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Published on: October 6, 2023
Optimising radiology workflow in a high-volume academic medical centre: a multi-phase, data-driven quality
Divyansh Gupta1, Parul Gupta2, Naman Gupta2
1Department of Radiodiagnosis, Sawai ManSingh Medical College and Hospital, Jaipur, India. drdivyanshrad@gmail.com.
Purpose:
High-volume public radiology departments face multifactorial workflow challenges driven by fragmented digital infrastructure and high imaging demand under state-sponsored health coverage programmes. We aimed to evaluate a multi-phase quality improvement initiative targeting pre-scan, scan and post-scan bottlenecks in CT and MRI services at a publicly funded, PPP-operated tertiary academic centre.
Methods:
A pre-post study using the Plan-Do-Study-Act framework was conducted per SQUIRE 2.0. A multidisciplinary team implemented 13 targeted interventions across three workflow phases. Outcomes were compared by independent-samples t-tests, Wilcoxon rank-sum tests, and chi-square or Fisher exact tests; process stability was assessed with Shewhart X-bar control charts (α = 0.05).
Results:
CT registration-to-scan time decreased from 2.1 to 1.2 h (-43%) and MRI waiting time from 10.2 to 4.8 h (-53%), both p < 0.001. Manual registration delay fell from 17 to 6 min per examination (-65%, p < 0.001). Reporting backlog dropped from 26 to 9 h and critical-result turnaround from 90 to 40 min (both p < 0.001). Protocol omission decreased from 15.4% to 5.2% (p < 0.001). Median staff burnout decreased from 7.0 to 4.0 and patient satisfaction rose from 58% to 82% (both p < 0.001). Study-unit throughput increased 20.2% (p < 0.001). Improvements were stable across the post-intervention window.
Conclusion:
A structured, low-cost, multi-phase QI initiative demonstrated statistically significant improvements in workflow efficiency, diagnostic completeness, staff well-being and patient experience without capital equipment investment, with process stability demonstrated over the short-term observation window. The framework is replicable in resource-constrained academic radiology departments with similar PPP arrangements.
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