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Table 1 A summary of the challenges faced by epidemiologists when conducting electronic health record-based research, their manifestations in terms of threats to validity, and potential solutions

From: A narrative review on the validity of electronic health record-based research in epidemiology

Challenge Sub-challenge Example Threat(s) to validity Potential solution(s)
#1 Representativeness -- Catchment of a federally qualified health center versus academic medical center Selection bias and generalizability Comparison to external data; Inverse probability weighting for selection bias
#2 Data availability and interpretation 2.1 Billing versus Clinical versus Epidemiological Needs Presence or absence of diagnostic codes Information bias and confounding Validation study; quantitative bias analysis
2.2 Consistency in Data and Interpretation Variations in reported laboratory results Information bias and confounding Validation study; quantitative bias analysis
2.3 Unstructured Data: Clinical Notes and Reports Operationalizing phenotypes from the encounter note Information Bias and confounding Natural language processing
#3 Missing measurements -- Socioeconomic status not captured Information or Selection Bias, Confounding Imputation, Surrogate Measures, Validation Study
#4 Missing visits -- Lack of longitudinal view of patient Information or Selection Bias Imputation, Surrogate Measures, Validation Study