Most veterinary practice managers across Europe will recognise the scenario immediately: a diagnostic result arrives by email, a staff member opens the PDF, reads the values, and manually types them into the practice management system. It takes a few minutes each time. Multiply that across dozens of samples a week, across a team of nurses and receptionists already stretched thin, and the cumulative cost in time, in attention, and occasionally in accuracy becomes significant. This manual loop persists not because of technical inevitability, but because of specific structural, commercial, and regulatory conditions that remain unresolved in European veterinary medicine.

What interoperability actually means in a veterinary context

Interoperability, in plain terms, is the ability of two software systems to exchange data automatically without a human acting as the messenger. In a veterinary practice, this means a practice management system (PIMS) and an external diagnostic laboratory system sharing information directly: a test request flowing out from the PIMS, and a structured result flowing back in, automatically populating the patient record.

Two distinct levels of this capability are worth distinguishing. Basic data transfer might mean a laboratory emails a PDF that attaches to a patient file. That is technically digital, but it still requires manual review and re-entry of any values the clinician wants to act on. True bidirectional integration means structured data moves in both directions: orders go out in a machine-readable format, results come back in a machine-readable format, and both systems update without staff intervention.

Most European practices currently sit closer to the first state than the second.

How the diagnostic workflow currently looks in most European practices

The typical workflow in a European veterinary practice follows a familiar pattern. A clinician requests a diagnostic test, such as haematology, biochemistry, culture, or imaging, and a sample is prepared and dispatched to an external laboratory. The lab processes the sample and returns results, usually as a PDF attached to an email or accessible through a laboratory portal. A staff member retrieves the result, reviews it, and either manually re-enters the key values into the patient record or attaches the PDF as a document.

This process introduces several points of friction. Time is lost at each handoff: someone must monitor the email inbox or portal, identify which patient the result belongs to, locate the correct record in the PIMS, and transcribe or attach the findings. The risk of transcription error is real. A misplaced decimal, a transposed digit, or a result filed against the wrong patient can have direct clinical consequences. Because results are not automatically surfaced within the clinical workflow, time-sensitive findings can sit in an inbox longer than they should.

A 2025 environmental scan of companion animal health surveillance systems found that only 42.4 per cent of systems extracted data from electronic health records and veterinary diagnostic laboratory data, and just 9.1 per cent integrated data at the point of collection. Those figures reflect how far the sector remains from seamless connectivity.

Why veterinary medicine has no equivalent of HL7 or FHIR

In human healthcare, data exchange between clinical systems relies on established standards. HL7 (Health Level Seven) and its more modern successor FHIR (Fast Healthcare Interoperability Resources) define how patient data, diagnostic orders, and results should be structured and transmitted between systems. These standards are not perfect, and adoption is uneven, but they provide a common language that makes integration at least technically tractable.

Veterinary medicine has no widely adopted equivalent. As the Puppilot interoperability guide notes, the absence of a universal veterinary data standard means each software vendor and each laboratory builds connections on proprietary terms, where they exist at all. There is no shared specification for how a haematology result from an external lab should be structured when it enters a PIMS, no agreed field names, and no common coding system for test types.

Standard veterinary terminologies do exist. The SNOMED-CT Veterinary Extension and VeNOM (used primarily in the UK) provide frameworks for consistent clinical coding. But as a peer-reviewed paper from the Association for Veterinary Informatics states directly, neither reference laboratories nor receiving PIMS routinely use standardised nomenclature such as SNOMED-CT or LOINC (Logical Observation Identifiers Names and Codes) during data transmission. These terminologies are "rarely integrated into a regular workflow." Without a shared semantic layer, even systems that can technically connect may exchange data that neither can reliably interpret.

The LabPortal.vet overview of veterinary lab integration confirms that while protocols such as HL7 and DICOM (Digital Imaging and Communications in Medicine) exist and are used in some veterinary imaging contexts, their absence across the broader diagnostic data ecosystem creates persistent bottlenecks that individual practices cannot resolve on their own.

The fragmented veterinary software market in Europe

Europe's veterinary PIMS market is not a single market. It is a collection of national and regional markets, each with its own dominant vendors, its own legacy infrastructure, and its own pace of modernisation. A practice in the Netherlands may run a system with no overlap in architecture or application programming interface (API) capability with the system used by a practice in Spain or Poland.

