Literature DB >> 19788480

The Royal Australian and New Zealand College of Radiologists (RANZCR) relative value unit workload model, its limitations and the evolution to a safety, quality and performance framework.

A Pitman1, D N Jones, D Stuart, K Lloydhope, K Mallitt, P O'Rourke.   

Abstract

The study reports on the evolution of the Australian radiologist relative value unit (RVU) model of measuring radiologist reporting workloads in teaching hospital departments, and aims to outline a way forward for the development of a broad national safety, quality and performance framework that enables value mapping, measurement and benchmarking. The Radiology International Benchmarking Project of Queensland Health provided a suitable high-level national forum where the existing Pitman-Jones RVU model was applied to contemporaneous data, and its shortcomings and potential avenues for future development were analysed. Application of the Pitman-Jones model to Queensland data and also a Victorian benchmark showed that the original recommendation of 40,000 crude RVU per full-time equivalent consultant radiologist (97-98 baseline level) has risen only moderately, to now lie around 45,000 crude RVU/full-time equivalent. Notwithstanding this, the model has a number of weaknesses and is becoming outdated, as it cannot capture newer time-consuming examinations particularly in CT. A significant re-evaluation of the value of medical imaging is required, and is now occurring. We must rethink how we measure, benchmark, display and continually improve medical imaging safety, quality and performance, throughout the imaging care cycle and beyond. It will be necessary to ensure alignment with patient needs, as well as clinical and organisational objectives. Clear recommendations for the development of an updated national reporting workload RVU system are available, and an opportunity now exists for developing a much broader national model. A more sophisticated and balanced multidimensional safety, quality and performance framework that enables measurement and benchmarking of all important elements of health-care service is needed.

Entities:  

Mesh:

Year:  2009        PMID: 19788480     DOI: 10.1111/j.1754-9485.2009.02094.x

Source DB:  PubMed          Journal:  J Med Imaging Radiat Oncol        ISSN: 1754-9477            Impact factor:   1.735


  4 in total

1.  What is the relation between number of sessions worked and productivity of radiologists-a pilot study?

Authors:  Shah H M Khan; William P Hedges
Journal:  J Digit Imaging       Date:  2016-04       Impact factor: 4.056

2.  Measuring radiologist workload: how to do it, and why it matters.

Authors:  Adrian P Brady
Journal:  Eur Radiol       Date:  2011-07-06       Impact factor: 5.315

3.  Covid-MANet: Multi-task attention network for explainable diagnosis and severity assessment of COVID-19 from CXR images.

Authors:  Ajay Sharma; Pramod Kumar Mishra
Journal:  Pattern Recognit       Date:  2022-06-06       Impact factor: 8.518

4.  Measuring Consultant Radiologist workload: method and results from a national survey.

Authors:  Adrian P Brady
Journal:  Insights Imaging       Date:  2011-04-21
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.