Sources & methodology
The savings calculator is deliberately cautious: every figure rests on published studies and specialist literature or on experience from comparable lab projects (so far mostly from German-speaking countries, with international projects being added all the time). What is an assumption is shown as an assumption. Your own figures replace the estimates in the Discovery workshop.
How the calculator works
The calculator looks at routine diagnostics: clinical chemistry and haematology. PCR and microbiology are not included; samples of this kind count as special material.
From everyday figures to the model
The Quick-Check’s opening questions ask about things you can see day to day – the share of samples without a pneumatic tube system, deliveries per day, cases and samples per day, the people at sample reception at peak times. The calculation still uses the model’s documented settings (rates and measured times); each answer is turned directly into the matching setting. For example, 30 sample–order mismatches a day with 3,000 samples is a mismatch rate of 1%, and “100% without a pneumatic tube system” simply means: there is none.
Only the question about people needs an assumption of its own: how much of the time present at peak hours is really manual registration and sorting work (experience value about 18%, adjustable in the Discovery workshop). The model values themselves can still be set directly on every area page in the expert view.
What the certainty levels mean
Every setting carries one of four labels in the calculator’s “i” button. It tells you how reliable the preset value is:
- validated
- Measured: the value comes from a field measurement or from the figures of a lab project, not from the literature.
- plausible
- Supported: a published study, a standard or a manufacturer document gives this value or the range it lies in; the source is in the list below.
- assumption
- Experience value: from comparable lab projects, without a study behind it. It sits at the lower end of what we have observed and is replaced by your figure in the Discovery workshop.
- still open
- No basis: a placeholder that we show openly instead of guessing it. It only becomes reliable with your figures.
Three savings without a literature value and what they deliberately leave out
For most figures in the calculator there are published studies; they are listed in the sources below. For the following three points there are none. So we treat them as experience values, set them at the lower end of what we have observed and adjust them with your figures in the Discovery workshop – instead of citing a study that measured something else.
Sample–order mismatches: sample without order, order without sample
Assumption: 1% of samples, 8 minutes of manual work per case, 60% of which the automatic matching resolves. All three are at the lower end of what has been reported.
Evidence: No study measures this case; the literature on incomplete requests measures something else (the form, not the matching).
Not counted: the wait for the referrer to call back, and anything already counted as a query or replacement material.
Guided archiving: pull instead of searching
Assumption: An add-on request costs 6 minutes today (lower end of the 5–15 range); with a known position, 1 minute is left.
Evidence: The only published figure (3.5 minutes) is an author’s estimate from a US hospital with an organised archive. In the calculator it is the share that the storage-location hint already covers.
Not counted: the gripper robot from the study (we do not sell it), the minute already saved elsewhere (it is deducted) and archive samples that went missing (not reliably recorded anywhere).
Night and weekend operation without anyone at reception
Assumption: 3 minutes of walking per delivery outside core hours, half of it a real saving; today the sample waits 20 minutes to be registered.
Evidence: There is evidence for the closed reception chain, but not for the walking and waiting times of a specific night shift. They depend on the floor plan.
Not counted: night-shift posts saved (your minimum staffing is your decision) and the sample’s waiting time as money.
What the technical terms mean
The words used on this website and in the calculator, each explained in one sentence, without jargon.
- Discovery
- The joint meeting after the Quick-Check: about two hours with your team, on site or online, in which we replace the calculator’s estimates with your own figures.
- HIS
- Hospital information system: the software in which a ward manages its patients and from which it places lab orders.
- LIS
- Laboratory information system: the software in which the lab manages its orders, samples and results.
- NC
- Nonconformity: a sample or order where something is not right – a missing label, missing details on the request form or the wrong tube.
- One-Touch
- The sample is handled only once: recording, sorting and passing it on happen in one go instead of in several separate steps.
- Order entry
- The step in which a lab order is created, usually before the sample arrives in the lab.
- Quick-Check
- The short self-test on this website: three figures about your lab, then four areas with three questions each. At the end you see what could be saved per year. No sign-up.
- Rip-and-replace
- Out with everything old, in with everything new: replacing an existing system completely instead of adding to it step by step.
- STAT
- An urgent sample, one that is moved to the front of the queue because the result is needed quickly, for example in A&E.
- TAT
- Turnaround time: on this website the time from the blood draw to the first result, so including transport and sample reception, not only from the moment the sample reaches the lab.
- TLA
- Total lab automation, the automated line in the lab: analysers connected by a conveyor that pass samples on without anyone handling them.