According to market analysis published in April 2026, Europe is seeing steady growth in veterinary software adoption, partly driven by regulatory requirements around animal health tracking. Growth in adoption does not automatically translate into growth in interoperability. Practices may move onto newer systems while those systems remain as siloed as the ones they replaced.

The Prior Knowledge and Practice analysis from May 2026 puts the scale of the problem in concrete terms: with approximately 15 major PIMS platforms and over 140 integration partners, there are potentially 2,100 distinct integration pairs in a theoretical maximum scenario where every PIMS connects to every partner. That figure alone illustrates why a market-led solution has not emerged organically, though the actual number of integrations that would realistically need to be built is considerably lower.

Digitail, a European-founded veterinary PIMS vendor, describes the current state plainly: many systems offer isolated third-party integrations that "can't see the full patient journey, don't have access to real-time medical records, and rarely communicate with other parts of the system."

Commercial dynamics that slow integration down

The interoperability gap is not simply a technical problem waiting for an engineering solution. It is also a commercial problem.

Diagnostic laboratories and PIMS vendors both have limited incentive to invest in open, standardised integrations when doing so may benefit a competitor. A laboratory that builds a seamless connection to every PIMS on the market makes it easier for practices to switch to a rival lab. A PIMS vendor that exposes a fully documented, open API makes it easier for practices to switch to a rival PIMS. Proprietary data formats can function as lock-in mechanisms, not necessarily by design, but as a structural consequence of how software businesses protect their customer relationships.

As the August 2025 Prior Knowledge and Practice analysis explains, laboratory connections from these vendors are largely proprietary, requiring separate development effort from each PIMS vendor. When a laboratory upgrades its systems, existing integrations frequently break, requiring renegotiation and redevelopment. The same analysis identifies that APIs across the sector are frequently "closed, undocumented, or fee-gated," meaning smaller PIMS vendors face a financial barrier even to begin building connections.

Small and mid-sized veterinary software vendors make up a significant share of the European market and typically lack the engineering capacity to build and maintain multiple simultaneous laboratory integrations. Their development resources go toward core clinical features, the things that win new customers, rather than integration work that benefits existing ones.

The regulatory environment: no mandate, no urgency

In human healthcare, interoperability is increasingly a compliance matter. The General Data Protection Regulation (GDPR) has established baseline data portability principles. National eHealth strategies across EU member states have pushed for medical record system connectivity. The European Health Data Space (EHDS), now advancing through EU legislative processes, is expected to create enforceable obligations around health data sharing and interoperability for human medicine.

Veterinary data sits almost entirely outside these regulatory drivers. There is no veterinary equivalent of the EHDS. There is no EU mandate requiring PIMS vendors to expose open APIs or requiring diagnostic laboratories to transmit results in a standardised format. GDPR applies to personal data about animal owners, but not to the clinical data about animals themselves, removing one of the more powerful levers that has driven change in human healthcare IT.

The European Medicines Agency's veterinary big data strategy acknowledges that connecting real-world data sources from animal health professionals remains a long-term challenge. The EMA's EU Implementation Guide for the Union Product Database uses HL7 FHIR for regulatory submissions of medicinal product data, but this applies to product information, not to clinical or diagnostic data generated within practices. The regulatory infrastructure and the practice-level infrastructure remain separate.

Without a compliance mandate, vendors face no external pressure to prioritise interoperability investment. The result is a market that can acknowledge the problem broadly while having no structural mechanism to resolve it.

Where integration does exist and what it takes to build it

Point-to-point integrations between specific laboratory systems and specific PIMS platforms do exist, and the landscape is not entirely disconnected. Large diagnostic chains, including IDEXX, Antech, and Zoetis, have built integrations with some of the larger PIMS platforms, typically through bilateral commercial agreements that involve significant development effort, contractual negotiation, and ongoing maintenance commitments.

Intermediary platforms such as Bitwerx, IDEXX DataPoint, and Covetrus Connect have emerged to address parts of the connection and structural layers of the problem, providing middleware that can translate between some PIMS and some laboratory systems. But as the May 2026 Prior Knowledge and Practice analysis notes, these platforms address the connection and structural layers without resolving the semantic layer: the question of whether both systems assign the same clinical meaning to the data being exchanged.

