Letter to the Editor: Dedicated consult shifts as a catalyst for resolving diagnostic disagreements in radiology quality assurance

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.

Key Words: Diagnostic disagreement; Radiology workflow; Quality improvement; Consult shift; Quantitative imaging analysis; Turnaround time

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.

TO THE EDITOR

Diagnostic disagreements are an inherent challenge in radiology practice, particularly within complex clinical trial and oncologic imaging environments where accuracy, consistency, and timeliness are equally critical[1,2]. As imaging increasingly drives therapeutic decisions and trial endpoints, delays in adjudicating discrepant interpretations can disrupt workflows, slow trial progression, and potentially affect patient management[3,4]. Historically, resolution of such disagreements has relied on asynchronous communication, periodic review cycles, and informal escalation pathways, all of which are vulnerable to inefficiencies and prolonged turnaround times[5-7].

Recent literature has emphasized that radiology quality improvement must move beyond retrospective error analysis toward proactive, system-level workflow redesign[8]. Against this backdrop, against this backdrop, Virarkar et al[9] provide timely evidence that implementing a dedicated consult shift can substantially improve the efficiency of disagreement resolution within a quality improvement in ambulatory care (QIAC). This letter examines the methodological rigor, contextual relevance, and broader implications of their findings.

Methods

Virarkar et al[9] recently published a study in World Journal of Clinical Cases, in which they conducted a retrospective quality improvement analysis of 1245 diagnostic disagreement cases recorded between 2017 and 2025 within a high-volume academic QIAC. The intervention, introduced in 2023, consisted of a dedicated consult shift supported by real-time dashboard monitoring, enabling immediate notification and adjudication of disagreements by an on-call radiologist and imaging specialist. Time to resolution served as the primary outcome measure, with comparisons made between pre-implementation (2017-2022) and post-implementation (2023-2025) periods. Robust statistical methods, including both parametric and non-parametric testing, were employed to account for non-normal data distributions and to ensure reliability of observed differences.

Key findings

The study by Virarkar et al[9] demonstrated a striking improvement in operational performance following implementation of the consult shift. Mean time to resolution decreased from over 100 days to approximately 33 days, while median resolution time fell from 20.9 days to just over 5 days, representing reductions of greater than 67% and 76%, respectively. These improvements were highly statistically significant and accompanied by a marked reduction in variability, indicating not only faster but also more predictable resolution timelines. Such consistency is particularly valuable in clinical trial imaging, where delays can cascade into protocol deviations and reporting bottlenecks[4,10].

Critical appraisal

The findings of Virarkar et al[9] align closely with prior studies demonstrating that structured workflow interventions can meaningfully improve radiology turnaround times. Earlier work at comprehensive cancer centers showed that digital workflow platforms and alert systems could reduce quantitative imaging report turnaround by nearly 50%, reinforcing the role of technology-enabled process redesign[4,10]. Similarly, international quality improvement initiatives have reported substantial gains in operational efficiency following standardization of radiology workflows and escalation protocols[11].

What distinguishes the present study is its focus on diagnostic disagreement resolution rather than general report turnaround time, an area that has received comparatively less empirical attention despite its importance for quality assurance[2,5]. The observed reduction in variability further strengthens the argument that the consult shift improved system reliability, a key dimension of healthcare quality.

At the same time, implementation of a dedicated consult shift warrants careful consideration of potential unintended consequences. Concentrating disagreement adjudication within a defined shift may redistribute workload across faculty, potentially increasing cognitive load or burnout risk for assigned radiologists. Financial implications, including protected time allocation and staffing coverage, may also affect sustainability, particularly in smaller departments. Furthermore, the success of dashboard-enabled monitoring depends on robust digital infrastructure and institutional culture supporting rapid escalation, conditions that may not be uniformly present across practice settings.

As a single-center retrospective analysis, the study cannot fully exclude the influence of unmeasured confounders such as staffing changes, evolving case complexity, or concurrent quality initiatives. Prospective multicenter validation would strengthen confidence in generalizability and clarify contextual determinants of success.

Future perspectives

The consult shift model described by Virarkar et al[9] has implications well beyond the QIAC setting. Real-time monitoring, defined accountability, and rapid escalation pathways could be adapted to emergency radiology, subspecialty consult services, and teleradiology networks. However, broader implementation will require adaptation to structural variability across institutions, including differences in staffing models, case volumes, informatics capacity, and reimbursement frameworks. Community hospitals or resource-constrained centers may face barriers related to limited subspecialty coverage or lack of integrated dashboard systems. Hybrid models, such as regional consult pooling or shared digital platforms, may offer pragmatic alternatives in such settings.

Future investigations should move beyond operational metrics to evaluate downstream impact. Measurable endpoints could include reductions in protocol deviation rates within clinical trials, frequency of management changes attributable to disagreement adjudication, time to therapeutic decision-making, and stakeholder-reported satisfaction among referring clinicians and radiologists. Additional metrics such as disagreement recurrence rates, variability indices, and cost-effectiveness analyses would provide a more comprehensive assessment of value.

Integrating consult shifts with complementary innovations, such as radiology e-consult services, may further enhance access to expertise while minimizing workflow disruptions[12]. Ultimately, linking workflow redesign to demonstrable improvements in patient-centered and trial-related outcomes will be essential for establishing the consult shift model as a sustainable best practice.

CONCLUSIONS

Virarkar et al[9] provide compelling evidence that a dedicated consult shift, supported by real-time dashboard tracking, can dramatically reduce the time required to resolve diagnostic disagreements in a complex radiology quality assurance environment. The intervention achieved substantial and sustained improvements in both speed and consistency of resolution, reinforcing the value of structured, data-driven workflow redesign. While broader validation across diverse practice settings is warranted, this study offers a practical blueprint for radiology departments seeking to enhance quality, efficiency, and reliability in diagnostic adjudication.