PMID- 34027590
OWN - NLM
STAT- MEDLINE
DCOM- 20211015
LR  - 20211015
IS  - 1618-727X (Electronic)
IS  - 0897-1889 (Print)
IS  - 0897-1889 (Linking)
VI  - 34
IP  - 4
DP  - 2021 Aug
TI  - The Composite Severity Score for Lumbar Spine MRI: a Metric of Cumulative 
      Degenerative Disease Predicts Time Spent on Interpretation and Reporting.
PG  - 811-819
LID - 10.1007/s10278-021-00462-1 [doi]
AB  - Conventional measures of radiologist efficiency, such as the relative value unit, 
      fail to account for variations in the complexity and difficulty of a given study. 
      For lumbar spine MRI (LMRI), an ideal performance metric should account for the 
      global severity of lumbar degenerative disease (LSDD) which may influence 
      reporting time (RT), thereby affecting clinical productivity. This study aims to 
      derive a global LSDD metric and estimate its effect on RT. A 10-year archive of 
      LMRI reports comprising 13,388 exams was reviewed. Objective reporting timestamps 
      were used to calculate RT. A natural language processing (NLP) tool was used to 
      extract radiologist-assigned stenosis severity using a 6-point scale 
      (0 = "normal" to 5 = "severe") at each lumbar level. The composite severity score 
      (CSS) was calculated as the sum of each of 18 stenosis grades. The predictive 
      values of CSS, sex, age, radiologist identity, and referring service on RT were 
      examined with multiple regression models. The NLP tool accurately classified LSDD 
      in 94.8% of cases in a validation set. The CSS increased with patient age and 
      differed between men and women. In a univariable model, CSS was a significant 
      predictor of mean RT (R(2) = 0.38, p < 0.001) and independent predictor of mean 
      RT (p < 0.001) controlling for patient sex, patient age, service location, and 
      interpreting radiologist. The predictive strength of CSS was stronger for the low 
      CSS range (CSS = 0-25, R(2) = 0.83, p < 0.001) compared to higher CSS values 
      (CSS > 25, R(2) = 0.15, p = 0.05). Individual radiologist study volume was 
      negatively correlated with mean RT (Pearson's R =  - 0.35, p < 0.001). The 
      composite severity score predicts radiologist reporting efficiency in LMRI, 
      providing a quantitative measure of case complexity which may be useful for 
      workflow planning and performance evaluation.
CI  - (c) 2021. The Author(s).
FAU - Caton, Michael Travis Jr
AU  - Caton MT Jr
AUID- ORCID: 0000-0003-1581-7702
AD  - Department of Radiology and Biomedical Imaging, University of California San 
      Francisco, 505 Parnassus Ave L305, San Francisco, CA, USA. 
      travis.caton@gmail.com.
FAU - Wiggins, Walter F
AU  - Wiggins WF
AD  - Department of Radiology, Duke University, Durham, NC, 27708, USA.
FAU - Pomerantz, Stuart R
AU  - Pomerantz SR
AD  - Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA, 
      02114, USA.
FAU - Andriole, Katherine P
AU  - Andriole KP
AD  - Partners Center for Clinical Data Science, 100 Cambridge Street, Boston, MA, 
      02114, USA.
LA  - eng
PT  - Journal Article
DEP - 20210523
PL  - United States
TA  - J Digit Imaging
JT  - Journal of digital imaging
JID - 9100529
SB  - IM
MH  - Female
MH  - Humans
MH  - Lumbar Vertebrae/diagnostic imaging
MH  - *Magnetic Resonance Imaging
MH  - Male
MH  - *Radiologists
PMC - PMC8455764
EDAT- 2021/05/25 06:00
MHDA- 2021/10/16 06:00
PMCR- 2021/05/23
CRDT- 2021/05/24 08:24
PHST- 2020/07/18 00:00 [received]
PHST- 2021/05/06 00:00 [accepted]
PHST- 2021/03/03 00:00 [revised]
PHST- 2021/05/25 06:00 [pubmed]
PHST- 2021/10/16 06:00 [medline]
PHST- 2021/05/24 08:24 [entrez]
PHST- 2021/05/23 00:00 [pmc-release]
AID - 10.1007/s10278-021-00462-1 [pii]
AID - 462 [pii]
AID - 10.1007/s10278-021-00462-1 [doi]
PST - ppublish
SO  - J Digit Imaging. 2021 Aug;34(4):811-819. doi: 10.1007/s10278-021-00462-1. Epub 
      2021 May 23.