Sources
- Collective agreement for practice and laboratory staff, Upper Austria 2025
- Collective agreement for employees of doctors and laboratories, Upper Austria (“Kollektivvertrag für die Angestellten bei Ärzt:innen und in Laboratorien, Oberösterreich”, GPA), valid from 1 February 2025 – salary scale for occupational groups 1–3, infection allowance, surcharges for extra work and Sundays.https://www.gpa.at/kollektivvertrag/gesundheit-und-soziales/arztpraxen-labors
- Collective agreement for Austrian religious-order hospitals 2025
- Collective agreement for the employees of the Austrian religious-order hospitals (“Kollektivvertrag für die DienstnehmerInnen der Ordensspitäler Österreichs”), valid from 1 March 2025 – pay-group scale, night allowance (night duty 20:00–06:00) and Sunday allowance according to Annex XII.B.https://www.aekwien.at/documents/263869/280056/Kollektivvertrag%20Ordensspit%C3%A4ler%20ab%201.3.2025.pdf/0237f6b7-4b77-b533-8021-7ed6dd64d6de
- TVöD-K (VKA) pay table 2026
- Collective agreement for the German public service, hospital sector (TVöD-K, VKA) – pay table valid 1 May 2026 – 31 March 2027 (2025 pay settlement: +3% / at least €110 from 04/2025, +2.8% from 05/2026). Grading according to the VKA pay regulations, section on medical-technical assistants: MTL with consistently difficult tasks = E9a (the standard case in the laboratory, as also seen in real hospital job advertisements).https://www.oeffentlichen-dienst.de/entgelttabelle/vka/a/4410-vka-2026.html
- MFA pay agreement + BA pay atlas for MTL (Germany, private)
- Private-lab reference for Germany – there is NO published sector-wide collective agreement for private laboratories (Synlab/amedes in-house agreements without public tables; only key Synlab figures such as the 40-hour week and +1.7% from 05/2026 are documented). The assistant rate is therefore taken from the MFA pay agreement (medical assistants, AAA/vmf, 21 November 2024; table from 1 January 2026): activity group I, years 1–4 of employment €2,939.59 per month, the agreement’s own divisor 1/167 → €17.60/h. Lab technician (MTL) from the pay atlas of the Federal Employment Agency (occupation 8959, full-time, data as of 31 December 2024): lower quartile €3,361 per month ÷ (40 h × 4.348) = €19.33/h.https://web.arbeitsagentur.de/entgeltatlas/beruf/8959
- Zurich pay book / Bern hospitals’ collective agreement (Swiss hospitals)
- Hospital reference for Switzerland – pay book of the Canton of Zurich (“Lohnbuch”, Economic Affairs Directorate, 2025/2026 edition): biomedical analyst HF CHF 6,007.23 per month, laboratory assistant CHF 4,129.85 per month; each ×13 monthly salaries with a 42-hour week (collective agreement of the Bern hospitals and clinics (“GAV Berner Spitäler und Kliniken”), version from 1 April 2026, and Canton of Zurich staff law). Hourly wage = (month × 13 ÷ 12) ÷ (42 × 4.348): BMA CHF 35.64/h, laboratory assistant CHF 24.50/h. Conversion at the ECB reference rate of 24 July 2026 (CHF 1 = €1.075): lab technician €38.30/h, assistant €26.35/h.https://www.gav-service.ch/gav/903010/version/7/vertrag/12418
- Portal medians for BMA and assistants (Switzerland, private)
- Private-lab reference for Switzerland – Unilabs/Viollier/Synlab Suisse/Dr. Risch publish no pay tables, and there is no laboratory collective agreement. Lab technician (BMA): jobs.ch median CHF 79,300 per year (incl. 13th monthly salary, 908 salary entries, as of 07/2026), calculated conservatively on a 42-hour week → CHF 36.20/h = €38.90/h (with the 40-hour week documented at Unilabs it would be CHF 38.00/h). Assistant: cross-sector median for unskilled workers CHF 45,000 per year (lohnanalyse.ch) on a 40-hour week → CHF 21.65/h = €23.25/h. Rate: ECB reference 24 July 2026, CHF 1 = €1.075.https://www.jobs.ch/de/lohn/?canton=ch&term=biomedizinische%20analytikerin
- Employer social costs, Austria/Germany/Switzerland
- Employer social costs (employer contributions, without overhead): AT ~28–30% (AK OÖ / WKO / Patka 2025), DE ~21–22% (zep.de / Personio), CH ~15–22%, average 21.8% (Swissmem / SECO / BSV).https://ooe.arbeiterkammer.at/interessenvertretung/verteilungsgerechtigkeit/steuern/Lohnnebenkosten.html
- Employer social costs, international (Eurostat / OECD)
- Employer social costs outside AT/DE/CH, with the same definition as [LNK-DACH] (actual employer contributions + wage-related taxes − subsidies, relative to gross wages). Calculation rule on the Eurostat labour cost survey `lc_nstruc_r2` (size class GE10, NACE B-S_X_O): (D121 + D4 − D5) / D11. Values from the 2020 wave, as a percentage of gross wages: SE 40.5 · FR 36.6 · IT 35.2 · CZ 33.6 · SK 32.6 · ES 32.0 · EE 32.0 · AT 28.7 · BE 27.9 · EU-27 25.7 · LV 25.0 · IS 23.5 · GR 22.9 · DE 21.0 · PT 20.9 · NO 20.1 · FI 19.8 · CH 19.3 · PL 18.2 · NL 18.2 · CY 17.8 · HU 15.8 · BG 13.9 · SI 12.2 · LU 12.0 · DK 10.4 · HR 9.4 · IE 8.5 · RO 2.9. For countries without Eurostat data, OECD Taxing Wages as a substitute (employer contributions as a share of LABOUR COSTS, tax year 2025): JP 13.5 · UK 12.0 · NO 11.5 · CA 8.8 · US 7.5 · AU 5.7.https://ec.europa.eu/eurostat/databrowser/view/lc_nstruc_r2/default/table
- Tubes per order (tube utilisation)
- Duan X, Shao W, Jiang W, et al. – “Status of phlebotomy tube utilization at a major medical center. Are we using too many phlebotomy tubes?” (Heliyon 2023;9(5):e15334). Zhongshan Hospital, Fudan University, Shanghai; 1,408,175 orders from 984,078 patients, each Q4 2018–2021. Trimmed means (1% outlier cap) of tubes PER ORDER: overall 3.08–3.34; inpatient 4.24–4.73; intensive care 3.94–4.10; emergency department 2.80–3.25; outpatient 2.40–2.65. Range 1–26. “Order” = all tests requested by one doctor at the same time.https://pmc.ncbi.nlm.nih.gov/articles/PMC10149253/
- Literature on the share of STAT samples
- Lippi G, Plebani M – “Phlebotomy, stat testing and laboratory organization” (Clin Chem Lab Med 2012); PMC6416811 “Critical Issues and New Trends on Stat Tests”. Hospital STAT share: US median ~37% (52 laboratories), up to ~50%; ~30% is considered the tipping point; a large share is driven by logistics.https://pmc.ncbi.nlm.nih.gov/articles/PMC6416811/
- Annual working time per full-time post (IAB working-time accounts)
- Net annual working time of a full-time post: gross ~2,080 h (52 weeks × 40 h) minus holidays, public holidays, sickness, training and set-up/allowance times gives a productive net working time of about 1,500–1,700 h per year (common calculation value ~1,600 h). Officially backed by the IAB working-time accounts (Institute for Employment Research, series “Arbeitszeit Vollzeit, in Stunden”, quarterly values): for 2024 the four quarters add up to 1,588.5 h of hours actually worked per full-time employee (407.6 + 377.7 + 405.7 + 397.5). For context from the same accounts (press release of 4 March 2025): across ALL persons in employment including part-time, 1,332 h per head; across all employees, 1,294 h.https://iab.de/daten/iab-arbeitszeitrechnung/
- Getawa et al. 2022 [Q1]
- Getawa S, Aynalem M, Melku M, Adane T – “Blood specimen rejection rate in clinical laboratory: A systematic review and meta-analysis” (2022). Systematic review of 16.1m requests; pooled rejection rate 1.99%. Distribution of rejection reasons incl.: labelling errors 7.3%, unsuitable tube 2.6–10.8%, plus the quality reasons clotted, haemolysed and underfilled.
