Cost-effectiveness of robotic-assisted versus conventional total knee arthroplasty: an analysis from a middle income country
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Robotic-assisted total knee arthroplasty (RATKA) can enhance surgical precision. In middle-income countries (MICs), constrained fiscal space and the double burden of rising demand for high-cost technologies and competing public-health priorities-unlike high-income countries with broader fiscal headroom and low-income countries with limited adoption of expensive innovations-make adoption decisions for RATKA particularly challenging. We aimed to evaluate the cost-effectiveness analysis (using a cost-utility framework) of RATKA vs conventional TKA (COTKA) from a societal perspective in Thailand as a MIC. METHODS: A discrete event simulation model was employed to compare the cost-effectiveness of unilateral RATKA with COTKA over 4.5 years from a societal perspective, using patient-level data from January 2018 to June 2022 from an arthroplasty center in Thailand. Patients were propensity matched to balance comorbidities. Base case analysis assumed 1 robot performs 434 TKA cases per year with an anticipated lifespan of 12.5 years. We considered direct medical, non-medical, and indirect costs, alongside quality-adjusted life years (QALYs) gained from a societal perspective. We calculated incremental net monetary benefits (INMB) and cost-effectiveness ratios (ICERs) as the main outcome measures. Sensitivity analyses and 10 scenario analyses were performed exploring various possible settings. Threshold analyses determined combinations where RATKA could be cost-effective with positive INMB under the Thai cost-effectiveness threshold of US$4,888 per QALY gained. RESULTS: The base case analysis involved 157 COTKA and 1570 RATKA matched cases with a mean age of 69 (standard deviation 8 years). The lifetime average outcomes per patient were: COTKA-US$5,031.9 and 9.07 QALYs; RATKA-US$5,666.9 and 9.16 QALYs. The incremental (RATKA-COTKA) differences were +US$633.6 (95% credible intervals [CrI] ~592-675) and +0.085 QALYs (CrI ~0.04-0.13), yielding an ICER of US$7,436.6/QALY. RATKA was not cost-effective compared with COTKA, with an INMB of -216.9 US$/patient. The probability of RATKA being cost-effective at the Thai cost-effectiveness threshold was 44.3%. For RATKA to be economically attractive, 1 robot must operate on at least 640 TKA cases/year over 12.5 years. 3 scenarios found RATKA to be cost-effective: (i) maximal robot utilization (850 cases/year); (ii) lowest capital costs (611,060 US$/robot) with high efficacy for RATKA (hazard ratio [HR] 0.6); and (iii) extreme efficacy of RATKA in reducing complications (HR 0.024). CONCLUSION: In the context of MIC, a broad adoption of RATKA is not economically attractive as treatment of end-stage knee osteoarthritis patients compared with COTKA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".