Cost per Test KPI

Cost per Test (CPT) is a crucial financial ratio that directly impacts operational efficiency and profitability.

It serves as a leading indicator of resource allocation effectiveness, influencing cost control metrics and overall financial health.

By optimizing CPT, organizations can improve forecasting accuracy and enhance strategic alignment with business objectives.

This KPI also aids in benchmarking against industry standards, providing analytical insights that drive data-driven decisions.

A lower CPT can lead to better ROI metrics, freeing up capital for innovation and growth initiatives.

Ultimately, managing this metric effectively can lead to significant improvements in business outcomes.

How Cost per Test Connects to Your Strategy

Cost per Test sits in KPI Depot's ISO 15189 KPI group, the metric set built around the accreditation requirements for medical laboratories. The metrics that group leads with are all process metrics: Turnaround Time, Critical Results Reporting Time, Test Turnaround Time (TAT) and Critical Value Reporting Timeliness at the head of the priority order, then Patient Identification Accuracy Rate, Patient Report Error Rate, Pre-analytical Error Rate and Post-Analytical Error Rate.

Cost per Test ranks far below all of those, well down a priority order that runs across dozens of members. It is a supporting metric in this KPI group rather than a headline one, and the ordering is deliberate rather than an oversight: an accredited laboratory is judged first on whether a result is correct, fast and attached to the right patient, and only after that on what producing it cost.

Its balanced scorecard placement is financial, which makes it the odd one out among the group's lead metrics, every one of which sits in the internal process perspective. The placement also tells you how to read it. Cost per Test is lagging. It reports the financial consequence of decisions already taken on staffing levels, platform choice, batching policy and repeat testing, and it moves after the process metrics move, not before.

The direct tension in this KPI group is with Turnaround Time and Test Turnaround Time (TAT). The cheapest way to run a laboratory test is to wait until there are enough samples to fill a run, so that calibration, controls, setup labour and a whole plate or cartridge are shared across as many samples as the run will hold. The fastest way to run a test is not to wait. Every priority assay pulled forward out of its batch, every extra evening run opened to clear a backlog, raises the cost of that individual test while the laboratory is doing precisely what the group's two highest priority metrics ask of it. Read Cost per Test without turnaround beside it and a service improvement presents itself as a cost failure.

A slower loop runs through Pre-analytical Error Rate. Saving money at the collection end, thinner phlebotomy cover, less frequent training, cheaper specimen transport, does not touch Cost per Test in the period the saving is made. It surfaces later as rejected samples and recollections, and each of those consumes reagent, labour and instrument time to produce nothing a clinician can act on, which pushes Cost per Test back up a quarter or two after the saving was booked.

Measuring Cost per Test in Practice

The formula, total testing costs over total tests performed, looks like arithmetic and is actually two unsettled definitions. Both have to be decided in writing before the figure belongs in a report, because either one can move it more than any real change in laboratory efficiency.

The numerator: what counts as a testing cost. The narrow reading is consumables and direct analytical labour, so reagents, calibrators, controls, tips and tubes, plus the hands-on time of the technologist who runs the sample. The loaded reading adds instrument depreciation or the equipment component of a reagent rental agreement, service and calibration contracts, quality control and proficiency testing materials, the competency assessment and accreditation program that ISO 15189 itself requires, laboratory information system licensing, courier and specimen transport, allocated facility cost, and the cost of repeat testing and amended reports. These are not two variants of one metric. They are different metrics that share a name, and a laboratory comparing its narrow figure against someone else's loaded figure is not benchmarking at all. Publish the inclusion list next to the number every time, without exception.

Two boundary calls deserve explicit decisions because they are where most of the disagreement hides. Send-out and referred testing: the reference laboratory's invoice is a real cost, but if those tests are stripped out of the count while their fees stay in the numerator, the in-house figure inflates for no reason. And rework: repeat runs, dilutions, confirmations and reruns after a control failure are the easiest costs to leave out and the most informative ones to leave in, because rework is the part of the cost base that quality problems actually move.

The denominator: tests attempted, or results someone can act on. Failed runs, repeats, calibrators, control material and proficiency samples all consume cost and produce nothing countable. Count only valid reportable results and the metric correctly absorbs the cost of failure, so it rises when analytical quality falls. Count everything started and failures dilute the unit cost, which lets a bad month read as a cheap one. Neither choice is wrong, but they answer different questions and cannot be mixed across periods. The panel question is separate and just as large: a chemistry profile, a coagulation screen or a molecular respiratory panel can be counted as one test, as one test per analyte, or as billable units under a coding schedule, and those counts differ by a wide multiple for identical work. Reflex and add-on tests triggered by a first result compound it, as does the choice between cost per test and cost per accession, since one requisition may carry many tests.

Volume flatters this metric, and that is its worst failure mode. Most of the cost base is fixed within any reporting period: staff on shift, instruments on the floor, the facility, the service contracts. Divide a largely fixed cost by a larger test count and the unit cost falls with nothing having improved. A laboratory that won a new outreach contract will post a gain it did not earn, and one that lost referral volume will post a deterioration it did not cause. Before reading any movement as performance, check volume over the same period, and report Cost per Test next to total cost and total test count so a customer can see which of the three actually moved.

Batching sets a floor the average hides. Run level costs do not scale with the samples in the run. Calibration, control material, plate or cartridge consumption and setup labour are incurred per run, so a lightly loaded run costs close to what a full one costs and carries a much higher cost per test. Reagent kits come in fixed lot sizes, and open vial stability means material discarded on expiry after a quiet week is cost with no test attached to it. A laboratory can improve this metric substantially by changing nothing except its run scheduling, which is a genuine gain, but it is a scheduling gain and should be described as one.