- Shalamar 2020 [Q2]
- PMC7109505 – Shalamar Medical & Dental College, 2020 – “Challenges in Preanalytical Phase: Rate of Blood Sample Nonconformity in a Tertiary Care Hospital”.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7109505/
- Phelan et al. 2016 – tube systems and haemolysis [Q3]
- PMC5017839 – Phelan MP, Reineks EZ, Schold JD, Hustey FM, Chamberlin J, Procop GW, 2016 – “Does Pneumatic Tube System Transport Contribute to Hemolysis in ED Blood Samples?” (West J Emerg Med). Result: 13.6% haemolysed samples after pneumatic tube transport versus 13.1% with hand transport, p = 0.90 – no statistical difference (n = 15,851 versus 92).https://pmc.ncbi.nlm.nih.gov/articles/PMC5017839/
- Black Book 2018 [Q8]
- Fierce Healthcare / Black Book Rankings, 2018.
- WBIT frequency (HSSIB / Bolton-Maggs) [WBIT-LIT]
- HSSIB – “Wrong patient details on blood sample” (Investigation Report) with Bolton-Maggs et al. 2015; confirmed by the UK National Comparative Audit of Blood Transfusion 2022. Difference by location: Emergency departments are higher-risk locations for WBIT errors (PubMed 34268775): ED WBIT 1.7× above wards, 5.1× above outpatient. “Wrong Blood In Tube” (WBIT) = blood of the wrong person in the tube, arising at sample collection. Evidence of the trend from the same UK audits: Booth C, Davies P – “Transfusion sample mislabelling and wrong blood in tube in the UK: Insights from the national comparative audits of blood transfusion in 2012 and 2022” (Transfusion Medicine 2025, doi 10.1111/tme.13092, PMID 39191512). In the survey month of October 2022, 179 sites reported 23,584 rejected samples – a rejection rate of 4.4% versus 2.99% in 2012 (+47%) – and 92 WBIT events, i.e. 1 per 5,882 samples versus 1 per 8,547 in 2012 (+45%).https://www.hssib.org.uk/patient-safety-investigations/wrong-patient-details-on-blood-sample/investigation-report/
- WBIT rate by place of draw (BEST Collaborative) [WBIT-ORT]
- Dunbar NM et al. – “Emergency departments are higher-risk locations for wrong blood in tube errors” (Transfusion 2021, PubMed 34268775). 143 WBIT among 1,394,862 samples from 39 transfusion services in nine countries, calendar year 2019.https://pubmed.ncbi.nlm.nih.gov/34268775/
- Scanning the wristband at the draw reduces WBIT (BEST Collaborative) [WBIT-EPI]
- Kaufman RM et al. – “Electronic patient identification for sample labeling reduces wrong blood in tube errors” (Transfusion 2019;59:972–980, PubMed 30549289). 20 hospitals, over 2.1m samples: 16 sites with manual patient identification (>1.6m samples) versus 4 sites that scan the wristband barcode before the draw (>0.5m samples), plus before/after at hospitals that switched.https://pubmed.ncbi.nlm.nih.gov/30549289/
- Al-Eshaq et al. 2023 – barcodes do not scan themselves [BARCODE-COMPLIANCE]
- Al-Eshaq DH et al. – “Patient and specimen identification in a tertiary care pediatric hospital: Barcodes do not scan themselves” (Transfusion 2023;63(7):1310–1317, doi 10.1111/trf.17399, PMID 37226989). Sidra Medicine, Qatar; 6,285 samples for blood grouping. Although scanners and barcodes were available in the hospital, patient AND sample were fully scanned in only 33.6% of draws; in 31.3% nothing was scanned at all, and in 32.3% only the sample label was scanned but not the patient wristband. Phlebotomists scanned fully much more often than nurses; the staff drawing blood named device problems and gaps in training as causes.https://pubmed.ncbi.nlm.nih.gov/37226989/
- Automatic labelling in a collection centre (Taiwan, 10 years) [LABELER-OPD]
- Ning HC, Lin CN, Chiu DTY, Chang YT, Wen CN, Peng SY, Chu TL, Yu HM, Wu TL – “Reduction in Hospital-Wide Clinical Laboratory Specimen Identification Errors following Process Interventions: A 10-Year Retrospective Observational Study” (PLoS ONE 2016). 3,800-bed hospital, about 30m samples 2005–2014, split into outpatient draw (OPD), emergency department and wards.https://pmc.ncbi.nlm.nih.gov/articles/PMC4975414/
- NESLI labelling robot – time per tube [LABEL-TIME-ROBOT]
- Demirci F – “Measuring the operational performance of an artificial intelligence-based blood tube-labeling robot, NESLI” (Am J Clin Pathol 2025;163(2):178–186, doi 10.1093/ajcp/aqae108). Simulated one-day operation based on twelve months of in-house data: 1,200 tubes from 330 orders plus 200 requests for non-standard tubes, adult blood collection at a single institution in Turkey, 16–18 May 2023. Median robot time per tube 8.96 s; this includes gripping the tube, printing and applying the label, and handing it out to the person drawing blood.https://doi.org/10.1093/ajcp/aqae108
- Share of pre-analytical errors (Plebani/Carraro; Lin 2025)
- Plebani M, Carraro P – “Mistakes in a stat laboratory: types and frequency” (Clin Chem 1997: 68.2% pre-analytical) and follow-up (Carraro & Plebani, Clin Chem 2007: 61.9%); confirmed by reviews (~60–70% of laboratory errors arise in the pre-analytical phase). Current large-scale evidence: Lin Y, Spies NC, Zohner K, McCoy D, Zaydman MA, Farnsworth CW – “Pre-analytical phase errors constitute the vast majority of errors in clinical laboratory testing” (Clin Chem Lab Med 2025;63(9):1709–1715, doi 10.1515/cclm-2025-0190, PMID 40311145). 16 months (January 2022 to May 2023) at a US university hospital (Washington University / Barnes-Jewish Hospital, St. Louis): about 11m samples with 37,680,242 billed results, including 87,317 documented errors (0.23% of results, 0.79% of samples). Of these, 85,894 pre-analytical (98.4%), 451 analytical (0.5%), 972 post-analytical (1.1%).https://pubmed.ncbi.nlm.nih.gov/9264270/
- Positive patient ID in phlebotomy [POC-PATID]
- “Reduction in Specimen Labeling Errors After Implementation of a Positive Patient Identification System in Phlebotomy” (Am J Clin Pathol 2010, 133:870). Barcode patient identification at the draw (instead of pre-printed labels) – also in the outpatient and collection-centre context.https://academic.oup.com/ajcp/article/133/6/870/1765950
- Pre-analytical errors by staff group [PREANALYTIC-STAFF]
- “Rates and Reasons of Laboratory Sample Rejection due to Pre-analytical Errors in Clinical Settings” (PubMed 35429958) and others: the pre-analytical error rate of non-laboratory phlebotomists is 2–4× higher than that of trained laboratory staff. Confirmed prospectively across several centres and extended upwards: Lippi G, Caola I, Cervellin G, Milanesi B, Morandini M, Giavarina D – “Error rates during blood collection in emergency departments and outpatient clinics: Results of a prospective multicenter study” (Clin Chim Acta 2015;445:91–92, PMID 25818240). Measured over three months on five pre-analytical quality indicators: underfilled and clotted samples 6–10× more frequent, identification errors and unsuitable tubes 2–3× more frequent than in outpatient clinics run directly by the laboratory.https://pubmed.ncbi.nlm.nih.gov/35429958/
- Haemolysis arises at the draw (LMBP meta-analysis)
- Heyer NJ, Derzon JH, Winges L et al. – “Effectiveness of practices to reduce blood sample hemolysis in EDs: a laboratory medicine best practices systematic review and meta-analysis” (Clin Biochem 2012;45(13–14):1012–1032, PMID 22968086). 16 included studies; ALL 11 comparisons of direct venepuncture against drawing from a freshly placed IV line find less haemolysis, pooled risk ratio 0.16 (95% CI 0.11–0.24) – i.e. about 84% less. Confirmed in more recent single studies: 7.3% versus 1.9% (Lee H et al., J Pers Med 2023;13(4):651, PMID 37109037), 5.6% versus 0.3% (J Emerg Nurs 2007).https://pmc.ncbi.nlm.nih.gov/articles/PMC4518461/
- Redraw cost per sample [WBIT-COST]
- J Clin Lab Anal 2019 (via MLO – “Recollecting blood specimens”): direct costs of a rejected sample that has to be drawn again – phlebotomy time, material, delayed result.https://www.mlo-online.com/information-technology/analytics/article/13009003/recollecting-blood-specimens
- Redraw versus report with comment (Karcher/Lehman 2014; Lippi & Simundic 2017)
- Handling rejected or quality-impaired samples – two practices: (a) redraw (recollection) as the analytically safest option, (b) report with a comment/disclaimer when a redraw is not possible. Peer-reviewed anchor: Karcher DS, Lehman CM – “Clinical consequences of specimen rejection: A College of American Pathologists Q-Probes analysis of 78 clinical laboratories” (Arch Pathol Lab Med 2014;138(8):1003–1008, PMID 25076290); prospective recording of consecutive rejected blood and urine samples in 78 laboratories. Finding: rejection mostly leads to a redraw, delays the result by a median of 65 minutes and in a considerable share of cases means the test is not performed at all; relabelling mislabelled samples achieved little and went along with a considerable share of samples mislabelled again. Rejection rates by setting: inpatient 1.0% / outpatient 0.35% / emergency 1.97% (Stark et al. 2007, about 1.4m samples, reported via MLO “Recollecting blood specimens”). Lippi & Simundic 2017 (PubMed 28207411): a redraw is safest, but in outpatient settings often impossible → report-with-comment algorithms.https://pubmed.ncbi.nlm.nih.gov/25076290/
- Barcode + order entry against labelling errors (Simpson 2001)
- Simpson 2001, reported via AcuteCareTesting and ADLM/AACC (Patient Safety Focus – Mislabeled Specimens): a combined barcode and order-entry system reduced labelling errors by 41%. Context: mislabelling at sample reception industry-wide ~0.2% (4.4 sigma) to ~0.3% (3,000 per million); costs per case USD 500–712.https://acutecaretesting.org/en/articles/specimen-mislabeling-a-significant-and-costly-cause-of-potentially-serious-medical-errors
- Samples-to-wards ratio (lit.)
- Deriving the number of sample-collecting areas from sample volume: ~1 nursing/functional unit per 20 beds (WHO Minimum Requirements for Health Service Delivery); ~9.67 laboratory tests per occupied bed day, CBC ~1.07 (StatPearls NBK570615); academic 3,800-bed hospital ~10,300 samples/day ≈ 2.7 samples/bed/day (lab utilisation study PMC9381313).https://www.ncbi.nlm.nih.gov/books/NBK570615/
- Automatic unloading station (Aerocom)
- Aerocom Automatic Unloading Stations / Quirepace Automatic Carrier Unloading: automatic receiving, opening and emptying of pneumatic tube carriers at the laboratory end; according to the manufacturer up to 50% higher efficiency in carrier handling and no more repetitive strain. Can only be connected to an Aerocom pneumatic tube system.https://www.aerocom.co.uk/products/lab-automation-systems/auto-unloading-stations/
- Märtens et al. 2022 – a tube-system carrier that can be unloaded automatically [AUS-CARRIER-LIT]
- Märtens CM et al. – “Evaluation of a pneumatic tube system carrier prototype with fixing mechanism allowing for automated unloading” (Clin Chem Lab Med 2022;60(8):1202–1210, doi 10.1515/cclm-2022-0193, PMID 35635785). Greifswald University Medicine with a carrier prototype from Aerocom (Schwäbisch Gmünd): the carrier holds nine tubes in place when the lid is closed, which makes automated unloading possible. 35 volunteers, triple sets (lithium heparin, EDTA, citrate) split across three modes of transport – porter, standard carrier AD160 and prototype – then 51 analytes from clinical chemistry, haematology and coagulation compared: 49 of the 51 analytes showed good agreement, especially between the standard carrier and the prototype. The authors’ conclusion: suitable for transporting diagnostic blood samples, with less hands-on time on the ward and in the lab and a lower risk of incorrectly packed carriers.https://doi.org/10.1515/cclm-2022-0193
- Automated delivery / TLA (lit.)
- Closed sample reception: an innovative pneumatic tube system delivers samples directly into the bulk loader of the laboratory automation (“closed-loop specimen reception and sorting”), manufacturer-independent, without cartridges (Suchsland et al., Clin Chem Lab Med 2017;55(2):225–231, doi 10.1515/cclm-2016-0380, see [PTS-TRANSPORT]; single-tube PTS, PMC12929093). Effect of a fully automated line, measured with time-and-motion studies before and after introduction (Yu HE, Lanzoni H et al., Laboratory Medicine 2019;50(1):96–102, PMID 29982789): −22 person-hours of hands-on time per day across chemistry, haematology, coagulation, hepatitis, HbA1c and add-on requests (Table 2: 22.0 h, or USD 232,650 wage equivalent per year), in the authors’ words almost the work of 3 full-time posts; −82% hands-on time in the add-on request processes; −2.5 full-time posts among testing staff through analyser consolidation; −86% individual processing steps; −45% floor space.https://www.degruyterbrill.com/document/doi/10.1515/cclm-2016-0380/html
- Kim et al. 2022 – the economics of a laboratory line [TLA-ECON]
- Kim KY, Lee S-G, Kim TH, Lee SG – “Economic Evaluation of Total Laboratory Automation in the Clinical Laboratory of a Tertiary Care Hospital” (Ann Lab Med 2022;42(1):89–95, doi 10.3343/alm.2022.42.1.89, PMID 34374353, PMC8368223). Severance Hospital, Yonsei University, Seoul; 2,500 beds, over 1m clinical chemistry and immunoassay tests per month. After introduction of the laboratory line: mean turnaround time −6.1%, 99th percentile of turnaround time −13.3%, coefficient of variation of turnaround time −70.0%; cumulative staff cost saving of USD 1,880k by the end of 2025, payback of the investment through staff costs alone after 4.75 years; a reduction of about 2.5–3.0 full-time posts by 2020.https://pmc.ncbi.nlm.nih.gov/articles/PMC8368223/
- Tube-system transport time (lit.)
- Pneumatic tube system vs. manual transport: Fenton & Klein 2005 (PubMed 16580476) – PTS lowers TAT without loss of quality; Yu J et al. 2024, Heliyon (PMC11141344) – manual delivery by porter 1,711 ± 78 s (~28.5 min) versus Swisslog pneumatic tube 147 ± 2 s (~2.4 min) and Tempus600 58 ± 2 s (~1 min), with equivalent sample quality; meta-analysis of PTS routine parameters (cclm-2017-0008). DACH evidence: Suchsland J, Winter T, Greiser A, Streichert T, Otto B, Mayerle J, Runge S, Kallner A, Nauck M, Petersmann A – “Extending laboratory automation to the wards: effect of an innovative pneumatic tube system on diagnostic samples and transport time” (Clin Chem Lab Med 2017;55(2):225–231, doi 10.1515/cclm-2016-0380). Greifswald University Medicine, Tempus600: a 300 m route in under 30 seconds with no adverse effect on the samples; the overall turnaround time fell from 2–3 hours to under 60 minutes.https://pubmed.ncbi.nlm.nih.gov/16580476/
- Tube-system planning: construction time and sizing (official)
- Two official planning sources. (1) CONSTRUCTION TIME in existing buildings, from EU tender notices: TED 343020-2026 (Staatliches Bauamt München 2 for Klinikum rechts der Isar, contract awarded 18 May 2026 to PTS tec GmbH) – renewal of all control, regulation and mechanical components of the EXISTING system, reusing the existing tubes and control lines; 194 send and receive stations, 91 diverters, 4 central distributors, approx. 645 m of transport tube; execution period 11 May 2026 to 3 September 2027, i.e. about 15.8 months; contract value €1,385,556.78. Smaller comparison case: TED 322451-2020 (München Klinik gGmbH, Bogenhausen) – existing system extended and connected to the pneumatic tube system of the new extension building, 1 central unit, 1,200 m of tube, 20 stations, duration 100 days. (2) SIZING: US Department of Veterans Affairs, PG 18-10 “Pneumatic Tube System Design Manual”, as of 1 May 2023, §1.0 – literally, no relationship can be established between a facility’s number of beds and its need for a pneumatic tube system; a system has to be justified economically through a life-cycle cost calculation in each individual case. As a practical station criterion the manual names a walking time of over 15 minutes; laboratory and pharmacy account for 75–85% of use there.https://ted.europa.eu/de/notice/-/detail/343020-2026
