USDHub: community resource for Urinary Stone Disease research

ABSTRACT Urinary stone disease (USD) is highly prevalent and contributes a substantial proportion of healthcare costs related to kidney and urologic disease. Approximately half of children and adults suffer recurrent symptomatic stone events, resulting in emergency department visits and surgery. More than a condition with episodic

occurrence of debilitating events, USD is a disorder of mineral metabolism with substantial morbidity, including increased future risk of chronic kidney disease, fracture, hypertension, and cardiovascular disease. Despite the high prevalence and burden of USD, advances in the understanding, treatment, and prevention of USD have

stalled due to deficiencies in available data resources. These critical gaps include lack of clinically important information, lack of longitudinal data, reliance on single-center designs that segregate pediatric and adult patients, and exclusion of key stakeholders in database design. To address this need, this proposal creates the

Urinary Stone Disease Hub (USDHub), a readily accessible research resource for the broad research community that would support a wide range of impactful clinical investigation to improve the health of children and adults with USD. USDHub will generated from 10 health systems in the United States that participate in STAR and

PEDSnet, two PCORnet clinical research networks that have standardized electronic health record data. We will ensure that the content and structure of USDHub has value to the USD research community by including stakeholders, including patients and caregivers. This work will include the following three Aims: First, we will

create a research cohort of >230,000 individuals across the lifespan with USD. We will link extant structured data from the PCORnet common data model to 24-hour urine results and stone composition data. Second, we will enrich USDHub with information extracted from CT images and clinical notes using natural language

processing and machine learning methods. Third, we will broadly disseminate USDHub to researchers using sustainable data access model. We will partner the USD research community to user test and refine the data access process. To maximize USDHub’s impact, we will provide pilot grants, clinics to orient researchers to

USDHub data, and partner with professional organizations to disseminate USDHub to the broader USD research communities. The outcome of this work will be a new research ecosystem for investigators to generate impactful real-world knowledge that will transform the way USD research is conducted and thereby improve care and

outcomes for the growing number of individuals living with the disease. This resource will spur and accelerate hypothesis-testing research and lead to impactful and clinically meaningful discoveries that improve the health of individuals and populations with USD across the lifespan.