A blended figure is a mix statistic first. Routine chemistry and haematology are inexpensive per test and high in volume; molecular assays, mass spectrometry, genetic testing and specialised microbiology are expensive per test and low in volume. Move the case mix slightly toward the expensive end and the blended number rises while every individual assay holds exactly where it was. Any conclusion from a blended figure needs the mix decomposition behind it: cost per test within each assay or each section, and a version held at constant mix, is what shows whether the laboratory became more efficient or simply received different work.

Where the data lives, and how to join it. Three systems hold the pieces and none of them was built to be joined to the others. The laboratory information system holds the test level record, so accession, ordered test codes, result and cancellation status, repeats, section and instrument. The general ledger holds cost by cost centre and account on an accounting calendar. Consumables sit in inventory or purchasing records as receipts and issues against catalogue items, and labour sits in payroll or rostering. The join is a documented crosswalk from cost centres and accounts to laboratory sections and instruments, built once, version controlled, and reviewed whenever the chart of accounts changes. Shared cost centres, phlebotomy, specimen reception, the courier round, need an allocation basis that is written down and stated wherever the metric is published, because an unstated allocation is the most common reason two sections in the same laboratory cannot compare their figures.

The timing mismatch between the ledger and the bench needs its own handling. A bulk reagent order is booked when it is purchased and consumed across the following months. Annual service, calibration and accreditation fees land in a single period. Depreciation follows a schedule with no relationship to activity. Use consumption from inventory issues rather than purchases wherever the records support it; where they do not, average over a window long enough for the lumps to cancel, and never compare a month that happened to contain a contract renewal with one that did not. Cut the cost period and the test count on the same boundary, and settle in advance how a test ordered near a period end and resulted after it is treated on both sides of the fraction.

Segmentation. Assay and section come first, then platform, then in-house against referred, then routine against priority and out of hours work, then site for a multi-site network. A single laboratory-wide figure is useful for a budget conversation and close to useless for an improvement conversation. Two further forks matter when an external figure is in play: the period, since monthly numbers are dominated by accounting lumps while rolling or quarterly ones are steadier but hide seasonality, and the geography and year, since labour rates, reagent pricing and the local definition of a billable test move this metric further than laboratory performance does.

Common Pitfalls

Many organizations overlook the nuances of Cost per Test, leading to misguided strategies that can inflate costs unnecessarily.

• Failing to standardize testing procedures can result in inconsistent costs across projects. Variability in methods leads to confusion and complicates accurate measurement, skewing results.
• Neglecting to track indirect costs associated with testing can distort the true CPT. Hidden expenses, such as labor or equipment depreciation, often go unaccounted for, leading to inflated figures.
• Overemphasizing speed over quality can increase costs in the long run. Rushed testing often leads to rework and higher failure rates, negating initial savings.
• Ignoring feedback from testing teams can perpetuate inefficiencies. Without insights from those directly involved, organizations miss opportunities to refine processes and reduce costs.

Improvement Levers

Reducing Cost per Test requires a focus on process optimization and resource management.

• Implement automated testing solutions to enhance efficiency and reduce manual errors. Automation can streamline workflows, allowing teams to focus on high-value tasks.
• Regularly review and refine testing protocols to eliminate redundancies. Continuous improvement initiatives can uncover areas for cost reduction without sacrificing quality.
• Invest in training for testing personnel to ensure best practices are followed. Well-trained staff can operate more efficiently, minimizing costly mistakes and rework.
• Utilize data analytics to identify trends and variances in testing costs. Analyzing historical data can reveal patterns that inform better resource allocation and budgeting decisions.

KPI Depot is trusted by consulting, strategy, finance, and analytics teams at leading organizations worldwide, including those listed below.

OKRs That Use Cost per Test

None of the ISO 15189 KPI group's OKR examples name Cost per Test as a key result. The group's OKR material is built around three objectives: eliminating error across all testing phases, achieving rapid and reliable turnaround to expedite clinical decisions, and maintaining full accreditation compliance through rigorous quality and regulatory controls. Its intro framing explains the absence rather than excusing it. It describes laboratories under rigorous demands for diagnostic accuracy, sample traceability and patient safety, which is a quality agenda, not a cost one.

The honest place for this metric is as a guardrail on the turnaround objective. The group's best practice guidance already says to align turnaround OKRs with clinical urgency and to keep overall Turnaround Time separate from Test Turnaround Time (TAT) for priority assays. A cost key result needs that same separation. A team working the turnaround objective can carry a directional key result to hold or reduce the cost of a reportable result for routine batched work while turnaround comes down, with priority and out of hours testing costed and reported separately rather than blended into the same average. Written that way the cost figure prevents the objective being satisfied by simply opening more runs and adding shifts, and it does not penalise the urgency the objective exists to buy.

The second framing sits under the accreditation objective, and it needs a warning attached. Quality control, proficiency testing, calibration, competency assessment and the remediation of audit findings are all cost, and all of it lands in this metric's numerator. A cost reduction key result written without that in view creates a quiet incentive to cut the exact spend accreditation depends on. The useful version is a visibility key result instead of a reduction one: separate quality and compliance cost from analytical cost in the reporting and defend it explicitly, so that any improvement in Cost per Test can be traced to rework and waste rather than to thinner controls. The group's own material connects Corrective Action Effectiveness and Accreditation Audit Non-conformity Rate to that objective, and the cost of rework is the thread that ties them to this KPI.

See OKR Examples for ISO 15189

Free Whitepaper

Want to achieve performance excellence in ISO 15189? Download our in-depth whitepaper: Definitive Guide to ISO 15189 KPIs.

Download the Free Guide

KPI Categories

This KPI is associated with the following categories and industries in our KPI database: