Development and Implementation of a Multisite Registry Using Structured Templates for Actionable Findings in the Kidney

Tessa S. Cook, Rebecca Paulus, Laura B. Gillis, Charles Chambers, Sujith S. Nair, Sandeep Deshmukh, Nabeel I. Sarwani, Hanna M. Zafar

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Purpose: The aim of this study was to scale structured report templates categorizing actionable renal findings across health systems and create a centralized registry of patient and report data. Methods: In January 2017, three academic radiology departments agreed to prospectively include identical structured templates categorizing the malignant likelihood of renal findings in ≥90% of all adult ultrasound, MRI, and CT reports, a new approach for two sites. Between November 20, 2017, and September 30, 2019, deidentified HL7 report data were transmitted to a centralized ACR registry. An automated algorithm extracted categories. Radiologists were requested to addend reports with missing or incomplete templates after the first month. Separately, each site submitted patient sociodemographic and clinical data 12 months before and at least 3 months after enrollment. Results: A total of 164,982 eligible radiology reports were transmitted to the registry; 4,159 (2.5%) were excluded because of missing categories or radiologist names. The final cohort included 160,823 examinations on 102,619 unique patients. Mean template use before and after addendum requests was 99.3% and 99.9% at SITE1, 86.5% and 94.6% at SITE2, and 91.4% and 96.0% at SITE3. Matching patient sociodemographic and clinical data were obtained on 96.9% of reports from SITE1, 94.2% from SITE2, and 96.0% from SITE3. Regulatory, cultural, and technology barriers to the creation of a multisite registry were identified. Conclusions: Barriers to the adoption of unified structured report templates for actionable kidney findings can be addressed. Deidentified report and patient data can be securely transmitted to an external registry. These data can facilitate the collection of diverse evidence-based population imaging outcomes.

Original languageEnglish (US)
Pages (from-to)637-646
Number of pages10
JournalJournal of the American College of Radiology
Volume19
Issue number5
DOIs
StatePublished - May 2022

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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