Desirability Optimization Based on the Poisson Regression Model: Estimation of the Optimum Dental Workforce Planning

Abstract

Aim: This study aims to estimate the optimum number of dentists needed by determining the social and economic variables that affect the dental workforce planning in Turkey. Method: A desirability optimization model based on the Poisson regression model was used to evaluate the importance of the variables of this study and to calculate the optimum values of the variables. The data used in the study cover the years 1960-2018. Population (x_p), gross domestic product per capita (x_pc), life expectancy (x_le), and literacy rate (x_lr) were considered as input variables affecting the dental workforce (y_d). Findings: The values of deviance R2, adjusted R2, and Akaike Information Criterion (AIC) were computed as 0.9941, 0.9941, and 960.11, respectively, which confirm the validity of the Poisson statistical test. The dual mechanism reliability was obtained by adhering to the 'what-if' perspective and desirability values of the top-ten optimum values of the dental workforce. Conclusion: The results of the study show that social and economic determinants play an important role in the estimated dental workforce planning assessment required for oral and dental health in Turkey.