From 22 minutes of hunting to under 30 seconds to find any medical equipment.
A top-10 EU hospital group across 14 acute sites was losing clinical time and over-renting equipment it already owned.
The programme and figures on this page come from an earlier work by our advisers. The client name is withheld under NDA. Figures are as reported at the time. Named references are available under NDA when you engage.
What they were up against.
22 minutes lost per shift
Nurses spent around 22 minutes a shift hunting for medical equipment, telemetry units and wheelchairs.
Rental spend was climbing
Owned equipment could not be found, so the group rented duplicates to cover the gap.
No data for biomed PM
Preventive-maintenance compliance suffered with no reliable location or utilisation data.
Earlier work by our advisers. Client name withheld under NDA. Client name withheld under NDA; figures as reported at the time. Named references available under NDA. We model your own numbers when you engage.
Independent, tied to a named KPI.
We ran an independent evaluation across BLE 5.x AoA and UWB, scored against the clinical environment and accuracy budget, then designed anchor placement around real clinical workflow. Delivery was phased across 14 sites with integration to Epic and the biomed CMMS.
What the engagement delivered.
- BLE 5.x AoA locating across 8,400 tagged assets
- Integration with Epic for ED bed-state events and the biomed CMMS
- A nurse-facing find-a-medical equipment app plus utilisation analytics for biomed
Results in this engagement
The stack behind it
Baseline, method, period and what we excluded.
This page describes an engagement our advisers led in earlier roles. The client name is withheld under NDA. Figures are as reported at the time, with published industry sources where noted.
- Baseline: Nurses hunt medical equipment and beds; utilisation guessed.
- Method: RTLS on critical fleet; search time samples; utilisation and par-level exceptions to biomedical.
- Period: One wing or theatre complex, then hospital standard.
- Excluded: Tag counts without a nurse-facing find workflow.
Programme context
Hospital equipment RTLS usually starts with a critical fleet (medical equipment, telemetry, beds, wheelchairs) on one wing or theatre complex, then standardises. BLE-AoA, ultrasound/IR clinical RTLS, or hybrid stacks are common; UWB appears where sub-room accuracy is justified.
Biomed utilisation and nurse find-workflows are the twin value drivers. PHI-minimised tag-centric design keeps privacy review manageable.
Outcomes and how they are earned
Comparable programmes report large cuts in search time, higher utilisation, and deferred capital on 'missing' fleet. Publish ranges carefully. Nurse adoption decides whether the map is used.
Lessons from this engagement
Lessons: no tag without a find UX; par-level exceptions must reach biomed; avoid campus-wide day-one installs.
Deeper problem framing
Nurses lose minutes per shift hunting medical equipment and beds; biomed cannot prove utilisation; finance buys buffer fleet. PHI panic blocks programmes that could have stayed equipment-only.
Approach
Critical fleet first; tag-centric PHI-minimised architecture; nurse find UX; par exceptions to biomed; wing pilot then standard; BAA early if any identity join later.
Outcomes and measurement
Search-time samples, utilisation uplift, CapEx deferral. Exclude tag counts without find workflow from success claims.
Governance, risk and what we refuse to claim
Figures from this engagement only. Your payback depends on adoption, integration quality and exception labour, not tag unit cost. Named references under NDA on engagement.
We challenge any supplier who asks you to accept demo-day averages as production truth.
Implementation sequence and change management
Form a triad: nursing, biomed, IT/privacy. Lock equipment-only scope for phase 1. Survey the wing; choose BLE-AoA, clinical RTLS or hybrid based on workflow and infrastructure, not brochure accuracy.
Ship a nurse find UX on day one of pilot. Par exceptions must page biomed. Measure search minutes and utilisation weekly. Only then discuss patient-flow modules behind a BAA and DPIA-quality review.
Pressure-test BAA willingness, RBAC templates and audit export before award.
Buyer checklist, supplier challenges and engagement shape
For hospital equipment RTLS, refuse go-lives without a nurse-facing find workflow and biomed exception path.
Buyer checklist before you sign: (1) written system of record for events; (2) acceptance tests with 95th-percentile performance under real interference; (3) integration owner named in IT/OT; (4) privacy or labour consultation path if people are tagged; (5) cybersecurity zoning sketch; (6) five-year TCO including batteries, spares, recalibration and SLA escalations; (7) exit/export terms so you are not hostage to a cloud tenant; (8) a pilot that can fail without political punishment.
Supplier claims to challenge in this pattern: brochure accuracy without production load; 'compliance included' without artefacts; ROI that assumes perfect adoption in 30 days; references that cannot be called under NDA; install partners who have never worked your vertical's overlays; shared support accounts; and any design that dumps locating onto a flat plant or clinical VLAN.
How TRACIO typically engages: stage-1 architecture and measurement design; independent shortlist and RFP language; pilot acceptance criteria; then optional implementation oversight or programme rescue if a prior pilot stalled. We don't sell hardware, so our advice stays independent. Pages like this one exist so you can prepare the workshop. Your numbers replace every planning band when we model payback.
Risk register themes that recur: mute fatigue on alerts; shadow spreadsheets reappearing beside the platform; battery logistics understaffed; master data too weak to support identity; works-council or IG review starting too late; and success declared on demo day before night-shift reality.
Document baseline windows explicitly: what you measured, for how long, which shifts, and what you excluded. Investment committees and auditors both punish fuzzy before/after stories. If your baseline is weak, spend two to four weeks fixing measurement before ordering anchors or portals. That discipline is cheaper than a stranded deployment and is the difference between a locating programme and a technology souvenir.
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Clinical operations, not gadget demos
Independent advisory means the radio is chosen last. After the job, the constraints and the system of record are clear.
Flow and equipment jobs
Patient flow, medical equipment and beds are different jobs. We separate them before shortlisting.
Independent across RTLS suppliers
Hospital RF and EMR/RTLS integration constraints pick the stack, not a preferred badge.
Operate inside clinical IT
Events into the systems nursing and biomedical already open every shift.
Measurement
Baseline: nurse search-time samples and biomed “unable to locate” tickets for target asset classes (medical equipment, beds, scopes). Pilot: one ward or theatre suite with RTLS + asset ID, measured against the same ticket taxonomy. Steady-state: mean time-to-find, utilisation of the tagged pool, and rental / over-purchase avoidance. Clinical outcomes stay out of marketing claims unless the trust signs off.