Shweta Sharat Kumar

All Publications

• Actionability of Recommendations for Additional Imaging in Head and Neck Radiology. Journal of the American College of Radiology : JACR Guenette, J. P., Lynch, E., Abbasi, N., Schulz, K., Kumar, S., Haneuse, S., Kapoor, N., Lacson, R., Khorasani, R. 2024; 21 (7): 1040-1048

  Abstract

  The aims of this study were to measure the actionability of recommendations for additional imaging (RAIs) in head and neck CT and MRI, for which there is a near complete absence of best practices or guidelines; to identify the most common recommendations; and to assess radiologist factors associated with actionability.All head and neck CT and MRI radiology reports across a multi-institution, multipractice health care system from June 1, 2021, to May 31, 2022, were retrospectively reviewed. The actionability of RAIs was scored using a validated taxonomy. The most common RAIs were identified. Actionability association with radiologist factors (gender, years out of training, fellowship training, practice type) and with trainees was measured using a mixed-effects model.Two hundred nine radiologists generated 60,543 reports, of which 7.2% (n = 4,382) contained RAIs. Only 3.9% of RAIs (170 of 4,382) were actionable. More than 60% of RAIs were for eight examinations: thyroid ultrasound (14.1%), neck CT (12.6%), brain MRI (6.9%), chest CT (6.5%), neck CT angiography (5.5%), temporal bone CT (5.3%), temporal bone MRI (5.2%), and pituitary MRI (4.6%). Radiologists >23 years out of training (odds ratio, 0.39; 95% confidence interval, 0.15-1.02; P = .05) and community radiologists (odds ratio, 0.53; 95% confidence interval, 0.22-1.31; P = .17) had substantially lower estimated odds of making actionable RAIs than radiologists <7 years out of training and academic radiologists, respectively.The studied radiologists rarely made actionable RAIs, which makes it difficult to identify and track clinically necessary RAIs to timely performance. Multifaceted quality improvement initiatives including peer comparisons, clinical decision support at the time of reporting, and the development of evidence-based best practices, may help improve tracking and timely performance of clinically necessary RAIs.

  View details for DOI 10.1016/j.jacr.2024.01.005

  View details for PubMedID 38220042

• Recommendations for Additional Imaging on Head and Neck Imaging Examinations: Interradiologist Variation and Associated Factors. AJR. American journal of roentgenology Guenette, J. P., Lynch, E., Abbasi, N., Schulz, K., Kumar, S., Haneuse, S., Kapoor, N., Lacson, R., Khorasani, R. 2024

  Abstract

  Background: A paucity of relevant guidelines may lead to pronounced variation among radiologists in issuing recommendations for additional imaging (RAI) for head and neck imaging. Objective: To explore associations of RAI for head and neck imaging examinations with examination, patient, and radiologist factors, and to assess the role of individual radiologist-specific behavior in issuing such RAI. Methods: This retrospective study included 39,200 patients (median age, 58 years; 21,855 female, 17,315 male, 30 with missing sex information) who underwent 39,200 head and neck CT or MRI examinations, interpreted by 61 radiologists, from June 1, 2021 through May 31, 2022. A natural language processing (NLP) tool with manual review of NLP results was used to identify RAI in report impressions. Interradiologist variation in RAI rates was assessed. A generalized mixed-effects model was used to assess associations between RAI and examination, patient, and radiologist factors. Results: A total of 2946 (7.5%) reports contained an RAI. Individual radiologist RAI rates ranged from 0.8% to 22.0% (median 7.1%, IQR 5.2%-10.2%), representing 27.5-fold difference between minimum and maximum values and 1.8-fold difference between 25th and 75th percentiles. In multivariable analysis, RAI likelihood was higher for CTA than for CT examinations (OR: 1.32), for examinations that included a trainee in report generation (OR: 1.23), and for patients with self-identified race of Black or African American than of White (OR: 1.25); lower for male than female patients (OR: 0.90); and associated with increasing patient age (OR: 1.09 per decade) and inversely associated with radiologist years since training (OR: 0.90 per 5 years). The model accounted for 10.9% of the likelihood of RAI. Of explainable likelihood of RAI, 25.7% was attributable to examination, patient, and radiologist factors; 74.3% was attributable to radiologist-specific behavior. Conclusion: Interradiologist variation in RAI rates for head and neck imaging was substantial. RAI appeared to be more substantially associated with individual radiologist-specific behavior than with measurable systemic factors. Clinical Impact: Quality improvement initiatives, incorporating best practices for incidental findings management, may help reduce radiologist preference-sensitive decision-making in issuing RAI for head and neck imaging and associated care variation.

  View details for DOI 10.2214/AJR.23.30511

  View details for PubMedID 38294159