Access and Privacy Control for Healthcare Decision Support System: A Smart Medical Data Exchange Engine (SMDEE)

ABSTRACT Secure and automated sharing of medical information among different medical entities/stakeholders like patients, hospitals, doctors, law enforcement agencies, health insurance companies etc., in a standard format has always been a challenging problem. Current methods for ensuring compliance with medical privacy laws require specialists who are deeply familiar with these laws' complex requirements to verify the lawful exchange of medical information. This article introduces a Smart Medical Data Exchange Engine (SDEE) designed to automate the extracting of logical rules from medical privacy legislation using advanced techniques. These rules facilitate the secure extraction of information, safeguarding patient privacy and confidentiality. In addition, SMDEE can generate standardised clinical documents according to Health Level 7 (HL7) standards and also standardise the nomenclature of requested medical data, enabling accurate decision‐making when accessing patient data. All access requests to patient information are processed through SMDEE to ensure authorised access. The proposed system's efficacy is evaluated using the Health Insurance Portability and Accountability Act (HIPAA), a fundamental privacy law in the United States. However, SMDEE's flexibility allows its application worldwide, accommodating various medical privacy laws. Beyond facilitating global information exchange, SMDEE aims to enhance international patients' timely and appropriate treatment.

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Publication Details

Journal
CAAI Transactions on Intelligence Technology
Published
2025-10-31
DOI
https://doi.org/10.1049/cit2.70077
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
0.00

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article

Access and Privacy Control for Healthcare Decision Support System: A Smart Medical Data Exchange Engine (SMDEE)

Javed Rashid, Muhammad Shoaib Saleem, Anwar Ghani, Humera Khan et al.
CAAI Transactions on Intelligence Technology
Privacy-Preserving Technologies in Data
article

Access and Privacy Control for Healthcare Decision Support System: A Smart Medical Data Exchange Engine (SMDEE)

Javed Rashid, Muhammad Shoaib Saleem, Anwar Ghani, Humera Khan, Muhammad Faheem, Imran Khan
article en

Abstract

ABSTRACT Secure and automated sharing of medical information among different medical entities/stakeholders like patients, hospitals, doctors, law enforcement agencies, health insurance companies etc., in a standard format has always been a challenging problem. Current methods for ensuring compliance with medical privacy laws require specialists who are deeply familiar with these laws' complex requirements to verify the lawful exchange of medical information. This article introduces a Smart Medical Data Exchange Engine (SDEE) designed to automate the extracting of logical rules from medical privacy legislation using advanced techniques. These rules facilitate the secure extraction of information, safeguarding patient privacy and confidentiality. In addition, SMDEE can generate standardised clinical documents according to Health Level 7 (HL7) standards and also standardise the nomenclature of requested medical data, enabling accurate decision‐making when accessing patient data. All access requests to patient information are processed through SMDEE to ensure authorised access. The proposed system's efficacy is evaluated using the Health Insurance Portability and Accountability Act (HIPAA), a fundamental privacy law in the United States. However, SMDEE's flexibility allows its application worldwide, accommodating various medical privacy laws. Beyond facilitating global information exchange, SMDEE aims to enhance international patients' timely and appropriate treatment.

CAAI Transactions on Intelligence TechnologyVol. 10(6)
Khazar University (AZ), Northern Border University (SA), International Islamic University, Islamabad (PK), Indian Institute of Technology Kharagpur (IN), University of Okara (PK), Nazarbayev University (KZ), University of Vaasa (FI), VTT Technical Research Centre of Finland (FI)
Teknologian Tutkimuskeskus VTT
Openalex Percentile: Top 83%
Privacy-Preserving Technologies in Data
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