Abstract
With the advancement in technology, data is also growing exponentially. Storing this BIG DATA in an efficient manner is the key for any successful project. Work done in this paper is dedicated towards presenting the possible efficient ways available to store Electronic Health Records (EHRs). The main hurdles in storing EHRs are sparseness and volatility which relational model is incapable to handle. The other models present for storing EHRs are Entity Attribute Value (EAV), Dynamic Tables, Optimized Entity Attribute Value (OEAV) and Optimized Column Oriented Model (OCOM). Authors have provided a comparative study which will help the administrator to choose the best model among the models specified above. Authors have also discussed about the different scenarios (standardized and non-standardized EHRs) in which a combination of these models can be used. Authors have simulated EAV, Dynamic tables, OEAV and OCOM models to provide comparison results of time taken for executing basic operations (queries) and memory consumed by different models.
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Batra, S., Sachdeva, S. (2014). Suitability of Data Models for Electronic Health Records Database. In: Srinivasa, S., Mehta, S. (eds) Big Data Analytics. BDA 2014. Lecture Notes in Computer Science, vol 8883. Springer, Cham. https://doi.org/10.1007/978-3-319-13820-6_2
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DOI: https://doi.org/10.1007/978-3-319-13820-6_2
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