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Objective: To compare rates of patient-reported kidney stone disease to Electronic Health Records (EHR) kidney stone diagnosis using a common dataset to evaluate for socio-demographic differences, including between those with and without active care.Methods: From the All of Us research database, we identified 21,687 adult participants with both patient-reported and EHR data.  We compared differences in age, sex, race, education, employment status and healthcare access between patients with self-reported kidney stone history without EHR data to those with EHR-based diagnoses.Results: In this population, the self-reported prevalence of kidney stones was 8.6% overall (n=1877), including 4.6% (n=1004) who had self-reported diagnoses but no EHR data. Among those with self-reported kidney stone diagnoses only, the median age was 66. The EHR-based prevalence of kidney stones was 5.7% (n=1231), median age 67. No differences were observed in age, sex, education, employment status, rural/urban status, or ability to afford healthcare between groups with EHR diagnosis or self-reported diagnosis only. Of patients who had a self-reported history of kidney stones, 24% reported actively seeing a provider for kidney stones.Conclusions: Kidney stone prevalence by self-report is higher than EHR-based prevalence in this national dataset. Using either method alone to estimate kidney stone prevalence may exclude some patients with the condition, although the demographic profile of both groups is similar.  Approximately one in four patients report actively seeing a provider for stone disease. [ABSTRACT FROM AUTHOR]

Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Competing Interests: Declaration of Competing Interest The author has no conflict of interest to declare.

Goal: We present a new framework for in vivo image guidance evaluation and provide a case study on robotic partial nephrectomy. Methods: This framework (called the "bystander protocol") involves two surgeons, one who solely performs the therapeutic process without image guidance, and another who solely periodically collects data to evaluate image guidance. This isolates the evaluation from the therapy, so that in-development image guidance systems can be tested without risk of negatively impacting the standard of care. We provide a case study applying this protocol in clinical cases during robotic partial nephrectomy surgery. Results: The bystander protocol was performed successfully in 6 patient cases. We find average lesion centroid localization error with our IGS system to be 6.5 mm in vivo compared to our prior result of 3.0 mm in phantoms. Conclusions: The bystander protocol is a safe, effective method for testing in-development image guidance systems in human subjects., (© 2023 The Authors.)