LinkEHR: Semantic Interoperability Platform


The rise of digitized health information means sometimes leads to a situation where it is difficult or impossible to access all of it in a simple, integrated and normalized way. LinkEHR interoperability platform is a Master Data Management system that consists of several modules that can be used together or independently according to each use case:

semantic interoperability

LinkEHR Integration provides the necessary infrastructure to facilitate a uniform access to dispersed data. This module allows the construction of a virtual Electronic Health Record, unifying and integrating the data we need from different clinical information systems.Our data integration technology provides a simple and flexible mechanism for creating views of existing information tailored to the needs of each user. It also incorporates mechanisms to preserve the integrity and privacy of data. In this way it becomes a very suitable solution for creating electronic health record systems built on existing systems and applications across the organization.

LinkEHR Studio offers a set of tools and technologies that help the adoption of standards and the normalization of data so that this information is interoperable between different systems. It allows to work with multiple norms and standards for the representation of the HCE, among which are the most adopted in the market such as HL7 CDA, HL7 FHIR, ISO EN 13606 and openEHR. Our platform helps to generate standardized data from existing data automatically. This means you can keep the existing information systems, without change, but improving their ability to communicate and integrate with other systems through standardized formats.

LinkEHR Model Manager is a service for the publication, annotation, management and collaborative government of clinical information models and other semantic resources used in your organization. You can manage and share archetypes, templates, implementation guides, data validators, sample instance or any other documentation about the clinical domain.

Get more information about LinkEHR here.

Qualize: Data Quality Analysis


The information of any organization is currently considered one of its main assets. If we want to take advantage of our company’s information, we need to ensure the quality of the data to reliably exploit the information.

This fact is particularly important in health information. First, data quality problems can have direct consequences on the healthcare process. Second, poor data quality can have a serious impact on their exploitation and/or reutilization in areas such as clinical trials, research, public health, health policy development, clinical practice evaluation or healthcare market research.

Data quality

Based on advanced technologies of health data representation standards, information theory and geometry and machine learning, VeraTech for Health offers qualize, an evaluation of the quality of biomedical data repositories and a rating service to assess their value for exploitation in clinical, strategic, managerial, and scientific decisions. 

qualize is an online service that helps you to carry out this work, automating as much as possible the evaluation process and offering a data quality analysis from a personalized perspective. qualize evaluates data quality in seven dimensions:

  1. Uniqueness. Is there replicated data?

  2. Completeness. Is there missing data?

  3. Correction. Are there unexpectedly anomalous registries?

  4. Consistency. Does my data comply with established rules? Formats, ranges ...

  5. Predictive value. Can I build decision support systems from my data?

  6. Temporal stability. Is there variability in my data over time?

  7. Multi-source stability. Is there variability in my data depending on their origin?


Try qualize demo here


HCOnco: Oncology Electronic Health Record System


Health is a field in which clinical knowledge is constantly changing. New tests and treatments are continuously researched and implemented in clinical practice, which makes  it difficult to develop large general systems adapted to all professionals. This is especially remarkable for the oncology area, where healthcare professionals need a system that is capable not only of managing the day-to-day of their consultation, but is also able to integrate new data required by the professional for their clinical tests.

HCEOnco is a Electronic Health Record system for the oncology domain which places special emphasis on serving as a research platform for oncologists. On the HCEOnco platform, users have views both for the clinical monitoring of patients and the visualization of grouped statistics that allow oncology personnel to carry out their research.

One of the platform key points is the ability to link tests and oncologic treatments with biological data, such as associated genes or detected mutations.

Key points

  • It is based on modern Electronic Health Record open standards

  • It relates on the same platform Clinical History data such as tests or treatments and biological such as associated genes or mutations detected in them

  • It has a statistics module to obtain population data on prevalences for cancer types by age, sex or other customizable criteria.

  • It contains the necessary information to provide oncological data to a population registry

  • Is is a meeting point of the different services that deal with cancer, from anatomical pathology, surgery or oncology, each of them with their own customizable views.

  • The application can be easily translated into any language

VeraSign: All-in-One Electronic Signature Solution



Electronic signature processes are perceived, often rightly, as complex, tricky and money and time consuming processes.

VeraSign is an intermediation system between applications and the verification and signing process. It is deployed as a service on any computer in your organization, with no need to manage additional applets or plugins, making it easily integrable with any web platform or desktop application already developed.

Using VeraSign services, users will be able to sign and validate documents in a transparent way and without requiring a previous knowledge about electronic signature

Digital signature

Moreover, VeraSign allows the creation of single sign-on (SSO) environments in which the user can authenticate against webs and applications automatically, without having to remember multiple users and passwords or through the use of personal digital certificates.


CTDOC: Mass diagnosis processing and encoding

Documentalists’ labour is crucial within the processes of an hospital. However, it is one of the most expensive processes, since it requires not only extensive clinical knowledge, but also deep knowledge about how the organization works and what language and expressions the clinical professionals use. It is for that reason that having tools that help in this problem and that are capable of learning the particularities of each hospital is a key element in the current systems.

In VeraTech we have developed a tool to aid in the ICD-10 coding of clinical reports. It incorporates an environment that covers the complete cycle of coding reports: Administration, Episode retrieval from the HIS, Coding, Validation and return encoded Episodes to the HIS. CTDOC provides a search engine based on approximate search techniques that allows the documentalist to find the ICD-10 codes that best suit the diagnoses and procedures contained in the report.


Key points:

  • Integration with the HIS: CTDOC can connect directly with the HIS to access  the different episodes of patients.

  • Multi-report. The documentalist has access from a single screen to all the reports in the episode. It allows the capture of structured reports so that the search algorithms are launched on the relevant parts of the report.

  • The search engine of CTDOC incorporates 1.500.000 synonyms that, together with the approximate search algorithms, respond to natural language coding

  • CTDOC incorporates a rule engine that helps the coder to assign the correct codes respecting the regulations in force: Incompatibilities by sex and age, multiple and combined codes, inclusion / exclusion of codes, consistency Diagnosis-Procedure

  • Role structure allows assigning/exchanging episodes between different Service documentalists.

  • It has an Coding module through Web Services that allows the unassisted coding of reports. (such as Emergency reports)

GIBIO: Interoperability Platform for biobanks

GIBIO is a semantic data interoperability management software for biological resource centers. The platform allows standardizing the incorporation, recovery and representation of clinical information associated with biological samples within the information management system (SGI) of the BRCs as well as facilitating their integration with other existing SGIs at the regional, national or international level. The main functionality of the manager is to establish a common platform where all the health research foundations linked to this platform and interested in the same research strategy work together an in a coordinated way in order to identify and prioritize the technological, innovation and research needs in the medium and long term.

GIBIO allows to cover activities from the analysis of technical and functional requirements, validation and feasibility of them, planning, estimation of effort and cost, analysis, design, development and testing (unit, integrated, regression and acceptance), to validation and approval of users. All of these functionalities will allow to achieve scientific and technological advances that ensure the competitiveness, sustainability and the growth of the global health ecosystem, aligning the strategies of the different agents and concentrating the R&D efforts..


Key Points:

  • Use of international standards for communication of electronic medical records, archetypes and medical terminologies for the exchange of information associated with samples, donors and biobanks.

  • Data exchange quality evaluation and validation based on three complementary dimensions: completeness, consistency and contextualization.

  • We propose a methodology and tools that can work with any standard based on a dual electronic medical history model and incorporate new archetypes over time with the consequent capacity for evolution and adaptation to new organizational models or health domains.