Today narrative text predominates on clinical reports stored on the patients’ medical histories. This text is the basis of most of the clinical processes that have to do with coding, billing, case-mix analytics, medical researching and benchmarking among hospitals, to name just a few.
On the other hand, volume, variety and veracity of both structured and unstructured data supose a real challenge for decision making and the interoperability of systems.
That’s why we believe that Health Sector faces an unprecedented digital transformation which allows improving the clinical processes to achieve the interoperability of information at different levels: organizational, semantic, syntactic and technical.
And as a result it gets a more precise knowledge about the clinical casuistry, the optimization of resources, a better evaluation of costs, a greater support to the decision making and, in general, a more efficiency in clinical and management processes.
Fortunately, healt sector has a powerful standards that help the interoperability of information at different levels. In a semantic level we find SNOMED, Nomenclator, CIE-10-ES, LOINC, UNE-EN-13606: 2 etc., in a syntactic level HL7, 13606: 1, OpenEHR) and in technical level XML, Web Services , messaging, etc.
All of them allow health organizations to classify, standardize, measure and make interoperable the clinical information as the basis for optimization, management, decision support and data analysis.
The other pillar of this transformation is Data Science and Big Data technologies that are the tools that complement the Clinical History systems and the hospitals management, so we can design and implement descriptive, prescriptive and predictive models based on Machine Learning techniques, Natural Language Processing, etc., in a more agile and efficient way.
Are you interested in our solutions?
It solves the problem of classifying medical reports written in free narrative text using algorithms and tools that extract in an automatic way the main medical concepts.
CliniCoder is a support tool for coding using ICD-10-ES (diagnostics, procedures, external causes, side effects of drugs, etc.) and ICD-O-3 (oncology) that allows a better classification for discharge reports to generate RAE-CMBD records that are sent to the to the Ministry of Health and that are used for statistics and to generate the economic information of clinical events in an organization.
• It allows to analyze medical reports and classify diagnoses and procedures written in a medical language
• It has a structure and data model that allows to store any type of clinical document, whether structured or unstructured.
•It allows to get online and collaborative coding using workflow tools.
It provides versioning and traceability of operations.
• It has an analytical module that allows to obtain performance information of encoders.
CliniTerm - Standardisation
It allows to register in a standardized way different aspects related to the clinical practice, as for example alerts registering, allergies, health services, prescription, medicines, etc. This will be integrated or exported to the different systems involved in medical practice. CliniTerm is a tool for storing reference information and master tables used in clinical reports and in HIS systems of hospitals and health centers. It allows the management of standard reference terminologies (SNOMED CT, CIE-10-ES, LOINC, Medications, etc.) as well as their maintenance and distribution.
It allows the management of local information catalogs (alerts, allergies, health services, prescription, medicines, etc.) as well as the mapping and correspondence of these catalogs with the standards, allowing their integration through a set of services that facilitates their use within a digital medical history (EHR) system.
Coding and standardization consultancy
A fast development using classic and new technologies
Big Data and Data Science to discover new knowledge
It allows the analysis of clinical casuistry, costs and benchmarking using an open universe of data exploitation.
Quality assurance services for data
For this, it is necessary to carry out a cleaning of the data from different sources and systems so we ensure the coherence, quality and integrity of them.
The objective of this service is to offer our clients a complete methodology of Master Data Management that allows to obtain a complete control managing data.
• Data uploaded after cleaning and applicating quality rules
• List of data series according to typology and origin
• Inventory of established business rules
• Priority of source for matching / merging
Discover our projects and success stories in this Sector.
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