This paper presents the study of Multi Document Summarization (MDS) of medical documents with the help of clustering model and building dictionaries. This paper also tells about efficiency of the method in practical abstract. This paper aims to reduce the complexity of the process by using the sequence of different methods. A summary generated from this method is evaluated against human written summaries. The objective of the multi document summarization is to generate an efficient summary with the help of sequencing a series of methods and algorithms. It also takes the keyword from the document and makes a local dictionary which is helpful in extracting summary from the document.It generates dramatically better summaries than an extractive summaries based on sentence extraction, reordering components and omitting useless words or lines. This presents an inter clustering method that takes events, topics or points from multiple clusters as inputs and then selects the most salient and relevant points to make the output. This also provides users a control over the summarization process using different methods. Besides the general idea and concept, we discuss the benefits and limitations concerning these methods. With the aim of enhancing MDS with this approach we can generate a better summary. © Research India Publications.