JOURNAL CLUB: Structured Reporting: The Voice of the Customer in an Ongoing Debate About the Future of Radiology Reporting

Assessing the impact of structured reporting on learning how to report lung cancer staging CT: A triple cohort study on inexperienced readers

PURPOSE

To assess the clinical utility of chest computed tomography (CT) reports for non-small-cell lung cancer (NSCLC) staging generated by inexperienced readers using structured reporting (SR) templates from the Royal College of Radiologists (RCR-SR) and the Italian Society of Medical and Interventional Radiology (SIRM-SR), compared to traditional non-systematic reports (NSR).

METHODS

In a cohort of 30 NSCLC patients, six third-year radiology residents reported CT examinations in two 2-month-apart separate sessions using NSR in the first and NSR, RCR-SR, or SIRM-SR in the second. Couples of expert radiologists and thoracic oncologists in consensus evaluated completeness, accuracy, and clarity. All the quality indicators were expressed on a 100-point scale. The Wilcoxon signed ranks, and Wilcoxon-Mann Whitney tests were used for statistical analyses.

RESULTS

Results showed significantly higher completeness for RCR-SR (90 %) and SIRM-SR (100 %) compared to NSR (70 %) in the second session (all p < 0.001). SIRM-SR demonstrated superior accuracy (70 % vs. 55 %, p < 0.001) over NSR, while RCR-SR and NSR accuracy did not significantly differ (60 % vs. 62.5 %, p = 0.06). In the second session, RCR-SR and SIRM-SR surpassed NSR in completeness, accuracy, and clarity (all p < 0.001, except p = 0.04 for accuracy between RCR-SR and NSR). SIRM-SR outperformed RCR-SR in completeness (100 % vs. 90 %, p < 0.001) and accuracy (70 % vs. 62.5 %, p = 0.002), with equivalent clarity (90 % for both, p = 0.27).

CONCLUSIONS

Inexperienced readers using RCR-SR and SIRM-SR demonstrated high-quality reporting, indicating their potential in radiology residency programs to enhance reporting skills for NSCLC staging and effective interaction with all the physicians involved in managing NSCLC patients.

Investigating the impact of structured reporting on the linguistic standardization of radiology reports through natural language processing over a 10-year period

OBJECTIVES

To investigate how a transition from free text to structured reporting affects reporting language with regard to standardization and distinguishability.

METHODS

A total of 747,393 radiology reports dictated between January 2011 and June 2020 were retrospectively analyzed. The body and cardiothoracic imaging divisions introduced a reporting concept using standardized language and structured reporting templates in January 2016. Reports were segmented by a natural language processing algorithm and converted into a 20-dimension document vector. For analysis, dimensionality was reduced to a 2D visualization with t-distributed stochastic neighbor embedding and matched with metadata. Linguistic standardization was assessed by comparing distinct report types' vector spreads (e.g., run-off MR angiography) between reporting standards. Changes in report type distinguishability (e.g., CT abdomen/pelvis vs. MR abdomen) were measured by comparing the distance between their centroids.

RESULTS

Structured reports showed lower document vector spread (thus higher linguistic similarity) compared with free-text reports overall (21.9 [free-text] vs. 15.9 [structured]; - 27.4%; p < 0.001) and for most report types, e.g., run-off MR angiography (15.2 vs. 1.8; - 88.2%; p < 0.001) or double-rule-out CT (26.8 vs. 10.0; - 62.7%; p < 0.001). No changes were observed for reports continued to be written in free text, e.g., CT head reports (33.2 vs. 33.1; - 0.3%; p = 1). Distances between the report types' centroids increased with structured reporting (thus better linguistic distinguishability) overall (27.3 vs. 54.4; + 99.3 ± 98.4%) and for specific report types, e.g., CT abdomen/pelvis vs. MR abdomen (13.7 vs. 37.2; + 171.5%).

CONCLUSION

Structured reporting and the use of factual language yield more homogenous and standardized radiology reports on a linguistic level, tailored to specific reporting scenarios and imaging studies.

CLINICAL RELEVANCE

Information transmission to referring physicians, as well as automated report assessment and content extraction in big data analyses, may benefit from standardized reporting, due to consistent report organization and terminology used for pathologies and normal findings.

KEY POINTS

• Natural language processing and t-distributed stochastic neighbor embedding can transform radiology reports into numeric vectors, allowing the quantification of their linguistic standardization. • Structured reporting substantially increases reports' linguistic standardization (mean: - 27.4% in vector spread) and distinguishability (mean: + 99.3 ± 98.4% increase in vector distance) compared with free-text reports. • Higher standardization and homogeneity outline potential benefits of structured reporting for information transmission and big data analyses.

