Rationale and Design of the Registry for Stones of the Kidney and Ureter (ReSKU): A Prospective Observational Registry to Study the Natural History of Urolithiasis Patients

肾结石和输尿管结石登记研究(ReSKU)的理论基础和设计:一项前瞻性观察性登记研究,旨在研究泌尿系结石患者的自然病程

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Abstract

OBJECTIVES: Registry-based clinical research in nephrolithiasis is critical to advancing quality in urinary stone disease management and ultimately reducing stone recurrence. A need exists to develop Health Insurance Portability and Accountability Act (HIPAA)-compliant registries that comprise integrated electronic health record (EHR) data using prospectively defined variables. An EHR-based standardized patient database-the Registry for Stones of the Kidney and Ureter (ReSKU™)-was developed, and herein we describe our implementation outcomes. MATERIALS AND METHODS: Interviews with academic and community endourologists in the United States, Canada, China, and Japan identified demographic, intraoperative, and perioperative variables to populate our registry. Variables were incorporated into a HIPAA-compliant Research Electronic Data Capture database linked to text prompts and registration data within the Epic EHR platform. Specific data collection instruments supporting New patient, Surgery, Postoperative, and Follow-up clinical encounters were created within Epic to facilitate automated data extraction into ReSKU. RESULTS: The number of variables within each instrument includes the following: New patient-60, Surgery-80, Postoperative-64, and Follow-up-64. With manual data entry, the mean times to complete each of the clinic-based instruments were (minutes) as follows: New patient-12.06 ± 2.30, Postoperative-7.18 ± 1.02, and Follow-up-8.10 ± 0.58. These times were significantly reduced with the use of ReSKU structured clinic note templates to the following: New patient-4.09 ± 1.73, Postoperative-1.41 ± 0.41, and Follow-up-0.79 ± 0.38. With automated data extraction from Epic, manual entry is obviated. CONCLUSIONS: ReSKU is a longitudinal prospective nephrolithiasis registry that integrates EHR data, lowering the barriers to performing high quality clinical research and quality outcome assessments in urinary stone disease.

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