Revision as of 12:31, 5 February 2023

These articles describe the Endeavour open source information model and various services, used 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 a common data model as part of a common 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 information models which present single ontology of the concepts, bound to a common data model, both underpinned by mappings to and from the disparate source types.

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

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 These articles describe the Endeavour open source information model and various services,  used as part of a broader set of Endeavour open source technologies, which have been adapted and used by a large scale [https://wiki.discoverydataservice.org/index.php?title=Welcome_to_the_Discovery_Data_Service_knowledge_base NHS  London Data linkage and normalisation Service] covering a population of 7 million registered citizens.
-==Health Record Data Service and Health Information model==
+==Health Information model==
-The health record data service is based on the hypothesis that; 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 a common data model as part of a common ontology, and then subsequently used for individual and population based decision support, great benefits to health can accrue.
+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 a common data model as part of a common ontology, and then subsequently used for individual and population based decision support, great benefits to health can accrue.
-To make sense of such a large repository of thousands of data types and millions of codes from thousands of providers using dozens of different systems,  it is useful to create a common information model which presents a simpler view but covers most of the data items published by providers.
+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 information models which present single ''ontology of the concepts,''  bound to a common data model, both underpinned by mappings to and from the disparate source types.
-Such a model is not an alternative to the health standards based models, instead it is a common model of the models as well as the proprietary data models and codes
+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.
-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.
-The services that link and normalise the data  (such as Discovery), can use this model, creating maps between source data and the common model and thus enabling easier and more efficient use of the data,
+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.
-All components of the information model are open source and are themselves built from open source and open standards such as W3C standards.
+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:
-The content of the model 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 data model resources such as FHIR making the IM FHIR compatible via simple transforms.
+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 enabling the IM to hold definitions of most complex business rules used in query.
+c) The main stream query definitions such as QOF.
 == Information model Components ==
 *[[Discovery health information model|Health Information model]] - An overview of the approach to the Health information model,  the purpose, and type of content.
-*[[Health Information modelling language|Information model language]] - The Semantic Web languages used to build the various components of the information models
+*[[Health Information modelling language|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 and matching concepts|Mapping concepts and transforming published data]] - Introduces the approaches to matching and mapping concepts and the structural maps used in transforming published data,