Application of latent class analysis in assessing the competency of physicians in China

Abstract

Background

The physicians’ competency is an important public health issue around the world. Several international organizations have taken the lead in examining the competencies required to be a physician. The purpose of this study is to identify subgroups of physicians’ competency based upon the importance results of competency evaluation and provide a scientific basis for the qualitative research of the competency of physicians.

Methods

A cross-sectional study was conducted on a large population-based sample in 31 provinces, autonomous regions and municipalities directly under the central government in China. The latent class analysis was performed to identify patterns of physicians’ competency using M-plus software.

Results

In this study, the latent class analysis was adopted to identify the appropriate number of distinct latent classes of physicians’ competency based on eight competency dimensions, and a four-class model best fit the data, which are excellent competency group, lack of professionalism competency group, individual competency driven group, and lack of competency cognitive group. Therefore, 6247 physicians can be divided into four latent classes based on the importance results of competency evaluation, and the number of each class is 5684, 284, 215 and 64, respectively.

Conclusion

These findings suggested that latent class analysis can be used to study the competency of physicians, and four distinct subgroups were identified. Therefore, we can effectively understand the patterns of physicians’ competency, and the health administrative departments could utilize more specific measures according to their different competency subgroups, and providing individualized training schemes in the future training and management of physicians.

Electronic supplementary material

The online version of this article (10.1186/s12909-017-1039-4) contains supplementary material, which is available to authorized users.