Musculoskeletal (MSK) conditions are a major and persistent drain on health services, worsening orthopaedic waiting times and consuming primary care capacity, according to clinicians working in health technology. Peter Grinbergs, co‑founder and chief medical officer of EQL, says a fundamental rethink of triage — one that combines rapid assessment, data science and inclusive design — is needed to improve outcomes and release scarce clinical resources.
From the pitch to primary care
Grinbergs draws on years of experience as a physiotherapist in elite sport to explain why immediate assessment and intervention matter. In professional football, an injury prompts near‑instant diagnosis and a management plan, which supports quicker recovery. By contrast, the routine patient journey outside elite sport can be slow and fragmented, he said, with access to timely care often determined by where someone lives, their income or who insures them.
"The moment you watch a player get injured, you begin making a diagnosis. Within minutes, you are implementing a management strategy."
That contrast prompted Grinbergs to help build tools intended to bring more rapid, standardised assessment into wider clinical pathways. His work with EQL focuses on an AI‑enabled triage approach that assesses risk and helps determine the most appropriate next step for patients with MSK complaints.
Problems the tool seeks to address
The source identifies several entrenched issues in current MSK pathways that the triage model targets:
- Fragmented access: pathways vary by postcode and socio‑economic status, creating inconsistent journeys for patients.
- Administrative delays: slow referral processes and reliance on paper correspondence leave patients waiting while letters are processed.
- Underused early intervention: delayed assessment can mean missed opportunities for simple, effective treatments that prevent progression.
- Digital exclusion: deprived communities are at risk of being left behind if new systems do not account for access barriers.
Grinbergs argues the combined effect of these problems is longer recoveries and avoidable pressure on secondary care and orthopaedic services.
How data-driven triage could help
The model described by Grinbergs uses algorithmic assessment to stratify risk and recommend pathways that match clinical need. Key intended benefits include:
- Faster identification of urgent cases that need rapid clinician input.
- Directing low‑risk patients to conservative care or community physiotherapy, reducing unnecessary referrals to specialists.
- Standardising initial questioning and assessment so decisions are based on consistent data rather than variable clinician availability or local protocols.
The approach takes inspiration from the immediate decision‑making culture in professional sport, where real‑time assessment enables timely management.
Inclusion must be designed in
Grinbergs warns that technology alone is not a panacea. He highlights the risk of entrenching health inequalities if digital tools are not designed to be accessible. Dismantling digital exclusion, he says, must be an explicit aim so deprived communities benefit equally from faster triage and early intervention.
This point is particularly relevant for health systems grappling with a postcode lottery in access to care: unless deployment plans address connectivity, literacy and support, new pathways could widen rather than narrow disparities.
Consequences for national services
For health systems under strain, an effective triage model that diverts appropriate patients away from specialist lists and accelerates care for those who need it could free clinical capacity and shorten waiting times. However, the success of such programmes depends on robust evaluation, integration with existing services and measures to guard against exclusion.
Clinicians and managers considering similar approaches should ensure local pilots measure outcomes, equity of access and impacts on referral volumes before widescale rollout. Patients with MSK conditions should continue to seek assessment from their clinician or clinic rather than self‑diagnose.
Note: this report summarises a discussion with the co‑founder and chief medical officer of EQL on the role of data‑driven triage in musculoskeletal care and the need for inclusive technology design. It limits itself to claims and observations made in that discussion.
