Md Manarat Uddin, Mithun and Rahanuma, Tarannum and Sakhawat Hussain, Tanim (2025) Privacy-Aware Analytics for Managing Patient Data in SMB Healthcare Projects. International Journal of Informatics and Data Science Research, 2 (10). pp. 27-57. ISSN 2997-3961
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Abstract
Healthcare-providing organizations of small-to-medium-sized businesses (SMB healthcare) are also turning to data analytics to enhance patient outcomes, streamline processes, and aid the decision-making process of clinicians. The studied research paper concerns itself with privacy-constrained analytics to the utilization of patient data, where the used healthcare projects of small and medium-sized business (SMB) balance between a robust usage of data privacy security, and an actionable knowledge for decision-making. As the trend of digital healthcare systems being dependant grows, there is a very real need for SMB healthcare providers to be careful not merely in meeting the strict requirements of the various regulations of data protection but also to make good use of patient data in their operations to reduce costs and achieve a high level of care outcomes. In order to build a complete framework of privacy-preserving and yet secure data management in healthcare, the study applies advanced analytics based on the Python programming language to process the data and Tableau as a visualization tool. The methodology is incorporated by combining encryption protocols, secure access controls, anonymization techniques and compliance monitoring software in ensuring the sensitivity of the information without compromising data utility. A comprehensive examination of real world data and privacy-compliance-based measures reveals how small- and medium-sized healthcare organizations can implement scalable, cost-efficient solutions that comply with HIPAA and GDPR guidelines, yet also allow informed decision-making and drive them forward. Outputs of visual analytics provide explicit visualizations of the pattern of patient data, compliance adherence, and possible privacy concerns, which satisfies the expectations of stakeholders, who can learn the relevance of complex data without breaching the privacy of data subjects. The results indicate that the offered privacy-aware analytics strategy is an optimal strategy that can effectively eliminate the risks of unauthorized data access, increase regulatory compliance, and increase the general trustworthiness to healthcare services. Also, the paper isolates major gaps in the prevailing SMB healthcare data management systems and describes future studies opportunities to incorporate blockchain and artificial intelligence-based security approaches related to improved privacy protection. This study adds to the growing market of governance challenges toward the use of healthcare data, creating a replicable technology-based solution that can balance the competing interests of security, compliance and utility ultimately enabling SMB healthcare providers to succeed within the regulation and data-driven healthcare system.
Item Type: | Article |
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Subjects: | Q Science > Q Science (General) |
Divisions: | Postgraduate > Master's of Islamic Education |
Depositing User: | Journal Editor |
Date Deposited: | 18 Oct 2025 09:27 |
Last Modified: | 18 Oct 2025 09:27 |
URI: | http://eprints.umsida.ac.id/id/eprint/16433 |
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