For independent or smaller diagnostic laboratories, the picture is considerably bleaker. Building a certified integration with even one major PIMS typically requires development resources, legal agreements, and ongoing maintenance that are not viable at smaller scale. Practices using specialist or regional laboratories, which may offer superior services for specific diagnostic needs, are almost always operating without any automated data exchange.

The hidden cost to practice managers and clinical staff

The operational cost of manual data handling is easy to underestimate because it is distributed across many small tasks rather than concentrated in a single visible failure. The aggregate impact is substantial.

Consider a practice processing 30 external diagnostic requests per week. If each result takes five minutes to retrieve, review, and manually enter or attach—an illustrative assumption that may vary by practice—that represents 150 minutes of staff time per week, or roughly 130 hours per year, on a task that adds no clinical value and could in principle be automated. For a fuller picture of how these hours accumulate into measurable cost, see documentation-cost-per-veterinarian-a-european-perspective. In practices with higher diagnostic volumes, the figure is proportionally larger.

The veterinary informatics research on data extraction challenges makes clear that the absence of standardised nomenclature during data transmission creates downstream problems not just for individual practices but for any attempt to aggregate or analyse veterinary diagnostic data at scale. This includes antimicrobial resistance surveillance, where data harmonisation across laboratory types requires significant additional effort precisely because raw data cannot be reliably exchanged between systems.

Beyond time, there is a cognitive load dimension that practice managers should take seriously. Cognitive load refers to the mental effort required to manage multiple tasks simultaneously. Veterinarians and nurses who must switch between a PIMS, a laboratory portal, an email inbox, and a PDF viewer to complete a single clinical task carry avoidable mental friction. Digitail's analysis of disconnected systems describes this directly as "a barrier to growth and a drain on your team," a characterisation that aligns with broader evidence on how fragmented digital workflows affect clinical staff.

Transcription errors, while individually rare, carry disproportionate risk. A result filed against the wrong patient, or a value entered incorrectly, can influence a treatment decision before the error is identified. In a high-throughput practice, the conditions for such errors, including time pressure, repetitive tasks, and multiple open records, are structurally present.

What practice managers can do right now to reduce the burden

While the systemic problem requires systemic solutions, there are practical steps practice managers can take to reduce the burden within their current constraints.

Audit your diagnostic providers.

Not all external laboratories are equally disconnected. Some offer structured data exports, such as CSV files, HL7 messages, or portal APIs, even without a direct PIMS integration. Ask your current laboratory suppliers what data export formats they support. A structured CSV export, even if it still requires a manual import step, is less error-prone than manual transcription from a PDF.

Ask your PIMS vendor directly about their integration roadmap.

Many vendors have integration plans that are not prominently advertised. A direct conversation, particularly if framed as a procurement consideration, can surface timelines and partnerships that are not visible in standard product documentation. The Puppilot interoperability guide recommends asking specifically about API availability, existing integration partnerships, and what development investment would be required to connect a specific laboratory.

Consolidate diagnostic providers where clinically appropriate.

The more laboratory suppliers a practice uses, the more disconnected systems it must manage. Where clinical quality is comparable, consolidating to fewer providers, particularly those with existing PIMS integrations or structured export capabilities, reduces the number of manual workflows in operation.

Introduce structured naming and filing conventions for manual imports.

Where manual attachment of PDF results is unavoidable, consistent naming conventions covering patient ID, date, and test type, alongside a defined filing protocol, reduce the risk of results being attached to the wrong record or becoming unsearchable. This does not solve the underlying problem but reduces its consequences.

Designate responsibility clearly.

Ambiguity about who retrieves and enters diagnostic results is a common source of delay and duplication. A clear, documented protocol specifying who checks for results, at what frequency, and how they are recorded reduces the chance that time-sensitive findings are missed.

Questions to ask your PIMS vendor and diagnostic suppliers

Practice managers who understand the interoperability landscape are better positioned to apply commercial pressure for change. The following questions are worth putting directly to your software and laboratory suppliers:

• Does your system have a documented, accessible API? Is it open or fee-gated?

• Which diagnostic laboratories do you currently have direct integrations with, and what does that integration cover: orders, results, or both?

• What data format do results arrive in: structured data or PDF?

• If a direct integration does not exist with our laboratory, what would it take to build one, and who bears the cost?

• Do you support any intermediary integration platforms such as Bitwerx, IDEXX DataPoint, or similar?

• What is on your integration roadmap for the next 12 to 24 months?

