Use cases

STUDY: Transforming Estonian health data to the Observational Medical Outcomes Partnership (OMOP) Common Data Model

Objective: This study aimed to describe the reusable transformation process of electronic health records (EHR), claims, and prescriptions data into Observational Medical Outcome Partnership (OMOP) Common Data Model (CDM), together with challenges faced and solutions implemented, by making use of Estonian national health databases.

Conclusion: Complete records from 3 national health databases were successfully transferred to OMOP CDM and created a reusable transformation process. This work will help future researchers to transform linked databases into OMOP CDM more efficiently, ultimately leading to better real-world evidence.

More information can be found in the blog and in the article published in JAMIA Open.

NETWORK STUDY: Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data

Objective: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process.

Conclusions: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost–benefit of integrating these analyses at this stage of signal management requires further research.

Read the full article published in Drug Safety.

 

Study: Background Rates of AESI for Vaccines

Objective: The largest, most extensive global network study (~126mio people in 8 countries) on background rates for AESIs (Adverse Events of Special Interest) identifies important age, sex and database differences to inform future surveillance efforts.

Conclusions: This study found large variations in the observed rates of AESIs by age group and sex, showing the need for stratification or standardisation before using background rates for safety surveillance. Considerable population heterogeneity in AESI rates was found between databases.

Link to this paper for detailed results.

Health Technology Assessment (HTA) Use Case: Chronic Obstructive Pulmonary Disease (COPD)

Objectives:

  • Understand the extent to which the OMOP common data model and standardised analytical tools support evidence generation for HTA of chronic diseases.
  • Assess the extent to which current ETL processes support common HTA use cases.
  • Assess the ability to generate reliable evidence for multiple jurisdictions.
  • Identify priority areas for further developments to the common data model or analytical tools to support such applications.

Conclusions:

  • Ensure use of data for HTA purposes is reflected in data processing and mapping processes and ensure HTA experts are involved in the ETL process.
  • Map visits in a way that reflects the specificity of healthcare delivery in different settings, e.g., distinguishing between primary and secondary care.
  • Development of analytical tools to support common analyses for HTA purposes

Complete results can be found in this abstract.