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Development of a local relative value unit to measure radiologists' computed tomography reporting workload.
- Source :
-
Journal of medical imaging and radiation oncology [J Med Imaging Radiat Oncol] 2016 Dec; Vol. 60 (6), pp. 714-719. Date of Electronic Publication: 2016 Jul 11. - Publication Year :
- 2016
-
Abstract
- Introduction: Demand for CT examinations is continually increasing, with radiologists' reporting times (RRTs) being the major constraint in CT productivity. As CT complexity varies according to the anatomical region, there is a need for methods that normalize radiologist work to address reporting workload.<br />Methods: All CT orders, from July 2013 to February 2015, from a 850-bed tertiary-care, university-based general hospital in southern Brazil, were studied. Type of examination and RRTs were retrieved from our Radiology Information System/IMPAX. Based on RRTs, after exclusion of spurious results, we calculated local relative value units (L-RVUs) for different examinations. We also compared these results with the US-Medicare/Medicaid RVU (US-RVU).<br />Results: The query resulted in 42,382 occurrences for 24 tests. Among the tests, 15 had sample size n ≥ 100. The 9 tests with n < 100 were grouped into 4 sets of tests, resulting in the analysis of 17 categories of tests. RRTs for total abdomen CT, thorax CT and central nervous system CT were 17.1 ± 14.6, 14.2 ± 11.1 and 7.0 ± 6.5 minutes, respectively. L-RVUs for the 17 categories of tests were calculated, resulting in values from 1.00 to 4.18. L-RVU and US-RVU displayed no correlation (r = 0.05; P-value = 0.86).<br />Conclusion: Computed tomography radiologists' reporting workload varies considerably across different tests. Moreover, the lack of significant correlation between US-RVU and L-RVU highlights the need for contextualized methods to locally address radiologists' reporting workload. Thus, the use of L-RVU could aid in planning and managing a CT Unit.<br /> (© 2016 The Royal Australian and New Zealand College of Radiologists.)
Details
- Language :
- English
- ISSN :
- 1754-9485
- Volume :
- 60
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- Journal of medical imaging and radiation oncology
- Publication Type :
- Academic Journal
- Accession number :
- 27397691
- Full Text :
- https://doi.org/10.1111/1754-9485.12492