A Sequential Structural Equation Modeling of Patient Satisfaction and Compliance to Treatment

With the renewed concern about health care quality, there is a need for improved surveillance tools and focus on special age groups. While Structural Equation Model (SEM) an important tool surveillance, prediction measuring intervention impact, to reduction in bias necessitates modification of SEM with Sequential (SSEM) study some specific groups delivery. This formulated model patient satisfaction compliance treatment using SSEM two stopping times exogenous, endogenous mediating variables that generally influence modelling Patient Satisfaction (PS) Compliance Treatment (CT) involves four latent (factors) manifest (dependent) variables. Statistical Packages Social Sciences (SPSS) Linear Relationship (LISREL) 8.80 were adopted analysis. The established fitted indices second time meet threshold rules all cases when various fitting used, result revealed insignificant PE HS [R2 =0.012, F = 3.199, P >.05]. indicates contributed insignificantly HS. Therefore, this concluded procedure sequential hypothesised relationship showed useful drive towards quality satisfaction. Hence, confirmed demographic are significant experience.