Substitution, delegation or addition? Implications of workforce skill mix on efficiency and interruptions in computed tomography
Andrew K. Cartwright
A B C D G , Tilley Pain E F and David J. Heslop C
A Medical Imaging Department, Townsville University Hospital, Douglas, Qld 4814, Australia.
B College of Medicine and Dentistry, James Cook University, Townsville, Qld 4810, Australia.
C School of Population Health, Faculty of Medicine, UNSW Sydney, NSW 2052, Australia. Email: d.heslop@unsw.edu.au
D Present address: University of Notre Dame Fremantle, School of Medicine, Fremantle, WA 6160, Australia.
E Townsville University Hospital, 100 Angus Smith Drive, Douglas, Qld 4814, Australia. Email: Tilley.pain@health.qld.gov.au
F College of Public Health, Medical and Veterinary Sciences, James Cook University, 1 James Cook Drive, Douglas, Townsville, Qld 4811, Australia.
G Corresponding author. Email: andrew.cartwright@my.nd.edu.au
Australian Health Review 45(3) 382-388 https://doi.org/10.1071/AH20118
Submitted: 1 June 2020 Accepted: 8 September 2020 Published: 11 March 2021
Journal Compilation © AHHA 2021 Open Access CC BY-NC-ND
Abstract
Objectives This study evaluated multiple computed tomography (CT) workforce models to identify any implications on efficiency (length of stay, scan frequency and workforce cost) and scanning radiographer interruptions through substituting or supplementing with a trained CT assistant.
Methods The study was conducted in a CT unit of a tertiary Queensland hospital and prospectively compared four workforce models, including usual practice: Model 1 used an administrative assistant (AA) and one radiographer; Model 2 substituted a medical imaging assistant (MIA) for the AA; Model 3 was usual practice, consisting of two radiographers; and Model 4 included two radiographers, with a supplemented MIA. Observational data were collected over 7 days per model and were cross-checked against electronic records. Data for interruption type and frequency, as well as scan type and duration, were collected. Annual workforce costs were calculated as measures of efficiency.
Results Similar scan frequency and parameters (complexity) occurred across all models, averaging 164 scans (interquartile range 160–172 scans) each. The median times from patient arrival to examination completion in Models 1–4 were 47, 35, 46 and 33 min respectively. There were between 34 and 104 interruptions per day across all models, with the ‘assistant role’ fielding the largest proportion. Model 4 demonstrated the highest workforce cost, and Model 2 the lowest.
Conclusion This study demonstrated that assistant models offer similar patient throughput to usual practice at a reduced cost. Model 2 was the most efficient of all two-staff models (Models 1–3), offering the cheapest workforce, slightly higher throughput and faster examination times. Not surprisingly, the additional staff model (Model 4) offered greater overall examination times and throughput, with fewer interruptions, although workforce cost and possible role ambiguity were both limitations of this model. These findings may assist decision makers in selecting the optimal workforce design for their own individual contexts.
What is known about the topic? Innovative solutions are required to address ongoing health workforce sustainability concerns. Workforce substitution models using trained assistants have demonstrated numerous benefits internationally, with translation to the Australian allied health setting showing promise.
What does this paper add? Building on existing research, this study provides clinical workforce alternatives that maintain patient throughput while offering cost efficiencies. This study also quantified the many daily interruptions that occur within the CT setting, highlighting a potential clinical risk. To the best of our knowledge, this study is the first to empirically test the use of allied health assistants within CT.
What are the implications for practitioners? Role substitution in CT may offer solutions to skills shortages, increasing expenditure and service demand. Incorporating appropriate assistant workforce models can maintain throughput while demonstrating implications for efficiency and interruptions, potentially affecting staff stress and burnout. In addition, the assistant’s scope and accepted level of interruptions should be considerations when choosing the most appropriate model.
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