- TriCollect (T&O LabSystems Sp. z o.o., Poland) + customer laboratory in Ludwigsburg
- TriCollect – reusable box-in-box collection and transport system (rack box + collection box + transport box) from referrer to laboratory, compliant with packing instruction P650 (UN 3373). Bulk delivery that is fed directly into the ATRAS bulk sorter at reception. Since 1 September 2025 sales and further development have been with T&O LabSystems Sp. z o.o. (Piła, Poland) – a different company from the system partner T&O LabSystems GmbH & Co. KG (Kaltenkirchen, Germany), which makes ATRAS, RS2, CSpin and InTrac. Capacity according to the manufacturer: “one rack box is designed for 30 tubes”, “one transport box holds 500 to 600 tubes”; over 160 referrers of the LaborUnion work with it. Customer statement from MVZ Labor Ludwigsburg (Dr. N. Stührwohldt): “at least 25 minutes saved, samples in analysis a few minutes after arrival” – about 23 minutes per batch in the customer story video.https://www.tricollect.de/
- Bhatt et al. 2019 [Q7]
- PMC6416806 – Bhatt RD et al., 2019 – “Factors affecting turnaround time in the clinical laboratory of Kathmandu University Hospital.” EJIFCC 30:14–24.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416806/
- STAT prioritisation / triage and TAT
- Structured STAT triage/prioritisation as a recognised TAT lever of the pre-analytical phase. Peer-reviewed: Zhang L, Liu ZH, Lv YJ et al. – “Comprehensive improvements in the emergency laboratory test process based on information technology” (BMC Med Inform Decis Mak 2023;23:292, doi 10.1186/s12911-023-02387-x, PMID 38115101). After the IT-supported redesign of the emergency laboratory process, the median reporting time fell from 30 to 25 minutes, and compliance with the time target rose from 98.77 to 99.03%. Field report in the same direction: SHS/IISE “Reduction in Turnaround Time for STAT Specimen” – pre-analytical time −34%, 29 → 19 minutes.https://pmc.ncbi.nlm.nih.gov/articles/PMC10729567/
- Dynamic load balancing / routing round congestion (middleware)
- Laboratory middleware dynamically redirects samples from a busy analyser to a free one (redirect rate = effective throughput − allocation rate, incl. transport time to the alternative station) – Roche patent specifications “Method of operating an analytical laboratory” (US 11313870 / 11860176). Effective above all at peak times; the following values are a MANUFACTURER STATEMENT from Beckman Coulter on the DxA 5000 (single core laboratory, measured in the peak hours 12:30–16:30) and not an independently published study: STAT TAT −61%, citrate −53%, routine serum −12%, “last sample of the day” 80 → under 60 min (−38%). Independently published and peer-reviewed alongside it is [TLA-TAT-PEER] (Tanasijevic 2021: median chemistry TAT −25 to −27%, add-on requests 66 → 28 min) – though on a Roche line, not on the DxA 5000. Automation above all cuts the TAT OUTLIERS (Angeletti et al., J Lab Autom 2015: outliers over 60 min 11 → 5%; the same direction with a −70% coefficient of variation in [TLA-ECON]). TLA workforce study: ~30% fewer staff despite +27% volume (PMC9109973).https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11313870
- ISO 15189 (medical laboratories)
- ISO 15189:2022 – Medical laboratories: Requirements for quality and competence. TAT targets according to clinical need (reporting clause) + risk management incl. for TAT/patient safety; urgent samples (vital/statim) must be recognised without delay and handled with priority.https://en.wikipedia.org/wiki/ISO_15189
- Incomplete request forms (lit.)
- Incomplete or incorrect laboratory request forms are an established pre-analytical source of error (overview: “Preanalytical Errors in Clinical Laboratory Testing at a Glance”, PMC10981510). Reported rates of incompleteness vary widely by setting – single studies ~14–39%, in low-resource hospitals up to >80% of forms with at least one missing mandatory item.https://pmc.ncbi.nlm.nih.gov/articles/PMC10981510/
- Paper form versus electronic request [OE-PAPER-LIT]
- Al Dogether M, Al Muallem Y, Househ M, Saddik B, Khalifa M – “The impact of automating laboratory request forms on the quality of healthcare services” (J Infect Public Health 2016;9(6):767–773, PMID 27670682). King Abdulaziz Medical City, Riyadh (Saudi Arabia), outpatient laboratory requests: 25% of the paper forms (57 forms) were incomplete, and not a single one of the electronic requests – there, all fields are mandatory. Legibility and clarity came out similarly: only 11.4% of the paper forms were fully clear, 33.8% legible, 54.8% unclear; among the electronic requests none was unclear.https://pubmed.ncbi.nlm.nih.gov/27670682/
- Nelson et al. 2015 – add-on testing (BMC Clin Pathol)
- Nelson LS, Davis SR, Humble RM, Kulhavy J, Aman DR, Krasowski MD – “Impact of add-on laboratory testing at an academic medical center: a five year retrospective study” (BMC Clinical Pathology 2015;15:11). 730-bed university hospital in Iowa (USA), 880,359 add-on requests (add-on tests) over 5.5 years. Add-on share 3.3% of test volume; 87.3% of add-on requests within 8 h, 96.8% within 24 h (by then the sample is already in the archive/fridge). Manual effort “from the moment the add-on is printed … to the time the sample is loaded on the proper analyzer averaged approximately 3.5 minutes” before a robotic archive/retrieval unit (Roche p701) was introduced, and 45 s afterwards → 2.75 min saved per add-on request, ~24.1 h per day.https://pmc.ncbi.nlm.nih.gov/articles/PMC4458334/
