Data Cleaning Framework for Healthcare Applications

Abstract

RFID technologies are used in various applications ranging from traditional applications such as access control, electronic toll collection, e-ID documents to modernizing applications such as asset management, baggage handling, cargo tracking/security, contactless payment and ticketing, supply chain management and healthcare. Of these medical healthcare applications are of more importance because minute errors in it can cost heavy financial and personal losses. Data captured by RFID reader often has errors including false negatives, false positives and duplicates. In order to provide reliable data to RFID application, it is necessary to clean the collected data. In this paper we have suggested physical solutions to solve missed readings, middleware solutions to overcome anomalies found within the reader and finally rule based solutions to correct various anomalies already exist in the database. Drawbacks of the methodologies are also discussed and some solutions are suggested. With the aid of the planned data cleaning technique we can bring down the health care costs, optimize business processes, streamline patient identification processes and improve patient safety. The security and privacy issues of RFID , and their solutions are also discussed.

Authors and Affiliations

Anne Leema A, Dr. M. Hemalatha

Keywords

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  • EP ID EP140890
  • DOI 10.9756/BIJRCE.1007
  • Views 108
  • Downloads 0

How To Cite

Anne Leema A, Dr. M. Hemalatha (2012). Data Cleaning Framework for Healthcare Applications. Bonfring International Journal of Research in Communication Engineering, 1(1), 31-33. https://europub.co.uk/articles/-A-140890