Common questions about pre-analytics.

143 such cases were measured among 1,394,862 samples from 39 transfusion services in nine countries. Broken down by where the sample was taken, that is 1.23 cases per 10,000 samples in the emergency department, 0.71 on the ward and 0.24 in outpatient phlebotomy (Dunbar et al., Transfusion 2021). So outpatient phlebotomy is the safest of the three places, not the most dangerous. All three figures are lower limits: the error is mostly only noticed when blood is prepared for transfusion, and a mix-up between two patients with the same blood group is never noticed at all.

Source: WBIT rate by place of draw (BEST Collaborative) ↗. Derivation and level of certainty under Sources & methodology.

Three independent measurements arrive at the same figure. Barcode-based patient identification at the draw cut labelling and identification errors from 5.45 to 3.2 per 10,000 samples, a fall of 41 per cent (Am J Clin Pathol 2010). A combined barcode and order-entry system also cut them by 41 per cent (Simpson 2001). And in an outpatient collection centre the error rate fell by 43 per cent after automatic tube labelling was introduced (PLOS One 2016, around 30 million samples over ten years). The other side belongs here too: around 59 per cent remain. No system prevents every case, and that is exactly the effectiveness the savings calculator works with, not 100 per cent.

Source: Positive patient ID in phlebotomy ↗ · Barcode + order entry against labelling errors (Simpson 2001) ↗ · Automatic labelling in a collection centre (Taiwan, 10 years) ↗. Derivation and level of certainty under Sources & methodology.

Because they are usually drawn and labelled by people who are not laboratory staff. Studies show a pre-analytical error rate two to four times higher when blood is drawn by non-laboratory staff than by trained laboratory staff. The savings calculator reflects that: for private laboratories, whose samples come mostly from GP practices, the share of labelling errors is set higher than for hospital laboratories, whose requesters are colleagues in the same organisation who can be trained.

Source: Pre-analytical errors by staff group ↗. Derivation and level of certainty under Sources & methodology.

Mostly, yes. In an analysis of more than 800,000 draws, around 84 per cent of rejected samples needed a redraw; only about 16 per cent could be resolved another way: by dilution, a second tube that was already there, or a partial report. The rejection rate itself was 1.0 per cent on the wards, 0.35 per cent in outpatients and 1.97 per cent in the emergency department. In outpatients a redraw is often not possible at all, because the patient has long since gone home; there the result is more often reported with a comment (Lippi and Simundic 2017).

Source: Redraw versus report with comment (Karcher/Lehman 2014; Lippi & Simundic 2017) ↗. Derivation and level of certainty under Sources & methodology.

Two different figures are being mixed up here. For ERRORS, around 60 to 70 per cent are pre-analytical: 68.2 per cent was measured in 1997 and 61.9 per cent in 2007, confirmed by later reviews (Plebani and Carraro). For TIME, pre-analytics is also the largest block, but at around 56 to 62 per cent of the turnaround time (Bhatt et al. 2019). The widely quoted 75 per cent covers pre- and post-analytical errors together, so everything outside the actual measurement. As a figure for pre-analytics alone, it overstates.

Source: Share of pre-analytical errors (Plebani/Carraro; Lin 2025) ↗ · Bhatt et al. 2019 ↗. Derivation and level of certainty under Sources & methodology.

Then it stays handwork – and that is not a fault but a question of specification. The GTL100 handles plastic tubes of 13 to 16 millimetres in diameter and 75 to 100 millimetres in length. Anything outside those dimensions is still labelled by hand, with the label coming from one of the desktop printers. How large that share is in your hospital is something we look at in the discovery workshop using your materials catalogue, rather than estimating it here.

More on this: Product overview for this area.

Then nothing changes for it. Automatic labelling works where your own organisation does the labelling. Whatever a requester has prepared carries on unchanged. That is why the savings calculator only counts the share of your samples you label yourselves, not all of them. For tubes labelled elsewhere with a barcode that is hard to read, the rework you already have today remains.

More on this: Sources & methodology.

Then the process carries on as it does today: print the label, stick it on by hand. The device is not a precondition for accepting samples. It takes one step off your hands, it does not replace a process. And one source of disruption disappears anyway: with no thermal transfer ribbon, there is no ribbon to change in the middle of a batch. Just in case: a three-year return-to-base warranty and standard GoDEX support on working days from 8 to 12 and 1 to 5 – by phone, by email and, where needed, by remote maintenance. We name two limits straight away: return-to-base means the device goes away for repair, and no loan device is included; and support covers working days, not nights or weekends.