• Can our laboratory export results in HL7 or a structured format that could be imported into our PIMS?

• How are integrations maintained when either system undergoes a major update?

These questions serve two purposes: they surface information that is genuinely useful for procurement decisions, and they signal to vendors that practice managers regard interoperability as a buying criterion, which over time shifts commercial incentives.

What better interoperability would look like and whether it is coming

A more connected veterinary data environment would look something like this: a clinician requests a diagnostic test from within the PIMS, the order is transmitted electronically to the laboratory in a standardised format, the laboratory processes the sample and returns a structured result that automatically populates the relevant fields in the patient record, and the clinician receives a notification within their existing workflow. No PDF. No manual re-entry. No switching between systems.

This is not a speculative vision. It broadly describes how well-integrated human healthcare systems operate in countries with mature eHealth infrastructure. The technical components required to build it in veterinary medicine, including APIs, structured data formats, and shared terminology standards, all exist. What is missing is the coordination mechanism to make them universal.

Some efforts are underway. VetXML, a UK-based initiative, has developed XML-based standards for veterinary data exchange and has been adopted by some UK PIMS vendors and insurers. The Puppilot guide describes it as promising but notes that global fragmentation persists. Veterinary informatics researchers have called for greater adoption of SNOMED-CT and LOINC in laboratory data transmission, and text-mining approaches have been explored as a way to extract structured information from unstructured veterinary records, a workaround that underscores how far the sector remains from native structured data.

The near-term outlook warrants realism. Without a regulatory mandate equivalent to what is driving interoperability in human healthcare, progress in European veterinary medicine is likely to be incremental and uneven. Larger practices with negotiating leverage, and practices using major diagnostic chains with existing PIMS partnerships, will see improvements sooner. Independent laboratories and smaller PIMS vendors will remain at the margins of integration investment for the foreseeable future. The market data points to modernisation pressure as legacy systems age out, which may create windows for better-integrated replacements. Modernisation alone does not guarantee interoperability if new systems replicate the same closed architectures.

A solvable problem that requires collective pressure

The interoperability gap between veterinary practice management software and diagnostic laboratory systems in Europe is not a technical mystery. The three-layer analysis, covering connection, structure, and semantics, maps the problem clearly. The solutions at each layer are known. What is missing is the combination of regulatory mandate, commercial incentive, and coordinated industry effort needed to implement them at scale.

Practice managers cannot resolve this alone. By understanding why the problem persists, including fragmented markets, absent regulation, misaligned commercial incentives, and the sheer scale of integration pairs required, practice managers are better placed to make smarter procurement decisions, ask harder questions of their vendors, and advocate credibly for changes that would reduce the daily operational burden on their teams. In a market where vendor behaviour is shaped partly by customer expectations, informed buyers are part of the solution.

Frequently asked questions

▶ What does interoperability mean for a veterinary practice?

Interoperability means two software systems exchange data automatically, without a staff member acting as the messenger. In a veterinary practice, it means the practice management system and an external diagnostic laboratory system share information directly: test requests flow out in a machine-readable format, and structured results flow back in, populating the patient record without manual intervention. Most European practices currently rely on PDF results sent by email, which still requires manual review and re-entry of values.

▶ Why doesn't veterinary medicine have data standards like HL7 or FHIR?

Human healthcare uses established standards such as Health Level Seven (HL7) and Fast Healthcare Interoperability Resources (FHIR) to define how patient data, diagnostic orders, and results are structured and transmitted between systems. Veterinary medicine has no widely adopted equivalent. Each software vendor and each laboratory builds connections on proprietary terms. Standard veterinary terminologies such as the SNOMED-CT Veterinary Extension and Logical Observation Identifiers Names and Codes (LOINC) exist, but research from the Association for Veterinary Informatics confirms they're rarely integrated into regular workflows during data transmission.

▶ Why is the veterinary software market in Europe so fragmented?

Europe's veterinary practice management software market is a collection of national and regional markets, each with its own dominant vendors, legacy infrastructure, and pace of modernisation. Analysis published in May 2026 identified approximately 15 major practice management platforms and over 140 integration partners, creating a theoretical maximum of 2,100 distinct integration pairs. Practices may move onto newer systems while those systems remain as siloed as the ones they replaced. Many vendors offer isolated third-party integrations that can't access real-time medical records or communicate with other parts of the system.

