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Data Privacy and Ethical Issues in Collecting Health Care Data Using Artificial Intelligence Among Health Workers.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Data Privacy and Ethical Issues in Collecting Health Care Data Using Artificial Intelligence Among Health Workers./
作者:
Gabriel, Orum Terese.
面頁冊數:
1 online resource (133 pages)
附註:
Source: Masters Abstracts International, Volume: 85-07.
Contained By:
Masters Abstracts International85-07.
標題:
Medical ethics. -
電子資源:
click for full text (PQDT)
ISBN:
9798381410549
Data Privacy and Ethical Issues in Collecting Health Care Data Using Artificial Intelligence Among Health Workers.
Gabriel, Orum Terese.
Data Privacy and Ethical Issues in Collecting Health Care Data Using Artificial Intelligence Among Health Workers.
- 1 online resource (133 pages)
Source: Masters Abstracts International, Volume: 85-07.
Thesis (M.Sc.)--Center for Bioethics and Research, 2023.
Includes bibliographical references
Background: Artificial intelligence (AI) is being rapidly used in healthcare systems due to the extensive amount of data collected and documented every day in medical practice. Data collection using artificial intelligence is increasing and this necessitates ethical issues to be addressed. The aim of this research is was to investigate the knowledge and practice of the Protection and privacy of healthcare workers towards patients' data collected using Artificial intelligence.Methods: This study was conducted using a quantitative and qualitative research design. A survey questionnaire was administered to a sample 384 health workers involved in healthcare data collection using AI. The questionnaire consisted of closed-ended questions and a key informant interview was carried out and was designed to collect information on the awareness, knowledge, and attitudes of health workers on data privacy and ethical issues in collecting healthcare data using AI. Data was analyzed using descriptive statistics such as proportions and percentages and presented as table and figures for questionnaire and Thematic discourse was used to describe the data from the key informant interview. Results: The study collected 232 questionnaires out of 384 from healthcare professionals, resulting in a response rate of 60.4%. The respondents included various healthcare professions, with the majority being nursing staff (43.5%) and medical doctors (22.8%). The results showed that a significant majority of respondents (84.9%) were familiar with artificial intelligence (AI), and 59.1% stated that healthcare data is not collected using AI. However, 76.7% believed that AI can effectively analyze patient medical data. The study revealed that healthcare workers generally recognized the importance of AI in medicine, particularly in early disease diagnosis. Concerns regarding privacy, confidentiality, ethical issues, and potential risks associated with AI-based healthcare data collection were also evident. The most significant ethical issues identified by respondents were privacy and data security (60.8%) and obtaining informed consent (41.8%). The study highlighted the need to address privacy and data security concerns while promoting transparency and accountability in AI algorithms. Regarding patient consent for data collection, 74.6% preferred broad consent, while 25.9% favored explicit consent for each specific use case. The research emphasized the importance of good management of patient records, including storage, policies, access, and security. Paper/file methods were predominantly used for data storage (82.2%), with varying levels of confidence in the security measures. The majority of respondents recognized the need for industry collaboration and standardization to safeguard healthcare data collected using AI. The key informant interview results showed that health workers in FMC possess a general understanding of AI technologies, but the use of AI in collecting health data is not widespread; health workers show a positive attitude towards using AI for data collection, acknowledging its potential to enhance healthcare services; ethical concerns related to data privacy, security, and potential misdiagnosis arise with the use of AI in healthcare; management of patient records relies on traditional physical documentation methods, indicating a lack of digital solutions; and there are no specific regulations or legal frameworks dedicated to AI in healthcare, but existing regulations address privacy and ethical issues. To mitigate ethical dilemmas, suggestions include staff training, upholding ethical principles, and incorporating ethical considerations in the development and governance of AI systems in healthcare.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024
Mode of access: World Wide Web
ISBN: 9798381410549Subjects--Topical Terms:
559096
Medical ethics.
Subjects--Index Terms:
Healthcare systemsIndex Terms--Genre/Form:
554714
Electronic books.
Data Privacy and Ethical Issues in Collecting Health Care Data Using Artificial Intelligence Among Health Workers.
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Background: Artificial intelligence (AI) is being rapidly used in healthcare systems due to the extensive amount of data collected and documented every day in medical practice. Data collection using artificial intelligence is increasing and this necessitates ethical issues to be addressed. The aim of this research is was to investigate the knowledge and practice of the Protection and privacy of healthcare workers towards patients' data collected using Artificial intelligence.Methods: This study was conducted using a quantitative and qualitative research design. A survey questionnaire was administered to a sample 384 health workers involved in healthcare data collection using AI. The questionnaire consisted of closed-ended questions and a key informant interview was carried out and was designed to collect information on the awareness, knowledge, and attitudes of health workers on data privacy and ethical issues in collecting healthcare data using AI. Data was analyzed using descriptive statistics such as proportions and percentages and presented as table and figures for questionnaire and Thematic discourse was used to describe the data from the key informant interview. Results: The study collected 232 questionnaires out of 384 from healthcare professionals, resulting in a response rate of 60.4%. The respondents included various healthcare professions, with the majority being nursing staff (43.5%) and medical doctors (22.8%). The results showed that a significant majority of respondents (84.9%) were familiar with artificial intelligence (AI), and 59.1% stated that healthcare data is not collected using AI. However, 76.7% believed that AI can effectively analyze patient medical data. The study revealed that healthcare workers generally recognized the importance of AI in medicine, particularly in early disease diagnosis. Concerns regarding privacy, confidentiality, ethical issues, and potential risks associated with AI-based healthcare data collection were also evident. The most significant ethical issues identified by respondents were privacy and data security (60.8%) and obtaining informed consent (41.8%). The study highlighted the need to address privacy and data security concerns while promoting transparency and accountability in AI algorithms. Regarding patient consent for data collection, 74.6% preferred broad consent, while 25.9% favored explicit consent for each specific use case. The research emphasized the importance of good management of patient records, including storage, policies, access, and security. Paper/file methods were predominantly used for data storage (82.2%), with varying levels of confidence in the security measures. The majority of respondents recognized the need for industry collaboration and standardization to safeguard healthcare data collected using AI. The key informant interview results showed that health workers in FMC possess a general understanding of AI technologies, but the use of AI in collecting health data is not widespread; health workers show a positive attitude towards using AI for data collection, acknowledging its potential to enhance healthcare services; ethical concerns related to data privacy, security, and potential misdiagnosis arise with the use of AI in healthcare; management of patient records relies on traditional physical documentation methods, indicating a lack of digital solutions; and there are no specific regulations or legal frameworks dedicated to AI in healthcare, but existing regulations address privacy and ethical issues. To mitigate ethical dilemmas, suggestions include staff training, upholding ethical principles, and incorporating ethical considerations in the development and governance of AI systems in healthcare.
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