Cellular electrophysiology underpins fields from basic science in neurology, cardiology, and oncology to safety critical applications for drug safety testing, risk assessment of rare mutations, and models based on cellular electrophysiology data even guide clinical interventions. Patch-clamp voltage clamp is the gold standard for measuring ionic current dynamics that explain cellular electrophysiology, but recordings can be influenced by artifacts introduced by the measurement process. A computational approach is developed, validated through electrical model cell experiments, to explain and predict intricate artifacts in voltage-clamp experiments. Applied to various cardiac fast sodium current measurements, the model resolved artifacts in the experiments by coupling observed current with simulated membrane voltage, explaining some typically observed shifts and delays in recorded currents. It is shown that averaging data for current-voltage relationships can introduce biases comparable to effect sizes reported for disease-causing mutations. The computational pipeline provides improved assessment and interpretation of voltage-clamp experiments, correcting, and enhancing understanding of ion channel behavior.