- García-Osuna et al. 2023 – add-on requests in a European core laboratory [ADDON-RATE-EU]
- García-Osuna Á, Guiñón Muñoz L, Costa Pallaruelo M, Mansilla Usero A, Cuevas Eduardo B, Llanos Ramos J et al. – “Characterization of add-on testing before and after automation at a core laboratory” (Heliyon 2023;9(11):e22096, doi 10.1016/j.heliyon.2023.e22096, PMID 38034602). Hospital de la Santa Creu i Sant Pau, Barcelona; two comparison months (November 2021 before, November 2022 after automation). Add-on requests: 1,345 of 25,949 orders (5.18%) and 1,119 of 26,445 orders (4.23%) respectively; at test level 2,904 tests (0.83% of all tests performed) and 2,494 tests (0.63%). Median turnaround time of an add-on request 52 → 30 min (−42.3%), together about 15 working hours per day.https://pmc.ncbi.nlm.nih.gov/articles/PMC10682109/
- Perrotta et al. 2020 – share of aliquoting (CAP Q-Probes)
- Perrotta PL, Novis DA, Nelson S, et al. – “Workflow Mapping: A Q-Probes Study of Preanalytic Testing Processes: A College of American Pathologists Q-Probes Study of 35 Clinical Laboratories” (Arch Pathol Lab Med 2020;144(12):1517–1524). Process mapping of 20 chemistry samples each in 35 US laboratories: 13.4% of routine and 11.5% of STAT chemistry samples went through an aliquoting step (route sample reception → chemistry analyser).https://pmc.ncbi.nlm.nih.gov/articles/PMC7720245/
- Bravo Ayuso et al. 2008 – fewer aliquots through routing
- Bravo Ayuso B, López Martínez R, et al. – “Estudio del tiempo de procesamiento de un sistema preanalítico en un laboratorio de atención primaria” (Revista del Laboratorio Clínico 2008). Roche Modular Pre-Analytics, primary care laboratory: baseline ~0.95 aliquots per serum sample; regrouping the analyser targets (routing) gives 11.2–18.3% fewer aliquots with ~18% shorter TAT.https://www.elsevier.es/es-revista-revista-del-laboratorio-clinico-282-articulo-estudio-del-tiempo-procesamiento-un-S1888400808000366
- Aliquoting material costs (laboratory supplier list prices) + hands-on time
- Material costs per aliquot from DACH laboratory supplier list prices (Carl Roth, net, as of 2026-07): sample tube 5 ml PP ~€0.025, stopper/cap ~€0.015, label ~€0.005–0.01 → together ~€0.05 per aliquot. Hands-on time per aliquot (pipetting/labelling/capping/sorting) ~19–30 s from a research biobank time study (Pokrovskaya et al. 2022, cryotubes/Tecan).https://www.carlroth.com/de/de/probenroehrchen/probenroehrchen-polypropylen/p/1e8y.1
- Automatic tube sorting (lit.)
- Automation of sample sorting/registration: manual pre-analytical error rate ~0.44%; after an automatic tube sorter was introduced, rejected samples fell from 0.4% to 0.2% and tests not performed from 4.5% to 1.4% (PMC5346795); error reduction through automation > 70%.https://pmc.ncbi.nlm.nih.gov/articles/PMC5346795/
- Pre-sorters on the European market (manufacturer figures)
- Functional scope and peak throughput of the pre-analytical sorters common in Europe, from the manufacturers’ product pages and data sheets: ASP Lab Automation SortPro (~3,600 samples/h, bulk input, registration + sorting) · T&O LabSystems ATRAS (~3,000 samples/h; TS up to 1,300 – manufacturer information 08/2026, RS2 module 1,300–1,500, CSpin module ~500 per module) · SARSTEDT BL 1200 Bulk Loader (1,200 samples/h, with gel check) and DC/RC 900 Flex (700–900 samples/h, sorting + decapping/recapping, 11–16 mm) · Beckman Coulter AutoMate 2500, formerly OLA 2500 (1,200 samples/h, rack-based, with decapper) and AutoMate 2550 (900 primary samples/h with aliquoting) · Roche cobas p 512/p 612 from the PVT series (up to 1,400 samples/h, aliquoting only on p 612, up to ~300 aliquots/h) · Line input modules: Inpeco FlexLab IOX (~1,000 tubes/h, also on the market as Siemens Aptio/FlexLab X and Grifols FlexLab) and Abbott ACCELERATOR a3600 (up to 3,600 samples/h, from Hamburg-based GLP systems). Also in the field, but not a bulk sorter: Sysmex TS-01/TS-10 (~660 samples/h, rack-based, pre- and post-analytical).https://www.asplabauto.com/en/products/sortpro-tubesorter-bulksorter/
- ADLM/CLN 2020 – Total Laboratory Automation: Samples on Track [CLOSED-TUBE-TLA]
- Nichols JH (ed.) / Clinical Laboratory News – “Total Laboratory Automation: Samples on Track” (Clinical Laboratory News, ADLM/AACC, December 2020). Overview article on how laboratory lines are built: describes the module chain of a TLA – decapper before analysis, aliquoting, transport of the open tubes on the track and a recapper before refrigerated storage; closed-tube sampling is presented as a feature of haematology analysers, whereas serum/plasma for chemistry and immunoassay is processed decapped.https://myadlm.org/cln/articles/2020/december/total-laboratory-automation-samples-on-track
- CLSI GP44-A4 / PRE04 (sample stability)
- CLSI GP44-A4 or its successor document PRE04 – Procedures for the Handling and Processing of Blood Specimens for Common Laboratory Tests: serum or plasma should be separated from the blood cells (centrifuged) within 2 hours of the draw. In addition on analyte stability: potassium stable for ~4 h at room temperature (PMC6807160); review Hedayati et al. 2020, J Clin Lab Anal.https://clsi.org/shop/standards/pre04/
- TAT benchmark [Q6]
- PMC2994570 – “Turn Around Time (TAT) as a Benchmark of Laboratory Performance”.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2994570/
- Tanasijevic et al. 2021 – automation and turnaround time (peer-reviewed) [TLA-TAT-PEER]
