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

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

The devastating outbreak of Coronavirus Disease (COVID-19) cases in early 2020 led the world to face health crises. Subsequently, the exponential reproduction rate of COVID-19 disease can only be reduced by early diagnosis of COVID-19 infection cases correctly. The initial research findings reported that radiological examinations using CT and CXR modality have successfully reduced false negatives by RT-PCR test. This research study aims to develop an explainable diagnosis system for the detection and infection region quantification of COVID-19 disease. The existing research studies successfully explored deep learning approaches with higher performance measures but lacked generalization and interpretability for COVID-19 diagnosis. In this study, we address these issues by the Covid-MANet network, an automated end-to-end multi-task attention network that works for 5 classes in three stages for COVID-19 infection screening. The first stage of the Covid-MANet network localizes attention of the model to the relevant lungs region for disease recognition. The second stage of the Covid-MANet network differentiates COVID-19 cases from bacterial pneumonia, viral pneumonia, normal and tuberculosis cases, respectively. To improve the interpretation and explainability, three experiments have been conducted in exploration of the most coherent and appropriate classification approach. Moreover, the multi-scale attention model MA-DenseNet201 proposed for the classification of COVID-19 cases. The final stage of the Covid-MANet network quantifies the proportion of infection and severity of COVID-19 in the lungs. The COVID-19 cases are graded into more specific severity levels such as mild, moderate, severe, and critical as per the score assigned by the RALE scoring system. The MA-DenseNet201 classification model outperforms eight state-of-the-art CNN models, in terms of sensitivity and interpretation with lung localization network. The COVID-19 infection segmentation by UNet with DenseNet121 encoder achieves dice score of 86.15% outperforming UNet, UNet++, AttentionUNet, R2UNet, with VGG16, ResNet50 and DenseNet201 encoder. The proposed network not only classifies images based on the predicted label but also highlights the infection by segmentation/localization of model-focused regions to support explainable decisions. MA-DenseNet201 model with a segmentation-based cropping approach achieves maximum interpretation of 96% with COVID-19 sensitivity of 97.75%. Finally, based on class-varied sensitivity analysis Covid-MANet ensemble network of MA-DenseNet201, ResNet50 and MobileNet achieve 95.05% accuracy and 98.75% COVID-19 sensitivity. The proposed model is externally validated on an unseen dataset, yields 98.17% COVID-19 sensitivity.

Determining diagnostic radiographer staffing requirements: A workload-based approach

INTRODUCTION

The topic of healthcare human resource planning for diagnostic radiographers has received limited research attention to date. This research is concerned with developing a framework that can be used to determine diagnostic radiographer staffing requirements at a unit- or department level (i.e. at the micro-level).

METHODS

An inductive approach is applied to formulate requirement specifications that inform the development of the framework. A number of verification and validation activities are performed, including theoretical verification and a case study application.

RESULTS

The diagnostic radiographer staffing framework consists of seven steps that comprise a workload-based approach to determining the number of full time equivalent diagnostic radiographers that are required for each modality, or group of modalities. Both clinical and non-clinical activities are considered, and guidance is provided on calculating staffing requirements to cover leave allowances. A number of potential approaches to determining activity times are also discussed.

CONCLUSION

The framework represents a holistic approach to determining the required number of diagnostic radiographers at a practice-level, that is designed to remain relevant as technological advances are made in the field of diagnostic radiography.

IMPLICATIONS FOR PRACTICE

By providing a practical guideline, with accompanying examples, the framework is expected to hold value for individuals involved in the management of diagnostic radiography practices. The framework proposes an approach to a topic that affects every radiography practice in operation yet has received limited attention in literature to date.

