Welcome to the Endeavour Health knowledge base

These articles describe the Endeavour information modelling open source technologies and services, proven at scale as part of a broader set of Endeavour open source technologies, which have been adapted and used by a large scale NHS London Data linkage and normalisation Service covering a population of 7 million registered citizens.

Health Information model

If health related data is brought together at the level of the individual in close to real time, and stored together at the level of a medium size residential population, and made available via an ontology, and then subsequently used for individual and population based decision support, great benefits to health can accrue.

To make sense of huge variation with thousands of data types and millions of codes from thousands of providers using scores of different systems, it is useful to create an information model covering a data model, an ontology of concepts bound to the data model, and presented via an application in a way that enables query of all of the data by a none technical user.

Having established such a model , it is then possible to construct logical definitions of query and concept sets that can then be used on the data published from the sources.

Services that link and normalise the data can use the model and/ or the ontologies within it, creating maps between source data and the common model.

Most models use either bespoke health care languages such as those used by HL7 or openEHR. The approach used in the Endeavour information model is to adopt and adapt the Main stream semantic web languages based on a view of health data as a graph with the nodes and edges identified and modelled as RDF.

The model is not a new standard or an invention of new concepts. Instead, the content of the Endeavour IM incorporates concepts from a number of recognised sources including:

a) The main stream health ontology Snomed-CT with extensions to accommodate the unmapped NHS data dictionary attributes, local codes, and code taxonomies such as OPCS, ICD10 as well as the legacy mappings to Read 2.

b) The main stream messaging model resources such as FHIR making the IM FHIR compatible via simple transforms.

c) The main stream query definitions such as QOF.

Information model Components

• Health Information model - An overview of the approach to the Health information model, the purpose, and type of content.
• Information model languages - The Semantic Web languages used to build the various components of the information models
• Health query definition- A logical machine readable definition of query, covering the majority of health data query requirements.
• Information model meta model. The class model (shapes model) of the classes used to hold the model content.
• Mapping concepts and transforming published data - Introduces the approaches to matching and mapping concepts and the structural maps used in transforming published data,
• Architectures - A high level overview of the architectures that the technologies contribute to
• GitHub repositories - descriptions and information relating to the application source code, .

Applications and APIs

These articles provide information about the applications that have been by the technologies

• Information model applications and services - the applications and technical services , such as APIs and apps that enable an model instance to be used or to implement an EHR based on the model or particular data model
• get Structured Record APIs - returns a project specific patient record in a structured format using FHIR standards.
• Monitoring and alerting - provides an overview of the monitoring and alert systems in place.

• Data Sharing manager- DSM provides a visual representation of data that is being shared and processed and by which organisations, regions, and/or services.
• ASSIGN- UPRN address matching application - a web based application that matches single or batches of hand entered address to authoritative addresses and assigns a unique property reference number.
• Alert Generator - APIs that generates a patient alert based on a query, sends a notification to recipients and provides recipients with access to a web application to view the content of the record according to the data set
• Data Distribution services that distribute daily weekly or adhoc small data sets from the linked core data stores with examples from 2020