Abstract Insomnia is a highly prevalent condition that significantly degrades the quality of life and health of millions of patients. By diagnostic definition, insomnia is a disease characterized by self-reported subjective criteria, thus therapeutic developers targeting insomnia typically evaluate their treatment’s efficacy based on patient reported outcomes in the form of sleep diaries. A critical flaw with this assessment approach is that self-perception of sleep is inherently noisy due to the inability of patients to perceive the transition to and from unconscious sleep and sources of variability related to bias, mood, and other contextual factors. To overcome this limitation, many clinical trials incorporate clinically validated wearable devices into their trials as surrogate assessments which are interpreted in conjunction with sleep diary data. Wearable devices are also imperfect tools to assess sleep because they are similarly limited by non-disease, non-treatment related factors including imperfect operation, imperfect algorithms, and misuse. Furthermore, numerous studies in clinical and non-clinical populations have demonstrated that there are significant discrepancies between sleep diaries and wearable device derived sleep metrics raising the question as to which assessment approach is valid. Without a method to reconcile differences between sleep diaries and wearable devices the current practice for clinical trials is to rely on sleep diary data which is suboptimal and may contribute to blunted or nonsignificant effects in trials. The improved patient reported outcome (iPRO) – Sleep Diary is a method and system designed to improve sleep assessment by combining sleep diary and wearable device data while maintaining the subjectivity of sleep assessment. The proposed solution is to provide patients their wearable device-derived sleep data contemporaneously with the completion of the sleep diary. The patient reported sleep diary measurement is still the outcome of interest, however patients have the freedom to incorporate or disregard their objective data in their assessment. This approach is inspired by signal processing theory where measurements from two sensors with uncorrelated sources of error (sleep diary and wearable device) are combined to improve the measurement of the underlying signal. The approach of providing patients their objective data and then using their sleep diary response (in contrast to averaging) is used to preserve patient autonomy and leverage the benefits of self-reported data. Preliminary data suggest the iPRO-Sleep Diary non-linearly improves measurement precision of sleep metrics and reduces discrepancy between device and sleep diary data. This platform technology is expected to improve the assessment of sleep in clinical trials and enable more efficient development of effective therapeutics.