Productivity evaluation of radiologists interpreting computed tomography scans using statistical process control charts

Radiology service managers search for efficient ways to monitor productivity and improve capacity. One way to assess radiologists' productivity is by measuring their time to complete reports. Radiology reporting times (RRTs) may be monitored using statistical tools, such as process control charts (CCs). This study was carried out in the radiology sector of a University-based general hospital with 850 inward beds. Productivity was monitored using CCs. The selected control variable was RRTs, and process capability was calculated using C_p and C_pk indices. Only chest computed tomography scans were analyzed, totaling 2862 exams over a 6-month period. Our objective was to develop a simple tool to monitor radiologist performance, as given by RRT, over time. For that, we constructed CCs using data from 10 radiologists to monitor the stability of their RRTs. Only 3 radiologists presented mean times below the group average; 6 displayed a trend in RRTs that characterized performance improvement, while 4 displayed the opposite trend. Capability measures for the group indicated a process that is not capable. We demonstrate that CCs may be a useful tool for monitoring radiologists' performances in CT scans interpretation. Results demonstrated that in the individual CT reporting process, common cause variability is the type of variability most frequently observed, being most likely related to natural variations in features of the images analyzed. Lastly, CCs may also assist in decision making in the sector, such as establishing minimum productivity goals based on historical performance.

Radiological 'SATs' monitor: The use of 'study ascribable times' to assess the impact of clinical workload on resident training in a resource-limited setting

INTRODUCTION

Globally, increasing clinical demands threaten postgraduate radiology training programmes. Time-based assessment of clinical workload is optimal in the academic environment, where an estimated 30% of consultant time should ideally be devoted to non-reporting activities. There has been limited analysis of the academic radiologist workload in low- and middle-income countries.

METHODS

Departmental staffing and clinical statistics were reviewed for 2008 and 2017. The Royal Australian and New Zealand College of Radiologists 'study ascribable times' (RANZCR-SATs) for primary consultant reporting were used with the Royal College of Radiologists (RCR) 2012 guidelines for secondary review of resident reports, to estimate the total consultant-hours required for each year's clinical workload. Analyses were stratified by type of investigation (plain-film vs. special) and expressed as a proportion of the total annual available consultant working hours.

RESULTS

Reporting all investigations required 90% and 100%, while reporting special investigations alone, demanded 53% and 69% of annual consultant working hours in 2008 and 2017, respectively. Between 2008 and 2017, the proportion of consultant time available for plain-film reporting decreased from 17% to 1%, while preserving 30% for non-reporting activities.

CONCLUSION

A time-based analysis of the academic radiologist's clinical workload, utilizing the RANZCR-SATs and RCR 2012 guidelines for primary and secondary reporting, respectively, provides a reasonably accurate reflection of the service pressures in resource-constrained environments and has potential international applicability.

Estimating the cost of radiotherapy for 5-year local control and overall survival benefit

BACKGROUND AND PURPOSE

Escalating health care costs have led to greater efforts directed at measuring the cost and benefits of medical treatments. The aim of this study was to estimate the costs of 5-year local control and overall survival benefits of radiotherapy for the cancer population in Australia.

MATERIALS AND METHODS

The local control and overall survival benefits of radiotherapy at 5-years and optimal number of fractions per course have been estimated for 26 tumour sites for which radiotherapy is indicated. For this study, a hybrid approach that merges features from activity based costing (ABC) and relative value units costing (RVU) were used to provide cost estimates. ABC methodology was used to allocate costs to all radiotherapy activities associated with each patient's treatment course, while the RVUs represent the cost of each radiotherapy activity relative to the average cost of all activities and were used to achieve a weighted cost allocation. A patient's journey for the financial year was constructed by consolidating all the radiotherapy activities and their associated costs, and the average cost per activity (fraction) was determined. The cost of radiotherapy per 5-year overall survival and local control was then estimated.

RESULTS

The estimated population 5-year local control and overall survival benefits of radiotherapy for all cancer were 23% and 6%, respectively. The optimal number of fractions per treatment course if guidelines were followed was 19.4 fractions. The average cost per fraction for all cancer was AU$276. The estimated cost of radiotherapy was AU$23,585 per 5-year local control and AU$86,480 per 5-year overall survival (equivalent to 5 life years) for all cancer.

