PURPOSE: To present the process of establishing a pharmacoepidemiological database in Saudi Arabia, challenges and models used. METHODS: The database establishment has started in 2017 by piloting the conversion of electronic health records of one hospital to the Observational Health Data Sciences and Informatics (OHDSI), Observational Medical Outcomes Partnership's Common Data Model (OMOP). RESULTS: During the pilot phase we have faced several challenges such as limited contribution in providing data by local medical institution due to uncertainty about data governance, diversity of systems used by hospitals, inconsistent coding of medical information, and limited awareness about data structure from participating hospital. The pilot phase was completed in 2019 containing information about patient attributes, medical care, therapies, and other additional services for around 130 000 patients in Saudi Arabia. The majority of patients were below the age of 50 years (89%), and acute respiratory infections were the most frequent diagnosis. The data quality was acceptable and no major anomalies were detected during the conversion. CONCLUSIONS: We demonstrated a successful creation of a pilot database using OHDSI Common Data Model. Our experience with the pilot database could be extended to other institutions to create a national dataset that could be used to generate real-world evidence.
PURPOSE: To present the process of establishing a pharmacoepidemiological database in Saudi Arabia, challenges and models used. METHODS: The database establishment has started in 2017 by piloting the conversion of electronic health records of one hospital to the Observational Health Data Sciences and Informatics (OHDSI), Observational Medical Outcomes Partnership's Common Data Model (OMOP). RESULTS: During the pilot phase we have faced several challenges such as limited contribution in providing data by local medical institution due to uncertainty about data governance, diversity of systems used by hospitals, inconsistent coding of medical information, and limited awareness about data structure from participating hospital. The pilot phase was completed in 2019 containing information about patient attributes, medical care, therapies, and other additional services for around 130 000 patients in Saudi Arabia. The majority of patients were below the age of 50 years (89%), and acute respiratory infections were the most frequent diagnosis. The data quality was acceptable and no major anomalies were detected during the conversion. CONCLUSIONS: We demonstrated a successful creation of a pilot database using OHDSI Common Data Model. Our experience with the pilot database could be extended to other institutions to create a national dataset that could be used to generate real-world evidence.