Less than people assume, which is why, by default, we count nothing for it. The draw dominates: puncturing directly instead of drawing through a freshly placed line reduces haemolysis by around 84 per cent (a meta-analysis of eleven studies, risk ratio 0.16). For transport, on the other hand, the most widely cited study finds no difference between a tube system and a porter run (13.6 against 13.1 per cent). So the savings calculator sets the transport-related reduction to zero out of the box; it only counts once a laboratory brings a measured difference from its own system. What a system certainly does influence is the extra stress from poor sizing: cell damage only rises measurably from about 6 metres per second or 250 metres of route – a braked, adjustable system stays below that.

Source: Phelan et al. 2016 – tube systems and haemolysis ↗ · Haemolysis arises at the draw (LMBP meta-analysis) ↗ · Tube-system transport time (lit.) ↗. Derivation and level of certainty under Sources & methodology.

Usually yes, but in stages. An installed tube system typically covers the main wards, rarely the whole site: outlying buildings, distant wings and specialist areas often stay manual. That is why the savings calculator asks how much of the site is covered and only counts the rest. What you already have is taken off, not sold again. Two further things depend on who made the existing system: AirLab single-tube transport can be coupled to any system, but the automatic unloading station only to an Aerocom system.

Source: Tube-system transport time (lit.) ↗ · project data / figures from experience. Derivation and level of certainty under Sources & methodology.

Public tender documents show it. For the complete renewal of an existing system at Klinikum rechts der Isar – 194 send and receive stations, 91 diverters and around 645 metres of tube, with the existing tubes left in place – the contract ran from May 2026 to September 2027, so just under 16 months. It can be smaller and faster: at Klinikum Bogenhausen an existing system was extended by 20 stations and 1,200 metres and connected to a new building, with 100 days allowed for it. What matters is what these figures mean and what they do not: they say how long the contractor is on site, not how long anything stands still for you. The work is done section by section. What applies to your hospital depends on the building and the routing, and in the end it is a question for the manufacturer, not for a statistic.

Source: Tube-system planning: construction time and sizing (official) ↗. Derivation and level of certainty under Sources & methodology.

The manufacturer states up to 50 per cent more efficient carrier handling. There are no published figures in seconds for it, and we say so openly. So the savings calculator uses a figure from experience: around 20 seconds per carrier for taking it out, opening it, emptying it and sending it back. That figure is marked as an assumption and can be checked in the workshop with a stopwatch.

Source: Automatic unloading station (Aerocom) ↗ · project data / figures from experience. Derivation and level of certainty under Sources & methodology.

No. The literature describes it as closed sample reception: the tube system delivers samples straight into the bulk input of the lab automation, independent of the manufacturer and without cartridges (Clinical Chemistry and Laboratory Medicine 2016). In our setup the automatic unloading station does this; AirLab single-tube transport even connects single tubes with no carrier at all.

Source: Automated delivery / TLA (lit.) ↗. Derivation and level of certainty under Sources & methodology.

Then the samples go on foot again. The tube system replaces the porter run, it does not abolish it – which helps in a fallback, because nobody has to invent a procedure. Within the system every shipment can also be tracked, so where a carrier is stuck is always known. What a fault means in a particular case, how quickly it is fixed and whether your design provides alternative routes belongs to the planning for your hospital; there is no general figure for it, and we do not give one here.

More on this: Product overview for this area.

Then it does not travel. Which sample types stay excluded is decided by your laboratory. That is a professional decision, not a device setting. For everything else: the transport speed can be configured per sample type rather than being fixed at the factory, and arriving carriers are braked pneumatically with counter-pressure air rather than stopped mechanically. So the design is the lever – not giving up the transport route.

More on this: Product overview for this area.

With automatic unloading nothing is left waiting: the station receives the carrier, opens the lid, unloads the samples and sends the empty carrier back by transponder. Without that extension, the carrier stays in the station until someone empties it. An existing tube system is required. Automatic unloading replaces unloading at the destination, not the transport route.

More on this: Product overview for this area.

