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Clinical coders' work engagement under China's healthcare payment reform: A cross-sectional study
Yicong Xu1, Jingya Zhou2,3,4, Zhenghua Liu5
1Medical Records Room, Department of Medical Administration, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Background:
The accuracy of clinical coding, which is essential for supporting managerial and policy decisions such as funding formulas, is closely tied to the work engagement of clinical coders.
Objective:
This paper aimed to evaluate the level of work engagement and associated factors among clinical coders through a nationwide survey in China.
Method:
Thirty-one tertiary public hospitals in China were selected via convenience sampling, and 354 clinical coders were surveyed with Question-star software. Work engagement was measured using the 17-item Chinese version of the Utrecht Work Engagement Scale (UWES), with each item rated from 0 to 6. Twenty-two potentially related variables were collected. Descriptive statistics and one-sample t-tests (vs UWES norms) were used to assess work engagement levels. Cluster analysis was performed to identify engagement patterns. Independent-samples t-tests or one-way analysis of variance were used to examine engagement differences across the 22 variables. Variables with p < 0.05 in univariate analysis were entered into multiple linear regression to identify associated factors.
Results:
The mean work engagement score among clinical coders was significantly lower than the UWES-17 norm (3.26 vs 3.82; t = -8.378, p < 0.001). The participants were classified into three engagement groups: high (29.5%), moderate (50.7%), and low (19.8%). Multiple linear regression analysis revealed seven variables that were significantly associated with work engagement (F (7, 331) = 11.493, p < 0.001, R2 = 0.196): region, continuing education, ideal clinical coding software, work position, perceived leadership support, physician-coder communication and sex.
Conclusion:
Clinical coders in China demonstrated moderate-to-low work engagement, shaped primarily by objective career development conditions, along with their perceived software support and organizational support.Implications for health information management practice:Enhancing work engagement requires managerial focus on continuing education, software usability, and perceived leadership support.
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