CONCLUSION

The cost of AU$86,480 per 5-year overall survival would translate to AU$17,296 1-year overall survival. Therefore, the cost of radiotherapy is inexpensive if delivered optimally. Policy implications from this study include knowledge about cost to deliver radiotherapy to allow one to quantify the expected benefit at a population level.

Measuring radiologist workload: Progressing from RVUs to study ascribable times

INTRODUCTION

The need to measure reporting workload in teaching departments remains a current pertinent need. In Australia, the Pitman-Jones reporting RVUs have been in the public domain since 2003 (revised in 2009). These are expressed in arbitrary units. In New Zealand, single-site Christchurch Hospital reporting times have been validated and placed in the public domain. Concurrently, the RANZCR has been developing a formulaic descriptor lexicon for imaging studies (the Body System Framework). There is a need to bring these three strands of work together into a common public resource. In 2015, under the auspices of the Chief Accreditation Officer, RANZCR convened the Radiologist Workload Working Group. The goal of the group was to develop a robust method of measuring radiologist workload in teaching departments in Australia and New Zealand for the RANZCR accreditation processes of teaching departments as training sites. This paper concerns itself with one aspect of the group's work, namely reaching a consensus on radiologist study ascribable times for common imaging studies.

METHOD

The BSF examination descriptors were reduced to a smaller, generic dataset of descriptors at the expense of loss of specificity. BSF study ascribable times had been previously obtained by stopwatch observation. The dataset was harmonized with the Christchurch descriptors to ensure commonality of case mix. The two lead authors reached an approximate consensus study ascribable time for each descriptor in agreement with the BSF and Christchurch data. Specifically, the Christchurch reporting times were relied on extensively to validate the new dataset's study ascribable times. The first draft of descriptors and times was tabled at the meetings of the RANZCR Radiologist Workload Working Group, and was progressively refined by iterative consensus.

RESULTS

The output of the Radiologist Workload Working Group comprises a simplified modality-based table of robust descriptors and 'best estimate' corresponding study ascribable times. These can be used with the extant Pitman-Jones methodology in order to estimate the reporting workload of a medical imaging teaching department in units of time. As a first for Australia and New Zealand, nuclear medicine and PET study ascribable times have been incorporated and balanced against radiology study ascribable times.

CONCLUSION

The RANZCR 2016 study ascribable times are ready for use by the Australian and New Zealand radiologist and nuclear medicine specialist community. We hope these times will also stimulate further data collection in our two countries towards a robust, bi-national study ascribable times database.

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

Increasing workloads and the current austerity measures are putting UK radiology departments under considerable stress. We need to look at the most efficient ways to manage radiology departments in order to cope with increasing demand. Consequently, a system is needed that can compare productivity between radiologists with different jobs. We measured workload in a UK radiology department and compared the productivities of consultants working different numbers of sessions, which are called programmed activities (PAs), to identify the optimal job plan structure for reporting productivity. Reporting data was gathered from electronic records for 14 consultants working different numbers of PA during the period April 2010-March 2011. These were converted into relative value unit (RVU) scores using a modified RCSI RVU system. Crude and net workloads were calculated for each consultant by dividing their total RVU score by the number of PAs they were contracted for and how many they spent reporting. The consultants reported 118,001 imaging studies. There was statistically significant variation in productivity between consultants working different numbers of PAs on χ (2) analysis (p < 0.05). Consultants working 12 PAs were more productive than consultants working 11 PAs, with net workloads of 7636 RVU/PA/year versus net 6146 RVU/PA/year, p < 0.05. Although UK consultants working 12 PAs per week are more productive than their colleagues, the reasons why are unclear. We have identified a method that can be developed further to identify efficient working practices in UK radiology departments. However, a UK-specific RVU system would make this productivity analysis more accurate.

Incidental findings detected on emergency abdominal CT scans: a 1-year review

INTRODUCTION

In recent years, there has been a substantial rise in the use of computed tomography (CT) in the emergency medicine setting. Accordingly, with increased CT usage there has been an upsurge in incidental pathology detection.

