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. 2023 Feb 3;18(2):e0281327.
doi: 10.1371/journal.pone.0281327. eCollection 2023.

Imaging delays among medical inpatients in Toronto, Ontario: A cohort study

Emily Bartsch  1 , Saeha Shin  2 , Surain Roberts  2 , Thomas E MacMillan  1   3 , Michael Fralick  1   4 , Jessica J Liu  1   5 , Terence Tang  1   6 , Janice L Kwan  1   4 , Adina Weinerman  1   7 , Amol A Verma  1   2   8   9 , Fahad Razak  1   2   8   9 , Lauren Lapointe-Shaw  1   5   9
Affiliations

Imaging delays among medical inpatients in Toronto, Ontario: A cohort study

Emily Bartsch et al. PLoS One. .

Abstract

Background: Imaging procedures are commonly performed on hospitalized patients and waiting for these could increase length-of-stay. The study objective was to quantify delays for imaging procedures in General Internal Medicine and identify contributing patient, physician, and system factors.

Methods: This was a retrospective cohort study of medical inpatients admitted to 5 hospitals in Toronto, Ontario (2010-2019), with at least one imaging procedure (CT, MRI, ultrasound, or peripherally-inserted central catheter [PICC] insertion). The primary outcome was time-to-test, and the secondary outcome was acute length-of-stay after test ordering.

Results: The study cohort included 73,107 hospitalizations. Time-to-test was longest for MRI (median 22 hours) and shortest for CT (median 7 hours). The greatest contributors to time-to-test were system factors such as hospital site (up to 22 additional hours), location of test ordering (up to 10 additional hours), the timing of test ordering relative to admission (up to 13 additional hours), and ordering during weekends (up to 21 additional hours). Older patient age, having more comorbidities, and residence in a low-income neighborhood were also associated with testing delays. Each additional hour spent waiting for a test was associated with increased acute length-of-stay after test ordering, ranging from 0.4 additional hours for CT to 1.2 hours for MRI.

Conclusions: The greatest contributors to testing delays relate to when and where a test was ordered. Wait times affect length-of-stay and the quality of patient care. Hospitals can apply our novel approach to explore opportunities to decrease testing delays locally.

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Conflict of interest statement

I have read the journal’s policy and the authors of this manuscript have the following competing interests: Lauren Lapointe-Shaw is supported by the University of Toronto Department of Medicine, the Toronto General Hospital Research Institute, the Women’s College Institute for Health System Solutions and Virtual Care (WIHV) and the Peter Gilgan Centre for Women’s Cancers at Women’s College Hospital, in partnership with the Canadian Cancer Society. Amol Verma and Fahad Razak are part-time employees of Ontario Health, outside of the submitted work. The development of the GEMINI data platform has been supported with funding from the Canadian Cancer Society, the Canadian Frailty Network, the Canadian Institutes of Health Research, the Canadian Medical Protective Agency, Green Shield Canada Foundation, the Natural Sciences and Engineering Research Council of Canada, Ontario Health, the St. Michael’s Hospital Association Innovation Fund, the University of Toronto Department of Medicine, and in-kind support from partner hospitals and the Vector Institute. Fahad Razak holds a salary award from the Mak Pak Chiu and Mak-Soo Lai Hing Chair in General Internal Medicine, University of Toronto and the PSI Graham Farquharson Knowledge Translation Fellowship. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Hospital-specific adjusted time-to-test (median, hours, +/- 95% confidence intervals) for imaging procedures for patients admitted to General Internal Medicine.
Note: Hospital B did not contribute information on time to MRI as it uses a paper-based ordering system.
See this image and copyright information in PMC

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