Quantifying the Effects of Structured Reporting on Report Turnaround Times and Proofreading Workload in Neuroradiology

RATIONALE AND OBJECTIVES

To assess the effects of a change from free text reporting to structured reporting on resident reports, the proofreading workload and report turnaround times in the neuroradiology daily routine.

MATERIALS AND METHODS

Our neuroradiology section introduced structured reporting templates in July 2019. Reports dictated by residents during dayshifts from January 2019 to March 2020 were retrospectively assessed using quantitative parameters from report comparison. Through automatic analysis of text-string differences between report states (i.e. draft, preliminary and final report), Jaccard similarities and edit distances of reports following read-out sessions as well as after report sign-off were calculated. Furthermore, turnaround times until preliminary and final report availability to clinicians were investigated. Parameters were visualized as trending line graphs and statistically compared between reporting standards.

RESULTS

Three thousand five hundred thirty-eight reports were included into analysis. Mean Jaccard similarity of resident drafts and staff-reviewed final reports increased from 0.53 ± 0.37 to 0.79 ± 0.22 after the introduction of structured reporting (p < .001). Both mean overall edits on draft reports by residents following read-out sessions (0.30 ± 0.45 vs. 0.09 ± 0.29; p < .001) and by staff radiologists during report sign-off (0.17 ± 0.28 vs. 0.12 ± 0.23, p < .001) decreased. With structured reporting, mean turnaround time until preliminary report availability to clinicians decreased by 20.7 minutes (246.9 ± 207.0 vs. 226.2 ± 224.9; p < .001). Similarly, final reports were available 35.0 minutes faster on average (558.05 ± 15.1 vs. 523.0 ± 497.3; p = .002).

CONCLUSION

Structured reporting is beneficial in the neuroradiology daily routine, as resident drafts require fewer edits in the report review process. This reduction in proofreading workload is likely responsible for lower report turnaround times.

Structured reporting in radiology: a systematic review to explore its potential

OBJECTIVES

Structured reporting (SR) in radiology reporting is suggested to be a promising tool in clinical practice. In order to implement such an emerging innovation, it is necessary to verify that radiology reporting can benefit from SR. Therefore, the purpose of this systematic review is to explore the level of evidence of structured reporting in radiology. Additionally, this review provides an overview on the current status of SR in radiology.

METHODS

A narrative systematic review was conducted, searching PubMed, Embase, and the Cochrane Library using the syntax 'radiol*' AND 'structur*' AND 'report*'. Structured reporting was divided in SR level 1, structured layout (use of templates and checklists), and SR level 2, structured content (a drop-down menu, point-and-click or clickable decision trees). Two reviewers screened the search results and included all quantitative experimental studies that discussed SR in radiology. A thematic analysis was performed to appraise the evidence level.

RESULTS

The search resulted in 63 relevant full text articles out of a total of 8561 articles. Thematic analysis resulted in 44 SR level 1 and 19 level 2 reports. Only one paper was scored as highest level of evidence, which concerned a double cohort study with randomized trial design.

CONCLUSION

The level of evidence for implementing SR in radiology is still low and outcomes should be interpreted with caution.

KEY POINTS

• Structured reporting is increasingly being used in radiology, especially in abdominal and neuroradiological CT and MRI reports. • SR can be subdivided into structured layout (SR level 1) and structured content (SR level 2), in which the first is defined as being a template in which the reporter has to report; the latter is an IT-based manner in which the content of the radiology report can be inserted and displayed into the report. • Despite the extensive amount of research on the subject of structured reporting, the level of evidence is low.

Communicating with the hepatobiliary surgeon through structured report

Communicating radiological findings to hepatobiliary surgeons is not an easy task due to the complexity of liver imaging, coexistence of multiple hepatic lesions and different surgical treatment options. Recently, the adoption and implementation of structured report in everyday clinical practice has been supported to achieve higher quality, more reproducibility in communication and closer adherence to current guidelines. In this review article, we will illustrate the main benefits, strengths and limitations of structured reporting, with particular attention on the advantages and challenges of structured template in the preoperative evaluation of cirrhotic and non-cirrhotic patients with focal liver lesions. Structured reporting may improve the preoperative evaluation, focusing on answering specific clinical questions that are requested by hepatobiliary surgeons in candidates to liver resection.