Simplifying conversion from structured reporting templates in PACS to openEHR-based reports : Facilitating mapping from structured reports to openEHR through a tool to increase semantic interoperability

Sammanfattning

Interoperability within the healthcare sector means the ability to share medical data in an organized manner. To achieve interoperability there is a need for structures and standards on multiple levels, including the semantic level. openEHR is an open framework that works to improve this area by providing technical standards for data within an electronic health record, but these standards are not yet widely used in Sweden. There is, however, already a lot of medical data being produced. One method used for writing reports within the healthcare sector is Structured Reporting (SR). These reports get their structure from SR templates and the fields in these templates can in theory be matched to fields in an openEHR template to make the report openEHR compatible. The process of matching fields between SR templates and openEHR templates is known as mapping. This thesis project investigates what the mapping process looks like today, what difficulties are associated with it, and how they can be alleviated. After interviewing informaticians it was found that the work they do is still largely manual in nature and could benefit from partial automatization. When two fields are being mapped, the person doing the mapping has to write out or copy the path to each field. This can be a time consuming task, especially for more complex templates where a deep structure creates long paths. From this it was decided the thesis would develop a tool with a graphical user interface which can produce and store the correct paths for mapped fields. Another issue with the state of mapping is the differences between SR and openEHR. A secondary focus of this thesis is thus looking at to what extent mapping is possible and why any unmapped fields could not be mapped. The resulting tool is a web application that can produce a mapping configuration file based on user input. The application takes SR and openEHR templates as input and after pre-processing, displays them in two separate tree structures. The user can then click on a node in each tree and map these to each other. The main benefits of the web application are the simple graphical user interface, the automatic generation of paths, and the pre-processing of the SR templates. To further reduce the manual labor associated with the mapping process future efforts should be made on implementing artificial intelligence and natural language processing. However, it should be stated that the real goal is for medical data to be openEHR compatible to begin with, completely erasing the need for mapping in the first place. The mappings possible in the application did not achieve 100% coverage for any of the SR or openEHR templates used in this project. While some of the disconnect can be erased by implementing further functionalities in the application, the results still show that there is currently a disconnect between the two structures. Neither SR nor openEHR has a widespread use, and as more work is done on implementing both SR and openEHR in healthcare there should be an awareness of the other structure to reduce the disconnect at the source. The effect that SR and openEHR have on interoperability today is therefore hard to conclude.