IMPLEMENTING A COMMON DATA MODEL TO STUDY RARE DISEASE: A METHODOLOGICAL FRAMEWORK FOR THROMBOTIC MICROANGIOPATHIES IN GREECE
Author(s)
Alexandros Rekkas, PhD1, Anastasia Farmaki, MS1, Antonia Sipaki, MS1, Achilleas Chytas, PhDc1, Dorothea Papadopoulou, MD2, Anna Kioumi, MD2, Parthena Kyriklidou, MD2, Panagiotis Pateinakis, MD2, Eleni Manou, MD2, Gousiaris Dimitrios-Fotios, MD2, Lambros Dermentzoglou, PhD2, Dimitrios Zeimpekis, PhD2, GEORGIOS IOANNIS TORTOPIDIS, MSc2, Maria Bigaki, MBA2, Nikolas Mathioudakis, PhD3, ZOE PAPAREPA, MSc3, Evangelos Chandakas, PhD4, Alexandros Sfikas, PhD3, Antonios Petropoulos, PhD3, Pantelis Natsiavas, PhD5.
1Centre for Research and Technology Hellas, CERTH, Thessaloniki, Greece, 2Papageorgiou General Hospital, Thessaloniki, Greece, 3AstraZeneca, Athens, Greece, 4AstraZeneca, London, United Kingdom, 5Centre for Research and Technology Hellas, CERTH, Thessaloniki, Greece, Greece.
1Centre for Research and Technology Hellas, CERTH, Thessaloniki, Greece, 2Papageorgiou General Hospital, Thessaloniki, Greece, 3AstraZeneca, Athens, Greece, 4AstraZeneca, London, United Kingdom, 5Centre for Research and Technology Hellas, CERTH, Thessaloniki, Greece, Greece.
OBJECTIVES: (1) To establish a standardized framework for the design, execution, and evaluation of observational studies; (2) To apply this framework in a characterization study of thrombotic microangiopathies (TMAs) in Greece.
METHODS: This is a retrospective analysis between January 2004 and December 2024 with data from the Electronic Health Records (EHR) of Papageorgiou General Hospital, comprising 30 clinics, 9 collaborative departments, and 10 laboratory centers, accommodating over 220,000 hospitalization days, 15,000 surgeries, and 1,200 daily outpatient visits annually was used. We defined TMAs using OMOP-CDM condition codes (Thrombotic microangiopathy: 313800 and Hemolytic uremic syndrome: 197253). Analyses were descriptive in nature. Continuous variables were summarized using means, standard deviations (SD), medians, and interquartile ranges (IQR). Categorical variables were summarized using frequencies and percentages. Incidence and prevalence rates were calculated per 100,000-person years and reported with 95% Confidence Intervals (CIs). The cohort was designed using OHDSI ATLAS, an open-source web application developed by the Observational Health Data Sciences and Informatics (OHDSI) community. Data extraction and statistical analyses were conducted in R, using open-source packages from the OHDSI HADES software suite, including CohortGenerator and CohortDiagnostics R-packages for cohort extraction and diagnostic assessment. Free-text clinical notes were manually reviewed and abstracted by healthcare professionals, who extracted relevant information in a structured format designed to align with the OMOP Common Data Model.
RESULTS: The study identified 49 patients, corresponding to 74 hospitalizations. Among these hospitalizations, 24% had a confirmed diagnosis of HUS, whereas 76% corresponded to other TMAs.
CONCLUSIONS: To our knowledge, this study is the first implementation in Greece of a standardized OMOP-CDM/OHDSI-based observational framework in the context of a rare disease enabling systematic characterization of TMA patients and establishing a reproducible framework for multi-center EHR studies.
METHODS: This is a retrospective analysis between January 2004 and December 2024 with data from the Electronic Health Records (EHR) of Papageorgiou General Hospital, comprising 30 clinics, 9 collaborative departments, and 10 laboratory centers, accommodating over 220,000 hospitalization days, 15,000 surgeries, and 1,200 daily outpatient visits annually was used. We defined TMAs using OMOP-CDM condition codes (Thrombotic microangiopathy: 313800 and Hemolytic uremic syndrome: 197253). Analyses were descriptive in nature. Continuous variables were summarized using means, standard deviations (SD), medians, and interquartile ranges (IQR). Categorical variables were summarized using frequencies and percentages. Incidence and prevalence rates were calculated per 100,000-person years and reported with 95% Confidence Intervals (CIs). The cohort was designed using OHDSI ATLAS, an open-source web application developed by the Observational Health Data Sciences and Informatics (OHDSI) community. Data extraction and statistical analyses were conducted in R, using open-source packages from the OHDSI HADES software suite, including CohortGenerator and CohortDiagnostics R-packages for cohort extraction and diagnostic assessment. Free-text clinical notes were manually reviewed and abstracted by healthcare professionals, who extracted relevant information in a structured format designed to align with the OMOP Common Data Model.
RESULTS: The study identified 49 patients, corresponding to 74 hospitalizations. Among these hospitalizations, 24% had a confirmed diagnosis of HUS, whereas 76% corresponded to other TMAs.
CONCLUSIONS: To our knowledge, this study is the first implementation in Greece of a standardized OMOP-CDM/OHDSI-based observational framework in the context of a rare disease enabling systematic characterization of TMA patients and establishing a reproducible framework for multi-center EHR studies.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
SA53
Topic
Epidemiology & Public Health, Real World Data & Information Systems, Study Approaches
Disease
Rare & Orphan Diseases, Systemic Disorders/Conditions (Anesthesia, Auto-Immune Disorders (n.e.c.), Hematological Disorders (non-oncologic), Pain), Urinary/Kidney Disorders