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In February 2026, Labcorp completed its acquisition of Empire City Laboratories assets in New York. Weeks earlier, it had acquired laboratory operations from Community Health Systems and Incyte Diagnostics. Within the same period, it announced an agreement with Parkview Health and invested in the construction of a new 500,000-square-foot facility in Indiana.
In Brazil, Dasa signed long-term contracts with Roche to modernize its diagnostic infrastructure, while Fleury-Pardini reinforced its investments in technology and strategic partnerships.
The consolidation wave in the laboratory sector isn’t new, but its current speed and scale are.
Yet there's a problem that rarely appears in the financial analyses of these transactions: what happens to laboratory data when two or more distinct systems need to function as one?
Buying laboratories is simple. Integrating their data is not.
According to a Digital Health Insights analysis, only 14% of healthcare mergers and acquisitions achieve full integration, and 83% of practitioners cite integration hurdles as the leading cause of failure. Deloitte data indicates that information technology accounts for up to 70% of expected synergies in hospital and laboratory mergers. When this integration stalls or fails, costs accumulate through disrupted billing cycles, duplicate testing, loss of clinical traceability, and dissatisfaction among referring physicians and patients.
The most common diagnosis is technical incompatibility between systems, but the problem runs deeper. One laboratory may run on one LIS, another on a different platform, and a third on a proprietary in-house system. Each stores data in different formats, uses distinct nomenclatures for the same tests, and applies reference values calibrated by specific methods and equipment.
The concrete result: a single creatinine test may appear as "Serum creatinine," "CREA," "creatinine," or "Creat. s." across different units within the same post-acquisition network. When a physician attempts to compare results over time, the trend curve, an essential tool in intensive care and chronic disease management, simply doesn't form. The data exists, but it's clinically unusable.
Scientific literature corroborates this dimension of the problem. A study published in the American Journal of Clinical Pathology demonstrated that differences in reference intervals between laboratories can generate diagnostic discrepancies in up to 25% of cases for certain tests.
The hidden cost of data fragmentation in consolidated networks
The consequences of post-acquisition data fragmentation manifest across three interdependent dimensions: operational, clinical, and strategic.
On the operational front, the absence of harmonization forces teams to maintain legacy systems running in parallel, a period that can extend for months or years. A Healthcare IT Today survey revealed that 60% of health systems receive duplicate, incomplete, or low-quality data from their integrated networks, and 69% report receiving incomplete data. Every hour a technician spends manually reconciling nomenclatures between systems is an hour subtracted from clinical analysis.
In a network of 100 physicians, if each spends just 15 minutes per day organizing test data that could be automated, the institution loses more than 5,000 hours of medical productivity per year. This calculation doesn't include time spent by nursing, clinical pharmacy, and population health management teams, who are also forced to reprocess or reinterpret reports in divergent formats.
On the clinical front, the impact is even more severe. Failures across the total laboratory cycle, from order to interpretation, account for approximately 70% of diagnostic errors in laboratory medicine.
On the strategic front, fragmented data renders the gains that motivated the acquisition unachievable. Benchmarking across units, population-level epidemiological analyses, AI-based predictive models, and chronic disease monitoring programs all depend on comparable, longitudinally consistent data.
Research indicates that only 18% of laboratories operate in a truly integrated manner with electronic health records, pharmacies, and surveillance systems. When integration is limited to technical connectivity without ensuring semantic and clinical equivalence, the informational asset that was supposed to justify the acquisition investment simply doesn't materialize.
A diagnostic network that consolidates units without harmonizing their data is, in practice, destroying part of the value that motivated the acquisition.
What the consolidation wave demands of laboratory data
Digitizing information transport isn't the same as ensuring its usability. Knowing that a result reached the system differs from knowing it can be compared, interpreted, and leveraged alongside data from other sources.
The distinction between standardization and harmonization is decisive in this context. Standardization unifies technical formats, ensuring systems speak the same communication protocol, such as HL7 or FHIR. Harmonization goes further: it ensures clinical and semantic equivalence between results from different laboratories, methods, and instruments. In other words, standardization organizes the form, but harmonization aligns the meaning, enabling data to be compared, integrated, and interpreted in a truly consistent and useful way for clinical practice and operational analysis.
This distinction is especially relevant in the post-acquisition context. Even when recognized standards such as HL7, FHIR, or LOINC are adopted on both ends of the integration, they alone don't eliminate clinical and semantic heterogeneity in results. A LOINC code may correctly identify a test type, but if reference values, units of measurement, and clinical metadata aren't equivalent, interoperability is only technical, not clinical.
The challenge is even more acute in Brazil, where there's no regulatory requirement for adopting unified nomenclatures. In Brazil, the landscape is particularly fragmented, with laboratories of different sizes operating under their own standards and no regulatory requirement for unified nomenclature adoption.
For networks growing through acquisitions, data harmonization isn't a step that follows system integration. It's the layer that determines whether integrated data will actually have clinical and operational value.
Without it, consolidation produces volume without intelligence: more data, but less information.
Harmonization as infrastructure for sustainable growth
When laboratory systems speak the same language, gains are distributed immediately: operationally, errors and duplicate tests are reduced, freeing time for higher-value clinical analysis; competitively, aligned data enables real benchmarking and measurable market advantages; and clinically, reliable reference ranges support more precise decisions and fewer avoidable readmissions.
Investment in harmonization, which typically represents a small fraction of a laboratory's total operating cost, should be evaluated not by its absolute value but by what it prevents: rework, wasted supplies, hours lost to manual categorization, unnecessary diagnostic cascades, erosion of clinical trust, and in the M&A context, the silent erosion of acquired value.
It's within this high-complexity scenario that the technology developed by OpenHealth Technologies fills a critical gap. OpenHealth Technologies automatically correlates multiple data streams with rigorously validated logical layers of laboratory tests, covering more than 8,000 biomarkers. Capable of extracting, normalizing, and interpreting data in any format, from legacy systems to modern electronic health records. The solution ensures not only technical connectivity but the semantic integrity and clinical accuracy essential for medical decision-making.
As a result, fragmented data from different units, systems, and methodologies is unified into a standardized, traceable, and clinically meaningful timeline.
For the manager of an expanding network, this means operations that are integrable from day one post-acquisition. For the physician, diagnostic confidence and continuity of care. For the patient, a journey free from unnecessary tests and supported by results that finally speak the same language.
Learn how your network can turn laboratory consolidation into real competitive advantage, with harmonized data from day one.