JMIR Publications

ABSTRACT

Background:

In China, there are two major government incentives in the development of health informatics, yet there have been limited systematic investigations on the pattern of interactions between informatics concepts/techniques and the health/medical needs.

Objective:

We propose an approach to mapping the interplay between different knowledge entities by using the tree structure of Medical Subject Headings (MeSH) to gain insights into the interactions between informatics-supply and health-demand in China.

Methods:

All terms under the MeSH tree parent node “Diseases [C]” or node “Health [N01.400]” or “Public Health [N06.850]” were labelled as H. All terms under the node “Information Science [L]” as I and all terms under node “Analytical, Diagnostic and Therapeutic Techniques, and Equipment [E]” as T. The H-I and H-I-T interactions can be measured by using their co-occurrences in a given publication.

Results:

Health informatics publications with both H- and I-related MeSH terms increased rapidly in China. The overall H-I interactions are sparse, focusing on several major diseases and two major informatics techniques. A weaker H-I-T linkage is observed and the technology transfer for health informatics is suggested to be enhanced. There is a positive correlation between the burden and the informatics research efforts for diseases. Artificial Intelligence (AI) is a competing field of health informatics research, with a greater focus on deep neural networks.

Conclusions:

Research on evidence-based health informatics, and electronic health records (EHRs) should be strengthened to improve the real-world applications of health information technologies and big data in health and medicine in the future.