Zhang JW. Letter to the Editor: Dedicated consult shifts as a catalyst for resolving diagnostic disagreements in radiology quality assurance. World J Clin Cases 2026; 14(15): 119818 [DOI: 10.12998/wjcc.v14.i15.119818]
Corresponding Author of This Article
Jin-Wei Zhang, PhD, Principal Investigator, Professor, State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, No. 345 Lingling Road, Shanghai 200032, China. jinweizhang@sioc.ac.cn
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Biology
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May 26, 2026 (publication date) through May 12, 2026
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World Journal of Clinical Cases
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2307-8960
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Zhang JW. Letter to the Editor: Dedicated consult shifts as a catalyst for resolving diagnostic disagreements in radiology quality assurance. World J Clin Cases 2026; 14(15): 119818 [DOI: 10.12998/wjcc.v14.i15.119818]
World J Clin Cases. May 26, 2026; 14(15): 119818 Published online May 26, 2026. doi: 10.12998/wjcc.v14.i15.119818
Letter to the Editor: Dedicated consult shifts as a catalyst for resolving diagnostic disagreements in radiology quality assurance
Jin-Wei Zhang
Jin-Wei Zhang, State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China
Author contributions: Zhang JW designed the overall concept and outline of the manuscript; Zhang JW contributed to the discussion and design of the manuscript; Zhang JW contributed to the writing and editing of the manuscript, illustrations, and review of the literature.
Supported by National Natural Science Foundation of China, No. 82170406 and No. 81970238.
Conflict-of-interest statement: The author declares that there are no conflicts of interest related to this work.
AI contribution statement: AI-assisted language polishing tools were used to refine the manuscript’s English expression, and we provide full transparency on the tool used and its specific role below: Tool name: Grammarly (Premium version, https://www.grammarly.com). The only AI tool used in the entire manuscript preparation process was Grammarly (Premium), and its use was strictly limited to language polishing and grammatical refinement (no substantive scientific content changes).
Corresponding author: Jin-Wei Zhang, PhD, Principal Investigator, Professor, State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, No. 345 Lingling Road, Shanghai 200032, China. jinweizhang@sioc.ac.cn
Received: February 7, 2026 Revised: February 13, 2026 Accepted: March 3, 2026 Published online: May 26, 2026 Processing time: 95 Days and 1.3 Hours
Abstract
Timely resolution of diagnostic disagreements is a cornerstone of effective radiology quality assurance, particularly within imaging-intensive clinical trial environments. In the recent issue of World Journal of Clinical Cases, Virarkar et al evaluated the operational impact of implementing a dedicated consult shift supported by real-time dashboard monitoring within a quantitative imaging analysis core. By comparing disagreement resolution times across pre- and post-implementation periods spanning 2017-2025, the authors demonstrated a marked and statistically significant reduction in both mean and median time to resolution. This editorial contextualizes these findings within the broader literature on radiology workflow optimization, diagnostic error mitigation, and quality assurance frameworks. The study underscores how structured process redesign, combined with digital infrastructure and defined accountability, can meaningfully enhance operational efficiency and reliability. Beyond local impact, the intervention provides a scalable model for radiology departments seeking to reduce diagnostic delays while preserving accuracy and collaborative oversight.
Core Tip: The introduction of a dedicated consult shift, integrated with real-time dashboard surveillance, represents a pragmatic and scalable strategy to address delays in resolving diagnostic disagreements. The substantial reductions in resolution time reported by Virarkar et al highlight how structured accountability and workflow redesign can strengthen radiology quality assurance without compromising diagnostic rigor.
