Real-World Robotics: How HTA Must Evolve to Assess Surgical Innovation

In the two decades since the arrival of robotic-assisted surgery (RAS), clinical teams across urology, colorectal, gynaecological and orthopaedic domains have embraced its ergonomic advantages, precision tooling and potential for same-day recovery. Yet, RAS remains one of the most hotly debated frontiers in health technology assessment (HTA) — challenged by insufficient economic justification, inconsistent data standards and a fragmented post-market evidence base. This blog explores how HTA must evolve to reflect the real-world complexities of surgical robotics, with a particular focus on registry infrastructure, health economics and regulatory-scientific policy frameworks — grounded in scientific literature, European real-world data mapping and HTA global consensus.

The Belgian KCE HTA clearly articulated a dilemma facing HTA bodies and payers: despite RAS’s technical promise (e.g. 3D vision, tremor filtering, improved articulation), the evidence of cost-effectiveness versus laparoscopic surgery remains inconsistent. Most existing evaluations suffer from:

• Small sample sizes
• Short-term endpoints (LOS, bleeding)
• Non-standardised comparator arms
• Absence of health-related quality-of-life (HRQoL) data

Marketing and prestige often drive procurement even where per-case costs exceed €3,000, without robust evidence of system-level improvement.

A landmark study by Pongiglione et al. (2021) identified 77 real-world data (RWD) sources on robotic surgery across 15 EU countries. The sobering finding: only a fraction were usable for HTA purposes due to Missing PROMs and HRQoL data, incomplete comparators and fragmented economic indicators

Ballini et al. (2010) proposed a gap-based HTA method now used in several EU evaluations:

1. Identify missing clinical-economic evidence domains
2. Classify gaps by criticality
3. Use structured observational studies or registries to close gaps
4. Incorporate safety analytics (FMECA) to assess robotic-specific workflow risk

These principles underpinned Italy’s early hospital-based HTA of robotic platforms, confirming positive clinical signals but systemic complexity in terms of staff coordination, cost and learning environment.

Health Economic Modelling: Limitations in Practice

HTA submissions for robotic platforms often fall short due to:

• Narrow time horizons (<5 years)
• Lack of learning curve adjustments
• Absence of indirect cost modelling (workforce reintegration, rehab)
• Missing utility/QALY values from PROMs

Lai et al. (2024) reviewed >40 robotic HTAs and found that only 20% included PROM-derived QALYs, and fewer than 10% applied societal perspectives.

Their key findings were::

• Robotic prostatectomy = £16,000–£35,000/QALY (only when PROMs included)
• Robotic colectomy = cost-neutral or dominated vs laparoscopy
• Break-even only at high-volume centres (>300 RAS cases/year)

To reflect real-world performance, HTA agencies should consider:

• Conditional funding tied to centre volume and surgeon proficiency
• Bundled procedure pathways (multi-specialty robotics)
• Real-time PROM-based feedback loops
• Operator-based costing models (e.g., per-surgeon outcome adjustment)

This logic underpins the NHS England Innovation Tariff, NICE’s Early Value Assessment (EVA) pathway and emerging modular HTA frameworks.

RAS evaluation is moving from static HTA toward continuous lifecycle evidence generation. 

This requires prospective, multi-centre registries, linked hospital+claims+PROM data and standardised fields for international comparability.

Ledidi x CMR Surgical: A Case Example

Ledidi is a regulatory-grade digital registry platform now deployed by CMR Surgical, manufacturers of the Versius™ system, to power real-time registry and PROM integration across NHS and EU centres. 

It enables:

• EQ-5D, Oxford Hip/Knee Scores, GIQLI
• Cross-arm comparisons (robotic vs laparoscopic vs open)
• LOS, readmission, complications
• Surgeon learning curve tracking
• Cost-utility exportable models for NICE, ZIN, HAS, and G-BA

Odelle Technology works alongside robotic manufacturers to structure these evidence platforms and align them with HTA submission milestones, conditional procurement pathways and investor-grade economic narratives.

Several manufacturers are now adopting similar strategies:

• Intuitive Surgical (da Vinci®) – long-standing data ecosystem, but pivoting to real-world linked economics
• Medtronic (Hugo™) – targeting multiprocedure footprint, early PROMs capture in EU
• Moon Surgical (Maestro™) – enabling collaborative robotics in constrained ORs, requiring new outcome frameworks
• Stryker (Mako™) – PROMs-backed registry in orthopaedics, with focus on mechanical alignment and revision risk
• Zimmer Biomet (ROSA™) and Johnson & Johnson (VELYS™) – integrating registry tools with implant tracking

These companies all stand to benefit from adaptive HTA, registry-powered pricing strategies, and modular procurement logic.

Lifecycle HTA Model

Payers and regulators need interoperable datasets that include:

• Patient safety (mortality, reintervention, LOS)
• Patient experience (EQ-5D, symptom scores)
• Comparator consistency
• Surgeon volume/proficiency
• Cost inputs from theatre staff, implants, device usage
• Learning environment tracking

This can be achieved through Ledidi-powered registries, jointly governed by HTA, clinical, and commercial actors.

Robotic surgery is no longer speculative — but its evaluation still is. 

Without PROMs, RWE and registry-linked pricing, we are left judging surgical technologies with frameworks built for static pharmaceuticals.

At Odelle Technology, we help bridge this gap — offering strategic HTA services, RWE integration, registry design, and reimbursement support across the UK, EU, and global markets.

Robotic Assisted Surgery is here to stay. The question is: “Can we measure what matters — and reward it accordingly?”