Ontology-based Phenotyping

The Leipzig Health Atlas (LHA) is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research fields in which our team has scientific and clinical expertise.

The Onto-Med Research Group conducts basic research in formal ontology, designs formal tools for constructing and managing ontologies and develops top level ontologies as well as domain and core ontologies for medicine, bio-medicine and biology, but also for other fields. The Onto-Med group uses an interdisciplinary approach, combining methods from logic, computer science, philosophy and cognitive linguistics. The Onto-Med group considers Formal Ontology as an evolving science which is concerned
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We evaluated if the PhenoMan returns correct/complete result sets and if it is working with real data. To simulate a FHIR health data store with real data we used Synthea(TM) to generate a large data set and imported it into a HAPI FHIR JPA Server. Based on the synthetic data set we developed ten example queries with different structure and complexity with PhenoMan and SQL. We compared the results of the queries in means of execution time and equality of results.

The detailed steps of the evaluation
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This assay bundles all synthetic FHIR data of the PhenoMan evaluation. The data arised from a subset of a Synthea(TM) generated data set.
We truncated some resource types like Encounter and Provider to reduce the size of the data set and to speed up the import in a FHIR health data store.

We modelled the algorithm for determining Type 2 Diabetes Mellitus (T2DM) cases presented by PheKB.org using Phenotype Manager (PhenoMan).

This data file contains FHIR bundles of observation resources, which were used for the evaluation of the PhenoMan.
Originally the observation data were generated with Synthea(TM) and truncated to reduce overall size and import times into a HAPI FHIR JPA Server.
Please import the patient resources prior to the observations.

This data file contains 8,026,380 observations.

This data file contains FHIR bundles of patient resources, which were used for the evaluation of the PhenoMan.
Originally the patient data were generated with Synthea(TM) and truncated to reduce overall size and import times into a HAPI FHIR JPA Server.

This data file contains 66,018 patients.

This data file contains FHIR bundles of allergy intolerance resources, which were used for the evaluation of the PhenoMan.
Originally the allergy intolerance data were generated with Synthea(TM) and truncated to reduce overall size and import times into a HAPI FHIR JPA Server.
Please import the patient resources prior to the allergy intolerances.

This data file contains 563 allergy intolerances.

This data file contains FHIR bundles of condition resources, which were used for the evaluation of the PhenoMan.
Originally the condition data were generated with Synthea(TM) and truncated to reduce overall size and import times into a HAPI FHIR JPA Server.
Please import the patient resources prior to the conditions.

This data file contains 139,763 conditions.

T2DM Phenotype Algorithm Specification Ontology (PASO) developed using PhenoMan