Analysis of Relevant Factors Influencing the Development of Pharmacist Human Resources in China: Based on the Time Series Vector Auto-Regression Model

Objective: To analyze and predict the dynamic influence trends and degrees caused by various factors that may affect the expansion of the hospital pharmacist team in China.

Methods: Time series data including the number of hospital visits in all hospitals in China, the total number of pharmacists, per capita health expenditure, and per capita GDP from 2002 to 2022 were collected at the national level. A vector autoregressive (VAR) model was constructed, and methods such as the Granger causality test, impulse response analysis, and variance decomposition were employed to explore the influence process and direction of various influencing factors on the number of pharmacists in China.

Results: The Augmented Dickey-Fuller (ADF) test indicates the first-order difference series of the time series is stationary (P<0.05). The model stability test shows the modulus of all specific root reciprocals falls within the unit circle, indicating model stability and credible results. The cointegration test reveals a cointegration relationship among the number of hospital visits, per capita health expenditure, per capita GDP, and the number of pharmacists (P<0.05). The Granger causality test indicates a unidirectional Granger causality relationship between the number of hospital visits, per capita health expenditure, and the number of pharmacists. The impulse response function indicates that the number of pharmacists shows an upward trend after being impacted by one unit of the number of hospital visits and per capita GDP, while the positive impact of per capita health expenditure on the number of pharmacists turns into a negative impact in the third stage. Variance decomposition shows that the contribution rate of the number of hospital visits to the number of pharmacists is 12%, the contribution rate of per capita health expenditure to the number of pharmacists is 57%, and the contribution rate of per capita GDP to the number of pharmacists is 80%.

Conclusion: The number of hospital visits, per capita health expenditures, and per capita GDP all positively contribute to the development of the pharmacist workforce. Per capita health expenditures lead to an increase in the number of pharmacists in the short term. Among the selected indicators, the primary drivers of pharmacist workforce development are per capita health expenditures and per capita GDP. Hospital visits have a relatively minor contribution to the growth in the number of pharmacists.