- Tanasijevic MJ, Melanson SEF, Tolan NV et al. – “Significant Operational Improvements with Implementation of Next Generation Laboratory Automation” (Laboratory Medicine 2021;52(4):329–337, doi 10.1093/labmed/lmaa108, PMID 33438745). Brigham and Women’s Hospital, Boston: an older pre-analytical line replaced by a Roche cobas 8100 line on cobas 8000 analysers and Stago STA R Max. Median turnaround time in clinical chemistry −25% (emergency department) and −27% (inpatient); coagulation (PT/INR) 29 → 25 min; add-on requests 66 → 28 minutes.https://doi.org/10.1093/labmed/lmaa108
- CAP Q-Probes TAT benchmarks
- College of American Pathologists Q-Probes – laboratory TAT benchmarks: early-morning draw, 657 institutions (delivery 25 / analytic 42 / total 73 min; PubMed 9786345); ED potassium TAT median ~36 min & clinician target 30 min (722 inst.; PubMed 8418756); routine outpatient TAT (PubMed 11800641).https://pubmed.ncbi.nlm.nih.gov/9786345/
- Fei 2015 / Zhang 2018 – intra-laboratory TAT (a DIFFERENT reference point from our anchor)
- Two national surveys from China on turnaround time in the laboratory. (1) Fei Y, Zeng R, Wang W, He F, Zhong K, Wang Z – “National survey on intra-laboratory turnaround time for some most common routine and stat laboratory analyses in 479 laboratories in China” (Biochem Med (Zagreb) 2015;25(2):213–221, doi 10.11613/BM.2015.021, PMID 26110033). Measured interval, verbatim: “time taken from the receipt of a specimen in the laboratory to the time of reporting of the test result” – sample reception → result release. Medians potassium routine 136.0 / STAT 43.0 min (10th–90th percentile routine 51.2–349.0); leucocytes 44.7 / 20.0; prothrombin time 85.0 / 40.0; blood gas pH 15.5 / 14.3. (2) Zhang X, Fei Y, Wang W et al. – “National survey on turnaround time of clinical biochemistry tests in 738 laboratories in China” (J Clin Lab Anal 2018;32(2):e22251, doi 10.1002/jcla.22251, PMID 28493522). Interval split into three parts (pre-examination = draw → reception, examination = reception → result, post-examination = result → clinician). Medians potassium routine 52 / 88 / 0, STAT 20 / 35 / 0 min; troponin routine 42 / 60 / 0, STAT 20 / 40 / 0.https://pubmed.ncbi.nlm.nih.gov/26110033/
- TAT phase times (analyser/centrifuge/autovalidation/transport)
- Literature on phase times: analyser run time “time to first result” Siemens Atellica ~9, Abbott Alinity ci ~10, ARCHITECT ci ~15 min (clinical chemistry/ISE), Sysmex XN-1000 100 samples/h (CBC ~3 min); centrifugation spin ~10 min (rapid protocol 5–7 min @3000 g; PMC academic.oup labmed 38/3); autovalidation TAT −19–33%, ~75% released automatically; pneumatic tube system vs. porter −8–10 min (PubMed 16580476).https://academic.oup.com/labmed/article-pdf/38/3/172/24960025/labmed38-0172.pdf
- Troponin TAT target ≤60 min (ESC/IFCC)
- ESC guidelines for acute coronary syndrome without ST elevation (2020/2023) and IFCC/AACC recommendations: high-sensitivity cardiac troponin with 0/1-h or 0/2-h algorithms requires a laboratory TAT (blood draw → result) of ≤60 min where possible; the measurement itself takes ~9–20 min depending on the platform.https://www.escardio.org/Guidelines
- Route and collection optimisation in sample logistics (lit.)
- Collected evidence on optimised sample collection and route planning: Benini, Detti & Zabalo Manrique de Lara 2021 (arXiv:2104.09275, real data from Bologna) – route optimisation cuts late deliveries from ~40% to 0%; Girdwood et al. 2022 (Afr J Lab Med 11(1):1725) – later/staggered collection → +6–13% same-day access, only 1.3% cheaper (the value lies in time, not cost); midnight/later-draw studies (Am J Clin Pathol 2014, 141(6):805) – staggered draws shift the morning peak from 55% to 39% in the 4–8 am window.https://arxiv.org/abs/2104.09275
- RFID/barcode stock management in the laboratory (state of evidence)
- Collected evidence on RFID- and barcode-supported reagent and stock management in the medical laboratory: BMBF project ReaTrace (“Nutzbarmachung der RFID-Technologie für das Reagenzienmanagement im medizinischen Labor” – making RFID technology usable for reagent management in the medical laboratory; KMU-innovativ, partners incl. DiaSys Diagnostic Systems GmbH and Städtisches Klinikum Karlsruhe) – a real, publicly funded project in a German clinical chemistry laboratory that set only qualitative goals (material movements without media breaks, less spoilage) and left no public figure on expiry or stock. Yamashita F, Watanabe T – “Development and free distribution of a reagent management system for laboratory operations” (English rendering of the Japanese title; 医学検査 / Jpn J Med Technol 2020;69(2):198–204; GS1-128-based recording of expiry dates and lots) documents the topic in the peer-reviewed laboratory literature, but likewise gives no figure on expiry, discards or costs.https://www.jstage.jst.go.jp/article/jamt/69/2/69_19-83/_article/-char/en
- IFCC WG-LEPS 2017 – samples that never arrived
- Sciacovelli L, Lippi G, Sumarac Z, et al. – “Quality Indicators in Laboratory Medicine: the status of the progress of IFCC Working Group “Laboratory Errors and Patient Safety” project” (Clin Chem Lab Med 2017;55(3):348–357, DOI 10.1515/cclm-2016-0929). Table 1, indicator Pre-NotRec = number of samples not received ÷ total number of samples, 25th/50th/75th percentile: 2014 0.06 / 0.261 / 1.123% · 2015 0.0875 / 0.493 / 1.089% · 2016 (6 months) 0.2175 / 0.6995 / 1.020%. 59 laboratories from 14 countries (Serbia 19, Italy 16, Croatia 6 … Germany 1, Austria 1, Switzerland 2), no industry funding. Supporting value: Caballero A, et al., Adv Lab Med 2022 (SEQCML EQA, 72 Spanish laboratories) – median not received: serum 0.210%, EDTA 0.266%, urine 0.877%.https://doi.org/10.1515/cclm-2016-0929
60 sources · Last updated: October 2026