoption pattern of robotic arthroplasty. Early adopters incur higher costs and steeper learning curves, but they pave the way for later adopters to benefit from refined workflows, broader training resources, and reduced technology prices as production scales up [7, 49, 50].

Finally, productivity gains driven by experience and workflow standardization are also well documented, with studies showing that operative times and system setup become increasingly efficient over time [15, 51, 52]. The cumulative benefits of technological innovation, scaled manufacturing, competitive pricing, and procedural refinement have collectively shifted the cost-utility curve in favor of robotic systems, reinforcing the notion that robotic arthroplasty is following a Moore’s Law-like progression toward broader accessibility and greater economic value.

Projected trends in adoption and cost decline

The projected trajectory of RA-TJA underscores its increasing integration within orthopedic practice. Recent modeling of national inpatient data suggests that RA-KA will account for approximately 70% of all TKA procedures in the United States by 2030 [4]. This growth is not solely driven by clinical efficacy, but also by nonclinical forces such as institutional marketing strategies, patient demand, and administrative prioritization of technological differentiation [2, 49, 53].

To facilitate this widespread adoption, emerging economic models are reducing the barrier to entry. Hospitals increasingly rely on leasing and pay-per-use arrangements that allow for cost deferral and flexible financing rather than large upfront capital expenditures [49]. In high-volume health systems, robotic units are also being shared across multiple sites, further amortizing the fixed costs associated with procurement and maintenance [10, 15].

Global adoption is also expected to accelerate as unit prices decline and financing structures proliferate. Middle-income countries, where high surgical volumes often coexist with limited capital liquidity, are increasingly exploring robotic platforms, particularly when leasing models or vendor-subsidized partnerships become available [52]. While the World Health Organization has not issued specific guidance on robotic arthroplasty, its broader emphasis on surgical capacity-building in low- and middle-income countries (LMICs) creates a supportive ecosystem for future adoption. Precedents from mobile health and telemedicine demonstrate that once hardware costs decline and infrastructure stabilizes, technological catch-up in LMICs can occur rapidly [52].

Challenges, limitations, and the need for standardization

Despite growing enthusiasm and adoption, RA-TJA faces persistent challenges that must be addressed to ensure its long-term viability and equitable integration into clinical practice. Chief among these is the lack of standardized outcome reporting across robotic platforms. Each system, whether MAKO, ROSA, CORI, or TSolution One, operates with distinct technical workflows and designs, and outcome studies often vary in endpoints, methodology, and follow-up duration. This heterogeneity has made cross-platform comparisons difficult and limits the ability to synthesize data in meta-analyses or generate consensus on best practices [54, 55]. To address these challenges in future work, each robotic system must be analyzed independently for accurate cross-platform comparisons to be made.

Additionally, major organizations such as the American Academy of Orthopaedic Surgeons (AAOS) continue to call for high-quality randomized trials and long-term outcome data to define the value proposition of robotic systems across diverse care settings. One of the most ambitious efforts is the UK Robotic Arthroplasty Clinical and Cost Effectiveness Randomised Controlled Trial for Hips (RACER-Hip) trials, which are multicenter, randomized controlled trials specifically structured to address both clinical and economic outcomes over extended follow-up periods. These trials are intended to provide robust, high-quality evidence to inform practice and policy, addressing current gaps in the literature [56, 57].

Although robotic arthroplasty holds immense promise, its continued advancement depends on standardized reporting, rigorous long-term studies, and harmonized metrics to ensure that innovation is matched by evidence, equity, and value.

Conclusion

RA-TJA is a rapidly maturing frontier within orthopedic surgery, with growing evidence supporting its technical precision and workflow advantages. However, its value is not universally recognized. Economic viability remains highly dependent on institutional factors including surgical volume, workflow optimization, and team integration. In high-throughput environments, robotic systems can be deployed efficiently, with reduced per-case costs and favorable outcomes that align with contemporary value-based care models.

Simultaneously, the RA-TJA landscape is being reshaped by increasing market competition, emerging technologies such as AI, and broader access enabled by leasing and vendor-financed models. These forces are accelerating adoption in both high- and middle-income settings, even as definitive comparative data remain limited. The absence of standardized outcome reporting and the heterogeneity across robotic platforms continue to challenge evidence synthesis and policy development.

Ongoing multicenter randomized trials will play a pivotal role in defining the long-term clinical and economic value of robotic arthroplasty. Until such data are available, broader adoption should be guided by local infrastructure, volume capacity, and a deliberate assessment of cost–benefit tradeoffs.

Author contributions

B.E.J. and S.T.K. wrote the main manuscript text. B.E.J. prepared the table. N.S.P. conceptualized the study and managed project administration. All authors (B.E.J., S.T.K., A.K.E., K.A.E., M.D., and N.S.P.) reviewed and edited the manuscript.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Conflict of interests

Conflict of Interest Statement: Mr. Benjamin E. Jevnikar, Dr. Shujaa T. Khan, Dr. Ahmed Emara, and Dr. Khaled A. Elmenawi have no conflicts of interest. Dr. Matthew E. Deren reports honoraria from Brasseler, stock in Romtech, and serves on the editorial board of The Journal of Knee Surgery. Dr. Nicolas S. Piuzzi reports research support from Osteal Therapeutics, Zimmer-Biomet, Peptilogics, RegenLab, and Signature Orthopaedics; consulting for Pacira and Stryker; and board/editorial roles with AAHKS, ISCT, and The Journal of Bone and Joint Surgery.