Waiting times for inpatient CT after the introduction of a five-level priority system: a retrospective quality-control study in a Swiss tertiary-care centre

Objectives: Inpatient computed tomography (CT) is frequently scheduled on a first-come, first-served basis with fixed slots and remains under-studied relative to emergency and outpatient imaging. We described waiting times for inpatient CT after the introduction of a five-level priority system (P1–P5), with the institutional historical dashboard value reported separately for context. Methods: Single-centre, retrospective quality-control study with a contextual historical comparison in the inpatient CT pathway of a Swiss tertiary-care hospital. A five-level priority system (P1, immediate, to P5, not urgent) was introduced on 1 May 2025. The post-implementation period (1 May to 31 July 2025) was compared with the same calendar window in 2024 as the historical reference. Waiting time was measured as the difference between the request date and the examination date, at calendar-day resolution. The historical dashboard value was reported separately because its measurement definition and inclusion criteria differed from those of the study cohort; placing each priority stratum against it required calibration and was retained only as an exploratory analysis. The ordering of waiting times across strata was assessed by Kruskal–Wallis and Dunn tests, with an urgent (P1–P3) versus non-urgent (P4–P5) contrast. Examinations that were manually accelerated or performed at a fixed time were excluded. Results: Of 1847 examinations screened, 1341 were analysed. Mean waiting time on the measured calendar-day scale was 0.09 days for P1 (n = 11), 0.19 days for P2 (n = 245), 0.49 days for P3 (n = 852), 1.34 days for P4 (n = 214) and 3.00 days for P5 (n = 19); the proportion examined on the same day decreased from 91% for P1 to 5% for P5. Waiting time differed significantly across strata (Kruskal–Wallis p < 0.001), and the urgent strata (P1–P3) waited less than the non-urgent strata (P4–P5) (0.42 vs 1.47 days, difference 1.05 days, p < 0.001). Mean waiting time increased monotonically from P1 to P5. The institutional dashboard reported 1.28 days for the same months in 2024 and 1.06 days in 2025, on its own metric. Conclusions: In this single-centre descriptive evaluation, observed calendar-day intervals increased across the final assigned priority categories from P1 to P5, while same-day examination proportions decreased. The findings describe the post-implementation pattern; they do not establish a causal improvement over the previous scheduling system or demonstrate clinical benefit.

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Publication Details

Journal
Swiss Journal of Radiology and Nuclear Medicine
Published
2026-10-31
DOI
https://doi.org/10.59667/sjoranm.v35i3.14
Primary Topic
Healthcare Operations and Scheduling Optimization
Type
article
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article

Waiting times for inpatient CT after the introduction of a five-level priority system: a retrospective quality-control study in a Swiss tertiary-care centre

Guillaume Fahrni, David Christian Rotzinger, Alban L. Denys, Adrien Jayet
Swiss Journal of Radiology and Nuclear Medicine
Healthcare Operations and Scheduling Optimization
article

Waiting times for inpatient CT after the introduction of a five-level priority system: a retrospective quality-control study in a Swiss tertiary-care centre

Guillaume Fahrni, David Christian Rotzinger, Alban L. Denys, Adrien Jayet
article en

Abstract

Objectives: Inpatient computed tomography (CT) is frequently scheduled on a first-come, first-served basis with fixed slots and remains under-studied relative to emergency and outpatient imaging. We described waiting times for inpatient CT after the introduction of a five-level priority system (P1–P5), with the institutional historical dashboard value reported separately for context. Methods: Single-centre, retrospective quality-control study with a contextual historical comparison in the inpatient CT pathway of a Swiss tertiary-care hospital. A five-level priority system (P1, immediate, to P5, not urgent) was introduced on 1 May 2025. The post-implementation period (1 May to 31 July 2025) was compared with the same calendar window in 2024 as the historical reference. Waiting time was measured as the difference between the request date and the examination date, at calendar-day resolution. The historical dashboard value was reported separately because its measurement definition and inclusion criteria differed from those of the study cohort; placing each priority stratum against it required calibration and was retained only as an exploratory analysis. The ordering of waiting times across strata was assessed by Kruskal–Wallis and Dunn tests, with an urgent (P1–P3) versus non-urgent (P4–P5) contrast. Examinations that were manually accelerated or performed at a fixed time were excluded. Results: Of 1847 examinations screened, 1341 were analysed. Mean waiting time on the measured calendar-day scale was 0.09 days for P1 (n = 11), 0.19 days for P2 (n = 245), 0.49 days for P3 (n = 852), 1.34 days for P4 (n = 214) and 3.00 days for P5 (n = 19); the proportion examined on the same day decreased from 91% for P1 to 5% for P5. Waiting time differed significantly across strata (Kruskal–Wallis p < 0.001), and the urgent strata (P1–P3) waited less than the non-urgent strata (P4–P5) (0.42 vs 1.47 days, difference 1.05 days, p < 0.001). Mean waiting time increased monotonically from P1 to P5. The institutional dashboard reported 1.28 days for the same months in 2024 and 1.06 days in 2025, on its own metric. Conclusions: In this single-centre descriptive evaluation, observed calendar-day intervals increased across the final assigned priority categories from P1 to P5, while same-day examination proportions decreased. The findings describe the post-implementation pattern; they do not establish a causal improvement over the previous scheduling system or demonstrate clinical benefit.

Swiss Journal of Radiology and Nuclear MedicineVol. 35(3)
Centre Hospitalier Universitaire Vaudois (CH), University of Lausanne (CH)
Openalex Percentile: Top 7%
Healthcare Operations and Scheduling Optimization
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