The literature gives very different figures: individual studies 14 to 39 per cent, and over 80 per cent in hospitals with few resources. What is measured there, though, is “at least one field incomplete”, hence the high rates. For the calculation, only the share that actually triggers a query or a correction counts; around 5 per cent is set for that, deliberately at the low end, because most ordering is electronic and paper is what is left over.

Source: Incomplete request forms (lit.) ↗. Derivation and level of certainty under Sources & methodology.

From measured data in a customer project, around 74 per cent fully automatically. The remaining 26 per cent or so stays handwork, but with assistance it falls to about 20 seconds per form. The savings calculator works with these two figures and not with 100 per cent. That was an earlier assumption and has been corrected.

Basis: project data / figures from experience. Derivation and level of certainty under Sources & methodology.

In an analysis over 5.5 years with 880,359 add-on requests, the share was 3.3 per cent of test volume. 87.3 per cent of these add-ons arrive within 8 hours, 96.8 per cent within 24 hours – by then the sample is already in the archive or the fridge and has to be found first (Nelson et al. 2015). The figures come from a single US university hospital and carry over to central European conditions only to a limited extent.

Source: Nelson et al. 2015 – add-on testing (BMC Clin Pathol) ↗. Derivation and level of certainty under Sources & methodology.

In hospitals the US median is around 37 per cent, with outliers up to about 50 per cent; from around 30 per cent, control is considered to tip over, because almost everything is urgent and prioritisation loses its meaning (Lippi and Plebani 2012). Routine outpatient work is far lower. The savings calculator starts cautiously with 25 per cent for hospital laboratories and 2 per cent for private laboratories.

Source: Literature on the share of STAT samples ↗. Derivation and level of certainty under Sources & methodology.

The direction is evidenced, not an exact figure. Structured urgent triage is a recognised lever in the pre-analytical phase, and field reports show a clear percentage reduction in the pre-analytical time for urgent samples through prioritisation. There is no reliable figure in minutes for central European laboratories; the savings calculator therefore uses a figure at the low end and shows it as an assumption. What it means in your laboratory is worked out by the savings calculator further down with your own figures.

Source: STAT prioritisation / triage and TAT ↗. Derivation and level of certainty under Sources & methodology.

A process survey across 35 laboratories found 13.4 per cent of routine and 11.5 per cent of urgent samples in clinical chemistry (Perrotta et al. 2020). The figure is more of a lower limit: only the route to the laboratory's own chemistry analyser was recorded, and aliquots for sending out, the archive or a biobank are missing. There is no central European figure and no split between hospital and private laboratories.

Source: Perrotta et al. 2020 – share of aliquoting (CAP Q-Probes) ↗. Derivation and level of certainty under Sources & methodology.

Then nobody guesses. Whatever recognition cannot resolve clearly goes to the order-entry backup: the case is put forward rather than waved through, and it is corrected before the handover to the LIS – not afterwards in the report. A plausibility check also runs before every handover. The query to the requester does not disappear, but it becomes the exception rather than the day's work.

More on this: Product overview for this area.

It does not have to be pushed to the front. The sample flow control moves urgent samples forward on the basis of the order and steers the sorter accordingly; the middleware also actively diverts urgent samples. That does not replace agreement within the team, but moving a sample forward no longer depends on who happens to see the sticker.

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Then order digitisation brings little, and the savings calculator says so by itself. If ordering is almost entirely electronic, it sets the items for typing in and form queries to zero, rather than showing a saving that does not exist. Independently of that, the control remains: moving urgent samples forward, spotting deviations at goods-in, and carrying on when the system of record slows down.

More on this: Sources & methodology.

You teach the system a new form layout yourselves. It needs neither a project nor a visit from an engineer. If you like, STIWA's customer service team will go through it with you. This is where a private laboratory with changing requesters makes its decision: layouts only you know, you also have to be able to maintain yourselves.

More on this: Product overview for this area.

In one study, after an automatic sorter was introduced, rejected samples fell from 0.4 to 0.2 per cent and tests not carried out from 4.5 to 1.4 per cent. The manual pre-analytical error rate is around 0.44 per cent; that is also the starting figure the savings calculator uses for sorting errors.

Source: Automatic tube sorting (lit.) ↗. Derivation and level of certainty under Sources & methodology.

The standard says: serum or plasma should be separated from the blood cells within 2 hours of the draw (CLSI GP44 and PRE04). Potassium is stable for around 4 hours at room temperature; what is critical is mainly the combination of delay and cold. How many samples actually miss that limit in a laboratory, the standard does not say – that is a measurement in your own building, not a figure from the literature. That is why the calculator deliberately has no default figure for it.

