TY - GEN
T1 - Ethical Implications of AI in Healthcare Data: A Case Study Using Healthcare Data Breaches from the US Department of Health and Human Services Breach Portal between 2009-2021
AU - Ugwu, Augustina O.
AU - Gao, Xianghua
AU - Ugwu, Johnson O.
AU - Chang, Victor
N1 - Copyright ©2022 IEEE
PY - 2023/3/23
Y1 - 2023/3/23
N2 - Digital technology in the healthcare industry through Artificial intelligence (AI) tools has laid a solid foundation for more convenient and accessible patient treatment, thereby making lives much more manageable. Recent developments in A I tools in the healthcare industry have heightened the need for healthcare professionals to identify and address ethical issues in digital health care. Notwithstanding the benefits of AI tools, healthcare industry data has become a central target for many cyber invaders in this era of big data, as they are regarded as valuable information. Health care data breaches occur due to unauthorized access to patients’ health records that violate the privacy and security of confidential health information. Therefore, this study aimed to use Microsoft Power BI tools to conduct in-depth data analytics and visualization on healthcare data breaches to determine the causes of the breach and provide insights that will help to enhance healthcare data security and confidentiality. This study observed from the analysis that Hacking /IT incidents are the major predominant types of data breaches in the healthcare industry, followed by unauthorized access/disclosures. This study was able to identify the significant factors that contribute to healthcare data breaches. The insight produced from this study could potentially contribute to our understanding of data breaches and set the benchmark that future security experts will undoubtedly tackle. Therefore, more in-depth studies are highly needed to validate the findings as this study has several important implications for future discovery. All the results are subject to the validity of the dataset analyzed.
AB - Digital technology in the healthcare industry through Artificial intelligence (AI) tools has laid a solid foundation for more convenient and accessible patient treatment, thereby making lives much more manageable. Recent developments in A I tools in the healthcare industry have heightened the need for healthcare professionals to identify and address ethical issues in digital health care. Notwithstanding the benefits of AI tools, healthcare industry data has become a central target for many cyber invaders in this era of big data, as they are regarded as valuable information. Health care data breaches occur due to unauthorized access to patients’ health records that violate the privacy and security of confidential health information. Therefore, this study aimed to use Microsoft Power BI tools to conduct in-depth data analytics and visualization on healthcare data breaches to determine the causes of the breach and provide insights that will help to enhance healthcare data security and confidentiality. This study observed from the analysis that Hacking /IT incidents are the major predominant types of data breaches in the healthcare industry, followed by unauthorized access/disclosures. This study was able to identify the significant factors that contribute to healthcare data breaches. The insight produced from this study could potentially contribute to our understanding of data breaches and set the benchmark that future security experts will undoubtedly tackle. Therefore, more in-depth studies are highly needed to validate the findings as this study has several important implications for future discovery. All the results are subject to the validity of the dataset analyzed.
KW - health data breach
KW - data analysis and privacy
KW - ethical issues for healthcare
KW - big data
KW - artificial intelligence
UR - https://ieeexplore.ieee.org/document/10077083
U2 - 10.1109/IIoTBDSC57192.2022.00070
DO - 10.1109/IIoTBDSC57192.2022.00070
M3 - Conference publication
T3 - Proceedings - 2022 International Conference on Industrial IoT, Big Data and Supply Chain, IIoTBDSC 2022
SP - 343
EP - 349
BT - 2022 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC)
T2 - 2022 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC)
Y2 - 23 September 2022 through 25 September 2022
ER -