JMIR Publications

ABSTRACT

Background:

Coronavirus disease 2019 (COVID-19) was discovered in China since December 2019, it has developed into an extremely threatening emergency for international public health. Except for China, the number of cases in other countries continues to increase. Lots of studies about disease diagnosis and treatment have been carried out and many clinically proven effective results have been achieved. Although information technology can improve the transferring of such knowledge to clinical practice rapidly, data interoperability is still a challenge due to the heterogeneous nature in hospital information systems. This issue becomes even more serious if the knowledge for diagnosis & treatment is updated rapidly like the one for COVID-19. An open, semantic sharing and collaborative information modeling framework is needed to rapidly develop a shared data model for exchanging data among systems. openEHR is such a framework supported by many open software that help to promote information sharing and interoperability.

Objective:

The study aims to develop a shared data model based on the openEHR modeling approach to improve the interoperability among systems for the diagnosis and treatment of COVID-19.

Methods:

The latest Guideline of COVID-19 Diagnosis & Treatment in China is selected as the knowledge source for modeling. First, the guideline was analyzed and the data items used for Diagnosis&Treatment/Management were extracted. Second, the data items were classified and further organized into domain concepts with mind map. Third, searching was executed in the international openEHR Clinical Knowledge Manager (CKM) to find the existing archetypes which can represent the concepts. New archetypes were developed for those concepts that cannot be found. Fourth, these archetypes were further organized into a template using Ocean Template Editor. Finally, a test case of data exchanging between CDR and CDSS based on the template has been conducted to verify the feasibility of the study.

Results:

22 archetypes have been used to develop the template for all data items extracted from the guideline. All of them could be found in CKM and reused directly. The archetypes and templates were reviewed and finally released in a public project within the CKM. The test case showed that the template can facilitate the data exchanging and meet the requirements of decision support.

Conclusions:

This study has developed the openEHR template for COVID-19 based on the latest guideline of China using openEHR modeling methodology. It represented the capability of the methodology of rapidly modeling and sharing knowledge through re-using the existing archetypes, which is especially useful in a new-coming and fast-changing area such as the one for COVID-19.