Source: CLSI GP44-A4 / PRE04 (sample stability) ↗. Derivation and level of certainty under Sources & methodology.

For fully automated laboratory lines it has been measured: one analysis with time-and-motion studies before and after introduction reports two and a half fewer full-time posts among testing staff and 82 per cent less hands-on time for add-on requests; a second reports around 30 per cent fewer staff with 27 per cent more sample volume. A sorter is one step of such a line, not the same thing. These figures show what is possible, not what we promise. What becomes free in your laboratory is worked out by the savings calculator further down with your own figures.

Source: Automated delivery / TLA (lit.) ↗ · Dynamic load balancing / routing round congestion (middleware) ↗. Derivation and level of certainty under Sources & methodology.

Because a sample's waiting time is not anyone's working time. While a sample waits for the centrifuge bucket to fill, nobody is working on it; multiplying those minutes by staff costs per hour would invent a saving that does not exist. So the calculator keeps two separate clocks: money depends only on actual working time, turnaround time only on the sample's own time. The same minute may appear on both clocks – two different things are then being valued.

More on this: Sources & methodology.

Then the sample is diverted out, not guessed at. The sorter has its own compartment for that: whatever it cannot register with certainty ends up there and comes to you, rather than being sorted wrongly into the analysis, where the same error only shows up hours later and costs more. For registration it reads the barcode and also the cap colour, using a purpose-built spectrometer; the cap colour supports the identification, it does not replace it. How much ends up in the divert compartment is not a property of the device but a question of sample quality: how cleanly the labels sit and how correctly the samples arrive decides the amount. So we do not give a general rate – the lever for it sits at the start of the chain, with the labelling.

More on this: Product overview for this area.

What matters is the shape, not the brand: the bulk sorter handles common cylindrical primary tubes regardless of manufacturer and recognises them by sensor from their dimensions plus the cap colour – from the slim haematology and coagulation tubes to the large-volume ones for urine and special tests. The supported formats are listed in the technical specification of the ATRAS R4. A tube has to meet three conditions: it must be firmly closed, the cap must be made of rigid plastic (pure rubber caps are excluded), and it must keep its shape and be free of sticky residue. A badly fitted label disrupts transport inside the device. Anything that does not meet these conditions does not belong in the bulk input but at the manual workstation.

More on this: Product overview for this area.

The fallback is the manual workstation. With the LabConnect sorter middleware it is explicitly intended as the backup if the hardware has problems, so not an emergency fix that is only invented when it happens. What that means for your organisation depends on two things we do not promise across the board: your service contract with the manufacturer, and how many samples arrive in that time. Both belong in the discovery workshop, not in a general figure.

More on this: Overview of the STIWA modules.

There is a dedicated way into the device for that: the ATRAS R4 has a separate STAT input through which an urgent sample is fed in without queuing behind the bulk. Continuous centrifugation also works first-in, first-out with urgent samples moved forward as well. The hand movement stays with you – the route behind it is provided for and does not have to be organised every time.

More on this: Product overview for this area.

No – and that is the more honest part of the answer. Automation mainly cuts off the outliers: in one study the share of samples with a turnaround time of more than 60 minutes fell from 11 to 5 per cent. But if staffing or opening hours are the real bottleneck, automation does not smooth the peak; turnaround time at the peak can even rise. Where that is the case, no device helps, and we say so in the conversation.

Source: Dynamic load balancing / routing round congestion (middleware) ↗. Derivation and level of certainty under Sources & methodology.

No. The entries stay only in your browser, so that your choices are still there when you come back. There is no sign-up, no form that sends data to a server, and no cookies. The result document is also created on your device, not on a server. If you have agreed to the counting, all we learn is THAT the calculator was used, never what you entered or what result you got.

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Every value is shown with its source and level of certainty: validated for measured or customer data, plausible for values backed by the literature, assumption for figures from experience, and open where there is no basis. Figures from experience are explicitly marked as assumptions and not presented as evidenced. The full list, with how each value was derived, is under sources and methodology.

More on this: Sources & methodology.

No. What a system costs depends on how it is tailored: the building, the routing, the number of samples and the systems already in place. That is why there is no price here and no blanket payback period. The savings calculator only works out potential savings from your own figures, not purchase costs.