A proof of concept for epidemiological research using structured reporting with pulmonary embolism as a use case

Objective: This paper studies the possibilities of an integrated IT-based workflow for epidemiological research in pulmonary embolism (PE) using freely available tools and structured reporting (SR). Methods: We included a total of 521 consecutive cases which had been referred to the radiology department for CT pulmonary angiography with suspected PE. Free-text reports were transformed into structured reports using a freely available IHE Management of Radiology Report Templates-compliant reporting platform. D-dimer values were retrieved from the hospitals laboratory results system. All information was stored in the platform's database and visualized using freely available tools. For further analysis, we directly accessed the platform's database with an advanced analytics tool (RapidMiner). Results: We were able to develop an integrated workflow for epidemiological statistics from reports obtained in clinical routine. The report data allowed for automated calculation of epidemiological parameters. Prevalence of PE was 27.6%. The mean age in patients with and without PE did not differ (62.8 years and 62.0 years, respectively, p = 0.987). As expected, there was a significant difference in mean D-dimer values (10.13 and 3.12 mg l^-1 fibrinogen equivalent units, respectively, p < 0.001). Conclusion: SR can make data obtained from clinical routine more accessible. Designing practical workflows is feasible using freely available tools and allows for the calculation of epidemiological statistics on a near realtime basis. Therefore, radiologists should push for the implementation of SR in clinical routine. Summary sentence: Implementing practical workflows that allow for the calculation of epidemiological statistics using SR and freely available tools is easily feasible. Advances in knowledge: Theoretical benefits of SR have long been discussed, but practical implementation demonstrating those benefits has been lacking. Here, we present a first experience providing proof that SR will make data from clinical routine more accessible.