PURPOSE: To describe the methods used to identify and validate congenital malformation diagnoses recorded in UK electronic health records, and the results of validation studies. METHODS: Medline and Embase were searched for publications between 1987 and 2019 that involved identifying congenital malformations from UK electronic health records using diagnostic codes. The methods and code-lists used to identify congenital malformations, and the methods and results of validations, were examined. RESULTS: We retrieved 54 eligible studies; 36 identified congenital malformations from primary care data and 18 from secondary care data alone or in combination with birth and/or death records. Identification in secondary care data relied on codes from the 'Q' chapter for congenital malformations in ICD-10. In contrast, studies using primary care data frequently used additional codes outside of the 'P' chapter for congenital malformation diagnoses in Read, although the exact codes used were not always clear. Eight studies validated diagnoses identified in primary care data. The positive predictive value was highest (80%-100%) for congenital malformations overall, major malformations, and heart defects although the validity of the reference standard used was often uncertain. It was lowest for neural tube defects (71%) and developmental hip dysplasia (56%). CONCLUSIONS: Studies identifying congenital malformations from primary care data provided limited details about the methods used. The few validation studies were limited to diagnoses recorded in primary care. Further assessments of all measures of validity in both data sources and of other malformation subgroups are needed, using robust reference standards and adhering to reporting guidelines.