EHDEN - D2.3 - OMOP-CDM enhancements for outcome driven healthcare
Creators: name: Fox, Frank
name: Sandijk, Sebastiaan Van
name: Wissig, Stephanie
Publisher: name: Zenodo
Year: 2020
Subjects: Outcome driven
OMOP
ICHOM
Standard set
Extension

description: <strong>Introduction: </strong>EHDEN’s mission is to develop a federated research data network, standardized to OMOP Common Data Model (OMOP-CDM). Work Package 2 has the objective to enable the transition towards outcomes-driven healthcare systems in Europe. As part of this work, WP2 intends to extend the OMOP-CDM with the ICHOM standard sets. WP2 Deliverable 2.3 (D2.3) assesses the potential marriage of ICHOM’s standard sets and the EHDEN/OHDSI technology stack, in particular the OMOP-CDM. <br> <strong>Aims &amp; Objectives:</strong> D2.3 aims to facilitate the extension of the OMOP-CDM to include ICHOM specific data domains such as patient reported outcome data. D2.3 will use the prioritised standard sets as proof of concepts to identify gaps in the OMOP-CDM structures and vocabularies and propose how this can be generalised to all standard sets. This aim has been refined to the following three main objectives. Identify gaps in the mapping of the Inflammatory Arthritis and Prostate Cancer standard sets to the OMOP-CDM structures. Identify gaps in the mapping of these standard sets to the OMOP-CDM vocabulary Based on gaps identified in objectives above, propose future activities to fill those gaps. <strong>Method</strong>: This research was exploratory in nature and the method drew from several sources. Central was the Book of OHDSI, ICHOM Reference guides, EHDEN Deliverable 3.2, EHDEN Study-a-thon outputs, and other previous publications. The steps can be summarised as: data acquisition, mapping ICHOM’s prioritised standard sets to the OMOP-CDM, generalisation of the techniques, further investigation using the OHDSI data analytics tools, and reflection on how to better align the two standards.<br> <strong>Results &amp; Outputs:</strong> The key findings are: The OMOP-CDM structure can currently accommodate the datatypes, the question &amp; answer types, and the recommended patient-reported outcome measures (PROMs) from the ICHOM Inflammatory Arthritis and Prostate Cancer standard sets. The OMOP-CDM standard vocabularies currently have patchy coverage of the vocabulary required to accommodate the prioritised standard sets and PROMs. This coverage can be enhanced at a local level by creating new vocabulary entries and/or by requesting that they required entries are included by default in new releases of the standard vocabulary. The key outputs are: Matching/Mapping of ICHOM prioritised standard set to the OMOP-CDM and gap identification (See Appendices B&amp;C). Generalised approaches for matching/mapping ICHOM standard sets to the OMOP-CDM structure and vocabulary including classification of question-types in the standard sets. Example approach for inserting ICHOM standard dataset into OMOP-CDM. Recommendations for stakeholders to enable and enhance the process. <strong>Discussion/Conclusion:</strong> Mapping the prioritised standard sets to the CDM structures worked well – including the accommodation of timing logic &amp; care-pathways. However, it is likely that other standard sets and real-world applications will bring new issues to light. Coverage of the prioritised standard sets in the CDM standard vocabularies was found to be patchy and this is likely to be an ongoing issue with real-world datasets (RWD). The vocabulary enhancement process needs consideration. Should commonly used PROMs be in the standard vocabularies? Should the mappings primarily aim to accommodate benchmarking, or should the mappings support the deeper EHDEN-adopted ‘FAIR’ philosophy?  Mastering the OHDSI/EHDEN/ICHOM environments proved a steep learning curve for the researchers - in both in the extract-transform-load (ETL) phase and in the data analytics phase. Many of the sophisticated tools and artefacts are open-source, intricate, and are new or untested in some respects. Data partners will need planning and implementation support. Guidelines are needed for implementation of standard sets in EHDEN and benchmarking. Lines of communication need to be established between ICHOM, OHDSI, the vocabulary teams, and data partners to facilitate efficient resolution of queries and issues. The discoveries from this exercise will be enriched by application to RWD although this will bring its own unique issues, particularly on data quality and provenance.