Construction and validation of a competency model for hospital operation assistant of public hospitals in China: a cross‑sectional study

To identify and generate the competency items of HOA, we used two strategies: job analysis and literature review. Job analysis is a systematic empirical procedure for collecting and analyzing information about a job and it has been widely used in the field of human resource management [17, 18]. West China Hospital of Sichuan University is the first hospital in Chinese Mainland to implement the HOM system, and it has trained a number of mature HOAs. Therefore, we conducted unstructured interviews with the HOAs of West China Hospital of Sichuan University to obtain the main responsibilities of HOA. The literature review was performed by searching the Web of Science, China National Knowledge Infrastructure, and Wanfang Database. Then we sort out the competency literature related to hospital management and HOM to extracted the competency items of the HOA.

A cross-sectional survey design was used in this study. We sent an online questionnaire to 373 participants who participated in the Hospital Operation Assistant Training Course organized by West China Hospital of Sichuan University. Most of these participants were the directors or HOAs from the hospital operation management department. Of course, some public hospitals in China have not yet established dedicated hospital operation management departments, but these Chinese hospital directors have realized the significance of HOM and promoted relevant work by assigning the hospital operation management functions to other departments such as performance management departments, human resources departments, etc. [19]. Therefore, some participants in the training course were the directors or management cadres who came from the hospital human resource management department, performance management department, and finance department and so on. The questionnaire contained three sections: hospital information, personal information, and the importance ratings for competency items. All items were rated using a 5-point Likert scale, ranging from “very unimportant” (1 point) to “very important” (5 points) (Additional file 1).

Descriptive statistical indicators were calculated to describe the characteristics of sample data. Continuous variables were described using mean and standard deviation, while categorical variables were analyzed using frequency, percentage and full-score proportion. Cronbach’s alpha (Cronbach’s α) coefficient, the Kaiser-Mayer-Olkin (KMO) sampling adequacy test and Bartlett’s sphericity test were used to test the reliability and validity of the questionnaire [20].

Exploratory factor analysis (EFA) was used [21]. Factors were extracted according to the principle that the initial eigenvalues were greater than 1.0 and the varimax rotation method was used to identify the role of each factor clearly [22, 23]. We used covariance-based structural equation model to analysis the relationship between the factors. The competency model path map was drawn and the standardized path coefficients were calculated [24]. Then, we used the second-order confirmatory factor analysis to validate the model’s fitting effect including fitting validity, convergent validity and discriminant validity. We used root-mean-square error of approximation (RMSEA < 0.080), standardized root mean square residual (SRMR < 0.080), comparative fit index (CFI > 0.90) and Tucker-Lewis index (TLI > 0.90) to test the fitting validity [25‐27]. The standardized factor load, composite reliability (CR > 0.800) and average variance extracted (AVE > 0.500) were used to verify the convergence validity [28, 29]. The relationship between the square root of AVE and the correlation coefficient between factors was used to identify the discriminant validity. If the square root of AVE is greater than the correlation coefficient between factors, the discriminant validity is good [28‐30]. All the data were analyzed by SPSS 19.0 and AMOS 23.0.

The study did not address privacy or ethical issues and all methods were carried out in accordance with relevant guidelines and regulations. First, we provided all participants with written survey information and promised that the survey results would only be used for scientific research. So, all informed consent was obtained from all subjects. Second, an anonymous survey was adopted. Finally, participants had the right to refuse to answer questions or withdraw from the study at any time.

After job analysis, we concluded the main responsibilities of the HOA as follows.

From the results of job analysis, HOA needs lots of professional knowledge, skills, and experience. Ulteriorly, based on the job analysis results and literature review, we screened out 23 competency items of HOA preliminarily and made a summary definition of these items (Table 1).

We collected a total of 318 questionnaires from 153 hospitals in 25 provinces of China. The response rate was 85.25% (318/373). Nine were excluded because of incomplete answers, which left 309 useable questionnaires. All the respondents were aged 23 to 57 years, among whom 47.57% were aged 31 to 40 years, 70.87% were females, 55.02% had obtained a bachelor’s degree, 41.74% had obtained a master’s degree or a doctor’s degree, 86.41% were from tertiary hospitals, and 58.90% were directly engaged in the work of HOM (Table 2).

The mean score, maximum score, and minimum score of the 23 competency items of HOA were 4.62,4.82 and 4.22, respectively. The standard deviation of each item was less than 1.00. The highest full-score proportion of the items was 83.17%, and the lowest was 40.13% (Table 3).

The Cronbach’s α coefficient of the competency questionnaire was 0.957, which was greater than 0.900, indicating that the questionnaire items had good internal consistency. The KMO value was 0.964, which was greater than 0.900, indicating that the structural validity of the questionnaire items was very good. Bartlett’s sphericity test showed that the χ² value was 7067.029 (P < 0.001), indicating that there was a strong correlation between competency items, which confirmed the appropriateness of the factor analysis technique.

Three principal factors were extracted according to the principle that the initial eigenvalues were greater than 1.0. These factors cumulatively explained 67.60% of the total variance, which was basically acceptable. After varimax rotation, all the items had factor loadings greater than 0.50, so they were all retained (Table 4).

Factor 1 included eight competency items (data processing and analysis, language and writing ability, structured thinking, interpersonal communication, innovation ability, teamwork and cooperation, adaptability and self-improvement), which reflected the basic professional skills that the HOA should have, so it was named “professional skills”. Considering that the contents of 7 items (financial and economic knowledge, management theoretical knowledge, medical knowledge, statistical knowledge, social science knowledge, medical experience and management experience) under factor 2 reflected the professional knowledge of the HOA, so we named it “professional knowledge”. The 8 items (anti-pressure ability, open-minded, empathy, self-evaluation, sense of responsibility, professional identity, organizational identity and organizational loyalty) under factor 3 reflected the psychological quality and professional sense of the HOA, so we named factor 3 “personality traits”.

According to the results of factor analysis, taking the competency of the HOA as the second-order potential variable, “professional skills”, “professional knowledge” and “personality traits” as the first-order potential variables, and the 23 competency items as the observation variables of the three factors, the competency model path map was drawn and the standardized path coefficients were calculated by using AMOS 23.0. The standardized path coefficient of professional skills, professional knowledge and personality traits were 0.86, 0.82 and 0.98 respectively. The competency items’ standardized path coefficients were all greater than 0.50. All these standardized path coefficients were significant (p < 0.001). The final path map of the competency model with 3 factors and 23 items is illustrated in Fig. 1.

The overall model fitness was acceptable, where the RMSEA (0.077) and SRMR (0.062) were both less than 0.08, and the CFI (0.927) and TLI (0.918) indexes were both greater than 0.90. According to the results that all the standardized path coefficients were greater than 0.50 (P < 0.001), the CRs of all dimensions were all greater than 0.800, and the AVEs were above 0.500, the model had good convergence validity (Table 5). The results showed the correlation coefficients between the three factors were all less than or very close to each square root of AVE, indicating the competency model of HOA had good discriminant validity (Table 6).

Our study had several limitations. Although the samples for the study were extensive, covering 153 hospitals in 25 provinces of China, no distinction was made between different levels or types of public hospitals. In the future, it is necessary to further expand the scope and the number of survey samples for deep exploration. Another limitation is that our sampling method was not strictly random and the answers could be biased. In addition, further research needs to be conducted on how to accurately measure each competency item.