2017
DOI: 10.14569/ijacsa.2017.081160
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Analysis and Formal Model of RFID-Based Patient Registration System

Abstract: Abstract-Patient Registration System (PRS) is an important part of hospital environment. Therefore, semiformal model of Patient Registration System that registers the patients by assigning Radio Frequency Identification (RFID) card or bracelet is presented in this paper. The existing Patient Registration Systems do not properly work due to ambiguities and semiformal modeling techniques. However, that is why we will propose formal modeling for PRS using Vienna Development Method (VDM-SL). Firstly, we develop th… Show more

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Cited by 2 publications
(1 citation statement)
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“…Positive patient identification (PPI) applications using RFID technology may include a smart wristband with a passive RFID tag, that can be scanned to identify patients and reveal information such as date of birth, name, insurance information, allergies, blood type and medication requirements (6,7). Several studies suggest that hospitals should work to prevent these errors from occurring by implementing a satisfactory patient identification system that can improve the safety procedures of hospitals (2,15,20,21). Likewise, (14,32) suggest that smart RFID technologies can potentially minimize errors resulting from misidentifications of patients.…”
Section: • Patient Identificationmentioning
confidence: 99%
“…Positive patient identification (PPI) applications using RFID technology may include a smart wristband with a passive RFID tag, that can be scanned to identify patients and reveal information such as date of birth, name, insurance information, allergies, blood type and medication requirements (6,7). Several studies suggest that hospitals should work to prevent these errors from occurring by implementing a satisfactory patient identification system that can improve the safety procedures of hospitals (2,15,20,21). Likewise, (14,32) suggest that smart RFID technologies can potentially minimize errors resulting from misidentifications of patients.…”
Section: • Patient Identificationmentioning
confidence: 99%