Case of Study
Radiology Associates
SAN LUIS OBISPO, CA
Sustained Performance Above National Benchmarks With a Button-Based Workflow
Background
Diagnostic imaging volume in the United States continues to grow while the radiologist workforce remains limited. National projections show increased utilization of CT and MRI, yet fewer than 32,000 radiologists are available to interpret the corresponding studies. Even small workflow inefficiencies affect access to care, turnaround time, and the well-being of clinicians who already operate under intense demands.
For many decades, radiology reporting has depended on spoken dictation. Although speech recognition systems have improved, they still require radiologists to repeat phrases, correct transcription errors, and spend time restating observations that are already clear on the image. These interruptions have nothing to do with clinical expertise and they reduce the time available for interpretation.
At Radiology Associates of San Luis Obispo, documentation became a limiting factor. Reporting was slow, not because studies were complex, but because dictation forced radiologists to waste time saying and repeating what their eyes had already diagnosed. This was not a performance issue. It was an inefficiency created by the reporting method itself. Rising imaging volume pushed the group to consider alternatives that could increase throughput without altering clinical judgment or adding staff.
The Need for a Better Method of Reporting
RASLO serves hospitals and outpatient centers across California’s central coast. As in many regions of the United States, the number of examinations increased steadily in the years preceding this study. National trends show that CT and MRI use has risen by approximately 20% on a case-mix adjusted basis over the past decade.
Traditional dictation created delays that affected the entire care cycle. Radiologists interpreted studies efficiently, but documenting the findings slowed the process. Speech recognition errors required extra time. Inconsistent phrasing created variation among reports that complicated communication with referring clinicians. Billing teams encountered differences in terminology that made coding more difficult.
RASLO did not need a tool that changed how clinicians read images. It needed a system that removed friction from the process of communicating what had already been determined.
Adopting a Button-Based Structured Reporting Platform
RASLO implemented TurboRad, a template-based structured reporting platform that replaces most spoken dictation with standardized text elements called TurboButtons. Radiologists select findings using organized clinical options that reflect relevant normal and pathologic findings. The system builds complete reports using consistent language that aligns with national standards while allowing radiologists to edit or dictate whenever they choose.
TurboRad does not interpret images and does not restrict clinical autonomy. It removes the mechanical burden of verbal repetition. Radiologists spend more time evaluating studies because they spend less time constructing sentences.
The platform supports the clinical workflow by:
-
Standardizing language and report structure
-
Reducing corrections and proofreading
-
Limiting time lost to repeated dictation
-
Making documentation fast without limiting judgment
Documentation quality improves without requiring radiologists to speak every detail. The interpretation remains entirely in the hands of the physician.
Methods
A retrospective review was performed to measure productivity after the implementation of TurboRad at RASLO. Twelve radiologists were included. Annual wRVUs were collected from billing cycles through Quinsite and were de-identified before analysis. To calculate daily productivity, data were normalized to 170 clinical days per year. National averages were based on a benchmark of 10,500 annual wRVUs, a mid-range estimate selected due to limited public access to paid datasets. This benchmark is consistent with published industry expectations for diagnostic radiology. Interventional radiologists were included in the dataset. They typically produce fewer wRVUs per day because procedures require more time than diagnostic interpretation. Including these clinicians strengthened the analysis by presenting a realistic group average
Results:
Over the three-year study period, the RASLO working group demonstrated higher average annual wRVUs per radiologist in comparison to the national average based on data collected from billing cycles. The average annual wRVUs per RASLO radiologist was 19,851 in comparison to the national average of 10,500.9,10
Average annual RASLO wRVU by group.
2022 - 19,295
2023 - 20,865
2024 - 19,393
In 2022, RASLO radiologists recorded an annual average of 19,295 wRVUs, exceeding the national benchmark of 10,500 wRVUs by 8,795 (Table 1). This represents 1.84 times the national average. The performance increased in 2023, with the RASLO annual wRVU average climbing to 20,865, 10,365 wRVUs higher than the national average, corresponding to 1.99 times the benchmark. This reflects a year-to-year increase of 1,570 wRVUs for the RASLO group. In 2024, RASLO average annual wRVUs declined to 19,393, yet remained higher than the national average. This difference of 8,893 wRVUs corresponds to 1.85 times the national average. The decrease from 2023 to 2024 represents an average reduction of 1,472 wRVUs per physician. Across the study period, RASLO radiologists maintained annual wRVU levels that were 84% to 99% above the national average. There was variation across the annual wRVUs in the RASLO working group across the three-year period (Figure 1 & Figure 2). The highest relative difference was in 2023, when RASLO annual wRVU output was nearly double the national benchmark. Although RASLO workload decreased in 2024 relative to the prior year, the difference remained substantial compared to national peers, indicating a consistent trend of elevated workload and productivity.
Figure 1. Annual wRVUs per radiologist in RASLO group 2022 – 2024.

Figure 2. Average annual wRVUs per radiologist in RASLO group 2022 – 2024.

