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Real‐world data in Saudi Arabia: Current situation and challenges for regulatory decision‐making
Author(s) -
Alnofal Fatemah A.,
Alrwisan Adel A.,
Alshammari Thamir M.
Publication year - 2020
Publication title -
pharmacoepidemiology and drug safety
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.023
H-Index - 96
eISSN - 1099-1557
pISSN - 1053-8569
DOI - 10.1002/pds.5025
Subject(s) - medicine , observational study , general partnership , informatics , health informatics , pharmacoepidemiology , data quality , medical record , medical emergency , family medicine , data science , public health , nursing , computer science , business , pathology , metric (unit) , finance , marketing , medical prescription , electrical engineering , radiology , engineering
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.