Leveraging the electronic health record to evaluate the validity of the current RVU system for radiologists

Reading Times of Common Musculoskeletal MRI Examinations: A Survey Study

BACKGROUND

The workload of musculoskeletal radiologists has come under pressure. Our objective was to estimate the reading times of common musculoskeletal MRI examinations.

METHODS

A total of 144 radiologists were asked to estimate reading times (including interpretation and reporting) for MRI of the shoulder, elbow, wrist, hip, knee, and ankle. Multivariate linear regression analyses were performed.

RESULTS

Reported median reading times with interquartile range (IQR) for the shoulder, elbow, wrist, hip, knee, and ankle were 10 (IQR 6-14), 10 (IQR 6-14), 11 (IQR 7.5-14.5), 10 (IQR 6.6-13.4), 8 (IQR 4.6-11.4), and 10 (IQR 6.5-13.5) min, respectively. Radiologists aged 35-44 years reported shorter reading times for the shoulder (β coefficient [β] = B-3.412, p = 0.041), hip (β = -3.596, p = 0.023), and knee (β = -3.541, p = 0.013) than radiologists aged 45-54 years. Radiologists not working in an academic/teaching hospital reported shorter reading times for the hip (β = -3.611, p = 0.025) and knee (β = -3.038, p = 0.035). Female radiologists indicated longer reading times for all joints (β of 2.592 to 5.186, p ≤ 0.034). Radiologists without musculoskeletal fellowship training indicated longer reading times for the shoulder (β = 4.604, p = 0.005), elbow (β = 3.989, p = 0.038), wrist (β = 4.543, p = 0.014), and hip (β = 2.380, p = 0.119). Radiologists with <5 years of post-residency experience indicated longer reading times for all joints (β of 5.355 to 6.984, p ≤ 0.045), and radiologists with 5-10 years of post-residency experience reported longer reading time for the knee (β = 3.660, p = 0.045) than those with >10 years of post-residency experience.

CONCLUSIONS

There is substantial variation among radiologists in reported reading times for common musculoskeletal MRI examinations. Several radiologist-related determinants appear to be associated with reading speed, including age, gender, hospital type, training, and experience.

Practical Strategies to Retain Radiologists

Since the great resignation associated with the coronavirus disease 2019 pandemic, radiology practices are now challenged with maintaining adequate radiology staffing requirements to cope with increasing clinical workload requirements. The authors describe practical strategies for radiology practice leaders to retain radiologists in the current challenging job market, while mitigating their burnout.

Productivity measurement in psychology and neuropsychology: Existing standards and alternative suggestions

Objective: The Relative Value Unit (RVU) system was initially developed to account for costs associated with clinical services and has since been applied in some settings as a metric for monitoring productivity. That practice has come under fire in the medical literature due to perceived flaws in determination of "work RVU" for different billing codes and negative impacts on healthcare rendered. This issue also affects psychologists, who bill codes associated with highly variable hourly wRVUs. This paper highlights this discrepancy and suggests alternative options for measuring productivity to better equate psychologists' time spent completing various billable clinical activities. Method: A review was performed to identify potential limitations to measuring providers' productivity based on wRVU alone. Available publications focus almost exclusively on physician productivity models. Little information was available relating to wRVU for psychology services, including neuropsychological evaluations, specifically. Conclusions: Measurement of clinician productivity using only wRVU disregards patient outcomes and under-values psychological assessment. Neuropsychologists are particularly affected. Based on the existing literature, we propose alternative approaches that capture productivity equitably among subspecialists and support provision of non-billable services that are also of high value (e.g. education and research).

Measurement of radiologist reporting times: Assessment of precision, comparison of three different measurement techniques and review of potential applications

INTRODUCTION

Radiologist reporting times are a key component of radiology department workload assessment, but reliable measurement remains challenging. Currently, there are three contenders for this task: median reporting times (MRTs), extracted directly from a department's radiology information system (RIS); study-ascribed times (SATs), using published tables of individual descriptors derived from a combination of measurement and consensus; and radiology reporting figures (RRFs), using published tables of measured times based on modality and numbers of anatomical areas.

METHODS

We review these techniques, their possible uses and some potential pitfalls. We discuss the level of precision that can realistically be attained in measuring reporting times, and list the strengths and weaknesses of each technique, comparing them in relation to each of eight potential applications.

RESULTS

We believe that SATs are challenging for practical use due to their static nature, absent common descriptors and large number. RRFs are more user-friendly but are also static and require ongoing updates; currently, they do not include ultrasound. MRTs cannot currently be extracted from every RIS, but where available they are easy to use and their dynamic nature provides the most objective data. They underestimate the unmeasurable components of a radiologist's work and therefore the total time spent in a reporting session.