Analysis of annual wRVU output demonstrated that the RASLO group consistently exceeded the national average for daily wRVU production across all three years examined (Table 2). In 2022, RASLO radiologists averaged 113 wRVUs per day compared to the national average of 62, representing an 85% higher workload. In 2023, RASLO daily wRVUs increased to 123, resulting in a 100% higher output than the national average benchmark. By 2024, RASLO radiologists averaged 114 wRVUs per day compared to the national average, a difference of 87%. Overall, RASLO radiologists maintained a consistently elevated daily wRVU output, ranging from 85% to 100% above national benchmarks during the study period. The highest relative difference was observed in 2023, when RASLO RVU production peaked at nearly double the national average. Although average daily wRVUs for the RASLO group declined slightly in 2024, they remained substantially higher than the national comparison, indicating a sustained trend of increased workload and productivity.
RASLO average wRVU per day
2022 - 113
2023 -123
2024 - 114
*170 annual workdays
Discussion
The data indicate that increased productivity did not result from additional staffing, longer working hours, or changes in study mix. Performance improved because radiologists no longer spent time repeating or correcting dictated text. Eliminating low-value speech tasks allowed cognitive effort to shift toward interpretation rather than documentation.
The change also influenced fatigue. Radiologists reported fewer interruptions and less frustration associated with repeating spoken phrases or correcting voice recognition errors. Burnout in radiology is closely linked to repetitive tasks, heavy volume, and inefficient tools. Reducing verbal repetition creates meaningful support for clinicians who must sustain attention throughout the day.
The impact extended beyond the radiologist. Standardized phrasing helped referring clinicians receive concise and consistent information. Billing processes became more straightforward. Reporting quality was more uniform for the same conditions and studies. TurboRad served as a structural improvement that benefited the full clinical pathway from interpretation to reimbursement.
Conclusion
RASLO’s experience shows that radiology productivity can be improved by addressing documentation inefficiency rather than interpretation speed. A button-based structured reporting platform helped the group sustain wRVU production at levels 85% to 100% higher than national benchmarks for three consecutive years.
By removing repetitive dictation and providing fast access to standardized language, TurboRad allowed radiologists to spend their time where it matters. Clinicians focused on reading images, supporting patient care, and communicating clear results instead of being a transcriptionist.
TurboRad enhances radiology productivity without automation that replaces clinical judgment. It supports radiologists by simplifying communication, preserving autonomy, and improving the operational strength of the entire reporting workflow.
References:
1. Hsiao WC, Braun P, Becker ER, et al. The Resource-Based Relative Value Scale. Toward the development of an alternative physician payment system. JAMA 1987;258(6):799-802
2. Duszak R, Muroff LR. Measuring and managing radiologist productivity, part 1: clinical metrics and benchmarks. J Am Coll Radiol 2010;7(6):452-8, doi:10.1016/j.jacr.2010.01.026
3. Duszak R, Muroff LR. Measuring and managing radiologist productivity, part 2: beyond the clinical numbers. J Am Coll Radiol 2010;7(7):482-9, doi:10.1016/j.jacr.2010.01.025
4. Statistics USBoL. Occupational Employment and Wage Estimates. Washington, DC; 2023.
5. Christensen EW, Parikh JR, Drake AR, et al. Projected US Radiologist Supply, 2025 to 2055. J Am Coll Radiol 2025;22(2):161-169, doi:10.1016/j.jacr.2024.10.019
6. Christensen EW, Drake AR, Parikh JR, et al. Projected US Imaging Utilization, 2025 to 2055. J Am Coll Radiol 2025;22(2):151-158, doi:10.1016/j.jacr.2024.10.017
7. Canon CL, Chick JFB, DeQuesada I, et al. Physician Burnout in Radiology: Perspectives From the Field. AJR Am J Roentgenol 2022;218(2):370-374, doi:10.2214/AJR.21.26756
8. Giess CS, Ip IK, Gupte A, et al. Self-reported Burnout: Comparison of Radiologists to Nonradiologist Peers at a Large Academic Medical Center. Acad Radiol 2022;29(2):277-283, doi:10.1016/j.acra.2020.10.013
9. Medical Group Management Association (MGMA) DataDive 2024-2025. Radiology RVU Guide. Accessed Nov. 2025.
10. American Group Medical Association (AMGA) Medical Group Compensation and Productivity Survey 2020. Accessed Nov. 2025.
11. Muroff LR, Berlin L. Speed Versus Interpretation Accuracy: Current Thoughts and Literature Review. AJR Am J Roentgenol 2019;213(3):490-492, doi:10.2214/AJR.19.21290
12. Toker I, Jansen S, Lorenz D. Impact of Standardized Reporting Systems on Patient Experience in Radiology. J Patient Exp 2025;12(23743735251314648, doi:10.1177/23743735251314648
13. Shanafelt TD, Hasan O, Dyrbye LN, et al. Changes in Burnout and Satisfaction With Work-Life Balance in Physicians and the General US Working Population Between 2011 and 2014. Mayo Clin Proc 2015;90(12):1600-13, doi:10.1016/j.mayocp.2015.08.023
14. Giess CS, Ip IK, Gupte A, et al. Self-reported Burnout: Comparison of Radiologists to Nonradiologist Peers at a Large Academic Medical Center. Acad Radiol 2022;29(2):277-283, doi:10.1016/j.acra.2020.10.013
15. Chang PJ. It Might Be Time to Get Serious about Generative AI in Radiology. Radiology 2024;313(1):e242813, doi:10.1148/radiol.242813
16. Bruno MA, Grimm L, Pang LJ, et al. Artificial Intelligence and Its Impact on Radiology: Summary of the 2024 Intersociety Summer Conference. J Am Coll Radiol 2025, doi:10.1016/j.jacr.2025.07.025