▶ What commercial factors slow down laboratory integration in veterinary practices?

Diagnostic laboratories and practice management software vendors both have limited incentive to invest in open, standardised integrations. A laboratory that connects seamlessly to every system on the market makes it easier for practices to switch to a rival lab. A software vendor that exposes a fully documented, open application programming interface (API) makes it easier for practices to switch to a rival system. APIs across the sector are frequently closed, undocumented, or fee-gated, meaning smaller vendors face a financial barrier even to begin building connections. When a laboratory upgrades its systems, existing integrations frequently break and require renegotiation.

▶ Is there a regulatory requirement for veterinary data interoperability in Europe?

No. In human healthcare, initiatives such as the European Health Data Space (EHDS) are creating enforceable obligations around health data sharing. Veterinary data sits almost entirely outside these regulatory drivers. There's no EU mandate requiring practice management software vendors to expose open APIs or requiring diagnostic laboratories to transmit results in a standardised format. The General Data Protection Regulation (GDPR) applies to personal data about animal owners, but not to clinical data about animals themselves. Without a compliance mandate, vendors face no external pressure to prioritise interoperability investment.

▶ What is the real cost of manual diagnostic data entry for veterinary practices?

The cost is distributed across many small tasks, which makes it easy to underestimate. A practice processing 30 external diagnostic requests per week, with each result taking five minutes to retrieve, review, and manually enter or attach, accumulates roughly 130 hours of staff time per year on a task that adds no clinical value. Beyond time, there's a cognitive load dimension: staff switching between a practice management system, a laboratory portal, an email inbox, and a PDF viewer carry avoidable mental friction. Transcription errors, while individually rare, carry disproportionate risk because a result filed against the wrong patient can influence a treatment decision before the error is identified.

▶ Where does direct laboratory integration currently exist in veterinary medicine?

Point-to-point integrations do exist between specific laboratory systems and specific practice management platforms. Large diagnostic chains including IDEXX, Antech, and Zoetis have built integrations with some larger platforms through bilateral commercial agreements. Intermediary platforms such as Bitwerx, IDEXX DataPoint, and Covetrus Connect provide middleware that can translate between some systems. However, these platforms address the connection and structural layers without resolving the semantic layer, meaning whether both systems assign the same clinical meaning to the data being exchanged. For independent or smaller diagnostic laboratories, building a certified integration with even one major platform typically isn't viable at smaller scale.

▶ What practical steps can practice managers take now to reduce the manual data burden?

Several steps are worth taking within current constraints. Ask your diagnostic laboratory suppliers what structured data export formats they support, such as CSV files or HL7 messages, as these are less error-prone than manual transcription from a PDF. Ask your practice management software vendor directly about their integration roadmap and API availability, framing it as a procurement consideration. Where clinical quality is comparable, consolidating to fewer laboratory providers reduces the number of disconnected manual workflows. Introducing consistent naming conventions for manual PDF attachments, and designating clear responsibility for who retrieves and records results, reduces the risk of delays and filing errors.

▶ What questions should practice managers ask their software and laboratory suppliers about interoperability?

The article recommends asking suppliers whether their system has a documented, accessible API and whether it's open or fee-gated. It's worth asking which diagnostic laboratories they currently integrate with and whether that covers orders, results, or both. Ask what data format results arrive in, whether structured data or PDF, and what it would take to build a connection with your specific laboratory. Ask whether they support intermediary platforms such as Bitwerx or IDEXX DataPoint, what's on their integration roadmap for the next 12 to 24 months, and how integrations are maintained when either system undergoes a major update. These questions also signal to vendors that interoperability is a buying criterion, which over time shifts commercial incentives.

▶ Is better veterinary data interoperability likely to arrive soon in Europe?

The near-term outlook warrants realism. Without a regulatory mandate equivalent to what's driving interoperability in human healthcare, progress in European veterinary medicine is likely to be incremental and uneven. Larger practices with negotiating leverage, and those using major diagnostic chains with existing platform partnerships, will see improvements sooner. Independent laboratories and smaller software vendors will remain at the margins of integration investment for the foreseeable future. Initiatives such as VetXML, a UK-based XML standard for veterinary data exchange, show promise but global fragmentation persists. The technical components required, including APIs, structured data formats, and shared terminology standards, all exist. What's missing is the combination of regulatory mandate, commercial incentive, and coordinated industry effort to implement them at scale.