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Healthsurance – Mobile App for Standardized Electronic Health Records Database

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Data Management and Analytics for Medicine and Healthcare (DMAH 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10494))

Abstract

With the increasing popularity of Electronic Health Records (EHRs), there arises a need to understand its importance in terms of clinical contexts for a standard based health application. Standards for semantic interoperability propose the use of archetypes for building a health application. A usual practice followed for storing of EHRs is through graphical user interfaces. Generally, user interface is static corresponding to the underlying medical concept, often made manually and are prone to errors. However, evolution in knowledge demands for dynamically generated user interfaces to reduce time, minimize cost and enhance reliability. Current research implements mobile app for standardized Electronic Health Records Database termed as HEALTHSURANCE. The application maintains its dynamic behavior through creation of graphical user interfaces at runtime by gaining knowledge from the artefacts (known as archetypes) available from standard clinical repositories (such as Clinical Knowledge Manager). This provides easy and hassle-free user operability without any need of mobile developer. A standardized format and content helps to uplift the credibility of data and maintains a uniform and specific set of constraints used to evaluate the user’s health. A generic centralized database is chosen for data storage to support evolution in clinical knowledge and to handle heterogeneity of EHRs data. Implementing mobile app based on archetype paradigm avoids reimplementation of systems, migrating databases and allows the creation of future-proof systems.

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Correspondence to Shelly Sachdeva .

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Jain, P., Bhargava, S., Jain, N., Sachdeva, S., Batra, S., Bhalla, S. (2017). Healthsurance – Mobile App for Standardized Electronic Health Records Database. In: Begoli, E., Wang, F., Luo, G. (eds) Data Management and Analytics for Medicine and Healthcare. DMAH 2017. Lecture Notes in Computer Science(), vol 10494. Springer, Cham. https://doi.org/10.1007/978-3-319-67186-4_11

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  • DOI: https://doi.org/10.1007/978-3-319-67186-4_11

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