Structured reporting for efficient epidemiological and in-hospital prevalence analysis of pulmonary embolisms

Tobias Jorg; Moritz C Halfmann; Dirk Graafen; Lukas Hobohm; Christoph Düber; Peter Mildenberger; Lukas Müller

doi:10.1055/a-2301-3349

RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, Table of Contents

Rofo 2025; 197(02): 186-195
DOI: 10.1055/a-2301-3349

Quality/Quality Assurance

Structured reporting for efficient epidemiological and in-hospital prevalence analysis of pulmonary embolisms

Article in several languages: English | deutsch

Tobias Jorg

¹Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany (Ringgold ID: RIN39068)

,

Moritz C Halfmann

¹Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany (Ringgold ID: RIN39068)

,

Dirk Graafen

¹Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany (Ringgold ID: RIN39068)

,

Lukas Hobohm

²Center for Cardiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany (Ringgold ID: RIN39068)

,

Christoph Düber

¹Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany (Ringgold ID: RIN39068)

,

Peter Mildenberger

¹Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany (Ringgold ID: RIN39068)

,

Lukas Müller

¹Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany (Ringgold ID: RIN39068)

› Author Affiliations

Abstract

Purpose

Structured reporting (SR) not only offers advantages regarding report quality but, as an IT-based method, also the opportunity to aggregate and analyze large, highly structured datasets (data mining). In this study, a data mining algorithm was used to calculate epidemiological data and in-hospital prevalence statistics of pulmonary embolism (PE) by analyzing structured CT reports.

Methods

All structured reports for PE CT scans from the last 5 years (n = 2790) were extracted from the SR database and analyzed. The prevalence of PE was calculated for the entire cohort and stratified by referral type and clinical referrer. Distributions of the manifestation of PEs (central, lobar, segmental, subsegmental, as well as left-sided, right-sided, bilateral) were calculated, and the occurrence of right heart strain was correlated with the manifestation.

Results

The prevalence of PE in the entire cohort was 24% (n = 678). The median age of PE patients was 71 years (IQR 58–80), and the sex distribution was 1.2/1 (M/F). Outpatients showed a lower prevalence of 23% compared to patients from regular wards (27%) and intensive care units (30%). Surgically referred patients had a higher prevalence than patients from internal medicine (34% vs. 22%). Patients with central and bilateral PEs had a significantly higher occurrence of right heart strain compared to patients with peripheral and unilateral embolisms.

Conclusion

Data mining of structured reports is a simple method for obtaining prevalence statistics, epidemiological data, and the distribution of disease characteristics, as demonstrated by the PE use case. The generated data can be helpful for multiple purposes, such as for internal clinical quality assurance and scientific analyses. To benefit from this, consistent use of SR is required and is therefore recommended.

Key Points

SR-based data mining allows simple epidemiologic analyses for PE.
The prevalence of PE differs between outpatients and inpatients.
Central and bilateral PEs have an increased risk of right heart strain.

Citation Format

Jorg T, Halfmann MC, Graafen D et al. Structured reporting for efficient epidemiological and in-hospital prevalence analysis of pulmonary embolisms. Rofo 2025; 197: 186–195

Keywords

epidemiology - CT-angiography - embolism/thrombosis

Full Text

References

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