The OMOP CDM – A contender for standardising healthcare data?
Tessa May - Technical Consultant
Data is an integral part of the healthcare system, and its importance cannot be overstated. In recent years, there has been a growing trend towards using standardised healthcare data models such as HL7, FHIR and OpenEHR. However, in an increasingly data-driven world, an emerging contender in the industry is the Observation Medical Outcomes Partnership Common Data Model (OMOP CDM). In this post, we look to explore what the OMOP model is, and how it could help you.
First of all, what does it mean to standardise healthcare data and why should we do it?
Standardising healthcare data means transforming raw data from various healthcare sources, which use different structures and terminologies, into a common format. This process has enormous benefits in improving patient outcomes by enabling more accurate and consistent tracking of patient’s health. It allows clinicians to make more informed decisions about treatment and provide personalised care. It can also reduce errors, by ensuring that all medical professionals are using the same terminology and guidelines.
What is the OMOP CDM?
The OMOP CDM is an international standardised data model, created by the Observational Health Data Sciences and Informatics (OHDSI, pronounced ‘Odyssey’) initiative, designed to facilitate the analysis of large, disparate datasets for observational research in healthcare. It is the pre-eminent data model within the clinical data analytics community, and aims to alleviate some of the challenges researchers face in using data from multiple sources due to differences in data structure, coding systems and terminologies. The model consists of a set of tables that represent healthcare data domains, such as patient demographics, clinical events, medications, and diagnoses. It also includes a set of standardised vocabularies, such as SNOMED-CT, which provide a common language for describing medical concepts.
Why should we use the OMOP CDM?
Firstly, it promotes interoperability, enabling researchers to easily combine and analyse data from different sources, allowing for larger and more robust studies. It increases efficiency, saving time and resources by providing a consistent approach to data organisation and analysis. It can reduce the requirement for specific expertise when analysing and manipulating data. A standardised data model can increase opportunity for collaboration, and it enables results to be more easily reproduced and validated by other researchers.
Will the OMOP CDM replace FHIR or OpenEHR as the preferred interoperability standard?
In short, no. The standards will complement each other, rather than compete. They serve different purposes and have different strengths. FHIR is a framework for exchanging healthcare information between different systems for real-time data access and interoperability. OpenEHR is an open standard that describes management, storage, retrieval and exchange of health data in electronic health records. Both are intended to support operational healthcare processes, whereas the OMOP CDM is intended for research and analysis, and is optimised for data warehousing. Together, FHIR, OpenEHR and the OMOP CDM can contribute to a holistic ecosystem for healthcare informatics. Striving for standardised data from the outset (i.e. the use of FHIR or OpenEHR in real-time), will lead to data which is easier to transform into the OMOP model for research, resulting in increased quality and more accurate insights.
Is there a catch?
All healthcare standardisation frameworks come with their own set of challenges, and the OMOP CDM is no exception. Careful consideration needs to be given as to how data is transformed, for example, factoring in the data quality, retention of context, international vs local definitions and interpretations and use of vocabulary. However, this is not an insurmountable challenge and we’ll explore this further in our next post. The OMOP model has wide community support and the OHDSI initiative provides a number of open-source tools available to assist with implementation.
Interested in the OMOP model or already implementing it? Here at Answer Digital, we are keen to collaborate across communities, so if you would like to hear more then please get in touch, and stay tuned for updates on our work!