A physician extensively relies on computers for collection of data, Insurance, analysis of medication and also his schedule. The same applies to the service receiver that is the patient. This process involves interacting with different web domains. Web service refers to a software system which was formulated for supporting inter-operable machine-to-machine interactions across networks. At times, one web service provided alone does not fulfill user requirements. In most cases, many web services are required to be composed for achieving the user’s aim. A number of web services offer the same functionalities however, they vary in non-functional Quality of Service (QoS) requirements. Given ‘m’ abstract service and ‘n’ concrete services for every abstract service, there are nm possibilities of composed solutions. As a result, the search space has large number of composed web services. Therefore it is necessary to discover the best composed web service with QoS constraints. The existing work addresses the web service composition task by considering various QoS constraints like Availability, Reliability, Response Time as well as Execution Costs. The Particle Swarm Optimization (PSO) protocol is applied for finding optimum solution by mapping the particles with the composed workflow. The proposed work combines PSO with Genetic Algorithm (GA) to improve the results of PSO since standard PSO is capable of rapidly causing particles to stagnate as well as premature convergence on sub-optimum solutions. The results show that the suggested hybridized model performs better than the standard PSO.