System design and integration
Data integration and terminology mapping
Clinical data is complex, subjective and frequently of poor quality. Many efforts have been made to use clinical terminologies and information model standards to capture better data. Our experience with clinical terminology, mapping techniques and semantic web technologies can help you when you need to integrate data from more than one system.
Terminology services design and implementation
Clinical terminologies are essential to collecting clinical data that can be reused. There is a national impetus to use SNOMED CT as the clinical terminology of choice in GP systems by 2017, and throughout the NHS by 2020. There remain concerns about the usability of clinical terminology in electronic health record systems. With our specialist expertise in the implementation of SNOMED CT, and technical knowledge of a broad range of other clinical terminologies, we can help EHR system suppliers design and implement terminology services that meet your client’s expectations.
Informatics standards profiling and conformance
Health interoperability standards such as HL7, SMART, FHIR, CEN13606, OpenEHR and their associated terminology and data type standards are complex, but also quite general purpose. They need specific constraint, profiling, or subsetting to meet the specific needs of a particular integration such as electronic discharge summaries. Critical to successful technical integration is the testing of conformance to standards. Our expertise in developing standards and automating API testing will help you achieve your integration goals.
Informatics strategy and health checks
Applications that collection personal health related data are widespread. The opportunities and challenges for developing these applications so that they are compatible with health information standards should be understood. We can review existing applications, or the architecture of your development work to make sure you make best use of existing health information standards.
Clinical data architecture
As applications collect, store or process health related data, detailed clinical information models are needed. These help structure electronic clinical information in ways in which clinicians understand, that supports direct patient care, but also allow secondary uses of clinical data, such as decision support, central data returns, or quality measurement. Our clinical expertise and domain modelling approach is designed to maximise the re-use of clinical information collected at the point of care.