Continuous Holter recordings are often used in thorough QT studies (TQTS), with multiple 10-second electrocardiograms (ECGs) visually selected around predesignated time points. The authors hypothesized that computer-automated ECG selection would reduce within-subject variability, improve study data precision, and increase study power. Using the moxifloxacin and placebo arms of a Holter-based crossover TQTS, the authors compared interval duration measurements (IDMs) from manually selected to computer-selected ECGs. All IDMs were made with a fully automated computer algorithm. Moxifloxacin-induced changes in baseline- and placebo-subtracted QT intervals were similar for manual and computer ECG selection. Mean 90% confidence intervals were narrower, and within-subject variability by mixed-model covariance was lower for computer-selected than for manual-selected ECGs. Computer ECG selection reduced the number of subjects needed to achieve 80% power by 40% to 50% over manual. Computer ECG selection returns accurate ddQTcF values with less measurement variability than manual ECG selection by a variety of metrics. This results in increased study power and reduces the number of subjects needed to achieve desired power, which represents a significant potential source cost savings in clinical drug trials.