CONCLUSION

MRTs are superior to the other methods in flexibility, precision and ease of use. All institutions should have access to this data and we call on vendors of Radiology Information Systems which are currently not capable of providing it to make the necessary modifications.

Rapid lumbar MRI protocol using 3D imaging and deep learning reconstruction

BACKGROUND AND PURPOSE

Three-dimensional (3D) imaging of the spine, augmented with AI-enabled image enhancement and denoising, has the potential to reduce imaging times without compromising image quality or diagnostic performance. This work evaluates the time savings afforded by a novel, rapid lumbar spine MRI protocol as well as image quality and diagnostic differences stemming from the use of an AI-enhanced 3D T2 sequence combined with a single Dixon acquisition.

MATERIALS AND METHODS

Thirty-five subjects underwent MRI using standard 2D lumbar imaging in addition to a "rapid protocol" consisting of 3D imaging, enhanced and denoised using a prototype DL reconstruction algorithm as well as a two-point Dixon sequence. Images were graded by subspecialized radiologists and imaging times were collected. Comparison was made between 2D sagittal T1 and Dixon fat images for neural foraminal stenosis, intraosseous lesions, and fracture detection.

RESULTS

This study demonstrated a 54% reduction in total acquisition time of a 3D AI-enhanced imaging lumbar spine MRI rapid protocol combined with a sagittal 2D Dixon sequence, compared to a 2D standard-of-care protocol. The rapid protocol also demonstrated strong agreement with the standard-of-care protocol with respect to osseous lesions (κ = 0.88), fracture detection (κ = 0.96), and neural foraminal stenosis (ICC > 0.9 at all levels).

CONCLUSION

3D imaging of the lumbar spine with AI-enhanced DL reconstruction and Dixon imaging demonstrated a significant reduction in imaging time with similar performance for common diagnostic metrics. Although previously limited by long postprocessing times, this technique has the potential to enhance patient throughput in busy radiology practices while providing similar or improved image quality.

Turnaround time and efficiency of pediatric outpatient brain magnetic resonance imaging: a multi-institutional cross-sectional study

BACKGROUND

Aside from single-center reports, few data exist across pediatric institutions that examine overall MRI turnaround time (TAT) and the determinants of variability.

OBJECTIVE

To determine average duration and determinants of a brain MRI examination at academic pediatric institutions and compare the duration to those used in practice expense relative value units (RVUs).

MATERIALS AND METHODS

This multi-institutional cross-sectional investigation comprised four academic pediatric hospitals. We included children ages 0 to < 18 years who underwent an outpatient MRI of the brain without contrast agent in 2019. Our outcome of interest was the overall MRI TAT derived by time stamps. We estimated determinants of overall TAT using an adjusted log-transformed multivariable linear regression model with robust standard errors.

RESULTS

The average overall TAT significantly varied among the four hospitals. A sedated brain MRI ranged from 158 min to 224 min, a non-sedated MRI from 70 min to 112 min, and a limited MRI from 44 min to 70 min. The most significant predictor of a longer overall TAT was having a sedated MRI (coefficient = 0.71, 95% confidence interval [CI]: 0.66-0.75; P < 0.001). The median MRI scan time for a non-sedated exam was 38 min and for a sedated exam, 37 min, approximately double the duration used by the Relative Value Scale (RVS) Update Committee (RUC).

CONCLUSION

We found considerable differences in the overall TAT across four pediatric academic institutions. Overall, the significant predictors of turnaround times were hospital site and MRI pathway (non-sedated versus sedated versus limited MRI).

Mandating Limits on Workload, Duty, and Speed in Radiology

Research has not yet quantified the effects of workload or duty hours on the accuracy of radiologists. With the exception of a brief reduction in imaging studies during the 2020 peak of the COVID-19 pandemic, the workload of radiologists in the United States has seen relentless growth in recent years. One concern is that this increased demand could lead to reduced accuracy. Behavioral studies in species ranging from insects to humans have shown that decision speed is inversely correlated to decision accuracy. A potential solution is to institute workload and duty limits to optimize radiologist performance and patient safety. The concern, however, is that any prescribed mandated limits would be arbitrary and thus no more advantageous than allowing radiologists to self-regulate. Specific studies have been proposed to determine whether limits reduce error, and if so, to provide a principled basis for such limits. This could determine the precise susceptibility of individual radiologists to medical error as a function of speed during image viewing, the maximum number of studies that could be read during a work shift, and the appropriate shift duration as a function of time of day. Before principled recommendations for restrictions are made, however, it is important to understand how radiologists function both optimally and at the margins of adequate performance. This study examines the relationship between interpretation speed and error rates in radiology, the potential influence of artificial intelligence on reading speed and error rates, and the possible outcomes of imposed limits on both caseload and duty hours. This review concludes that the scientific evidence needed to make meaningful rules is lacking and notes that regulating workloads without scientific principles can be more harmful than not regulating at all.