METHODS

A retrospective review of all emergency CT abdominal scans performed at a university teaching hospital was examined. The frequency of incidental findings, their clinical significance and workload effect for the radiology department was assessed.

RESULTS

1155 patients had an emergency abdominal CT scan of which 700 had incidental findings detected. Of the incidental findings, 143 were deemed indeterminate requiring urgent investigations. Twenty-four occult neoplasms were confirmed subsequently. Additionally, 259 patients were recommended for additional diagnostics. The cumulative effect of the initial emergency abdominal CT was 15,015 relative value units (RVU). Subsequent imaging of incidental findings resulted in another 1674 RVU workload for radiology.

CONCLUSION

Incidental findings cause considerable debate and concern over which patients require significant follow-up, investigations, and/or surveillance. This exerts significant pressures on sub-specialties for their expert input, with increased workload and implications on healthcare service provision.

Workload of consultant radiologists in a large DGH and how it compares to international benchmarks

AIM

To measure radiologist workloads in a UK radiology department using relative value units (RVUs), and compared these data to current international standards from Australia and Ireland.

MATERIALS AND METHODS

Data on reporting throughput was gathered for 13.5 whole-time equivalent (WTE) consultants at the DGHs of East Lancashire Hospitals Trust (ELHT) between April 2010 to March 2011. RVUs were assigned to the reported imaging studies to create a crude RVU/WTE score. This was compared to benchmarks from Australia and results from a similar study in Ireland. Time spent on teaching, multidisciplinary teams, and administration was factored in to create a net RVU/WTE score, more accurately assessing workload.

RESULTS

Radiologists in ELHT reported 110,315 imaging studies, producing a total of 649,617 RVUs. Crude reporting workloads were 48,119.78 RVUs/WTE, and net workloads were 83,674.00 RVUs/WTE (with consultants spending 42.49% of their time on non-reporting commitments). These crude and net workloads are far above the Australian maximum reporting benchmark of 45,000 RVUs.

CONCLUSION

The workload is much higher than international benchmarks, indicating high-quality service and excellent value for money, but also highlights understaffing. Foreign RVU systems do not accurately reflect current UK practices and a UK-specific RVU system should be developed to assess staffing and analyse performance.

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

This article discusses the results and implications of a nationwide survey of radiologist workload. Although the results are specific to one country, the method used, the underlying issues and the discussion engendered should be of interest to all radiologists worldwide. The balance between quality and quantity is highlighted, and the growing impact of activities outside of traditional reporting is considered. Variations in health care funding and staffing amongst countries clearly influence patterns of workload. It is hoped that this discussion will lead other radiologists to consider the method used, and to analyse workload in other countries, with a view to creating more robust workload data and stimulating debate.

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

Objectives

The role of the Consultant Radiologist has changed substantially in recent decades, yet manpower planning is often based on older inappropriate methods of measuring Radiologist workload. We report a nationwide survey of Consultant Radiologist workload in Ireland in 2009.

Methods

Relative value units (RVUs) were assigned to easily countable studies. Hospitals’ activity was collated for the full calendar year of 2009. Radiologist time engaged in activities not easily counted (interventional and procedural work, multi-disciplinary meetings, teaching, administration, etc.) was separately measured.

Results

Data were obtained from 28 of 38 public hospital radiology departments. Mean Consultant Radiologist workload across all hospitals was 57,659.1 crude RVUs/WTE and 103,987 net RVUs/WTE. A mean of 32.47% of WTEs are engaged in non-countable activity. Means of 85.35% and 65.73% of the required numbers of WTEs were available in 2009 to achieve respectively annual crude and net RVU/WTE figures of 45,000. Excluding Specialist Centres, plain films accounted for 28–41% of recorded activity, mammography for 0.8–5.8%, US for 16–20%, CT for 27–32% and MR for 5.9–15.8%.

Conclusions

Irish Consultant Radiologist staffing levels are well below appropriate international benchmarks for the current workload. Approximately one-third of radiologist time is engaged in activity not easily counted in study numbers.