Data Ethics in balancing patient benefit and privacy issue
The right to privacy of medical data guarantees the patient that the information concerning him and his health problems remain inaccessible for other individuals. All information resulting from medical interactions is considered private and access to it must be secure. The data on the patient’s health can only be consulted or retrieved through his authorization or at the request of the specialized health administrators. When the patient cannot grant permission for reasons of age or health, the legal representative or caregiver is the one who can provide it.
Why the privacy of the data is important?
The right to privacy of health information is increasingly relevant. The privacy protection of the individual is highlighted in all the legal documents of the liberal democracies and is a defining aspect of civil society. The violation of the confidentiality of medical data can affect the life of any individual, generating practical consequences. In addition, information about the existence of serious diseases (for example, chronic-degenerative, infectious, neoplastic, psychiatric), about the use of drugs or medicines, or about sexual choices, can generate discrimination with possible harmful effects for the patient both in the personal and social life (Househ et al., 2018).
With the augmented development of bioengineering research, it is now possible to rapidly and inexpensively complete the whole genetic sequence of the individual. Virtually, this sequence can provide information on all protein variants encoded in the genome of the individual and influence the emergence of various diseases or syndromes. In this way, the protection of the privacy of patients becomes even more important when we consider genetic or bioengineering research. It is because the data discovered there can affect not only patients but also their families and future generations.
The privacy of health data is currently so significant that obtaining informed consents about the storage of medical data is part of the procedure of emergency management, clinical hospitalizations, and surgeries. It is equally essential for any clinical or research protocol that includes the use of biological materials.
Big data ethics and patient privacy
People in the brave new world of big data will get more healthy longevity, but less privacy. The question of the priority, the ratio of individual rights, and collective benefits remain open. The global concept of personal data was developed at a time when the value of the data became apparent, but the possibilities for its automated processing were still small. The more digitalization, the greater the threat to the personal life of a particular person, targeted advertising for most people causes only rejection (Ehrenstein et al., 2017).
In principle, it would be necessary for the machines to have the capacity to autonomously generate and exchange data among themselves by means of an internet connection. This is what we call today the internet of things. Second, it would be necessary to store, process and analyze large volumes of data with the appropriate algorithms. This could help us make decisions. This is what we call big data. Third, it would be necessary for the machines to be able to perceive what is happening in their environment and carry out actions to maximize their chances of success in reaching their objective, making decisions with the context information, and the algorithms that are supplied to them. This is what we call machine learning.
These three elements are now a reality and it is foreseeable that they will have a great impact in the health field as well as patient benefit. Healthcare administrators can lay special emphasis on prognostic, diagnostic imaging, pathological anatomy, and accuracy in the clinical diagnosis. For technological progress to be possible, it is necessary at this time to advance in big data. Yogarajan et al.(2018) stated health researchers and administrators in collaboration with information technology experts need to construct algorithms that hypothetically will benefit the patients themselves. So, every time we use more algorithms to automate health decisions, it is necessary that their resolutions are not only correct but also fair.
The decisions taken today will have different consequences depending on the ethical values. This is why the need arises for the ethical analysis of the impact of big data in health areas and especially in patient privacy. On the one hand, it is necessary to address the challenges in providing care to patients that may arise in the management of electronic medical record information. Healthcare researchers use big data to generate new knowledge, generate algorithms to help decision-making and their incorporation into automated processes.
In terms of privacy, there is a need to clearly explain to the patient the essence of the intervention in terms of what consequences it may or may not have. The main advantage of the use of big data in healthcare is the rapid access to patient information. However, big data can also pose serious threats to the patient’s privacy and confidentiality. In principle, clinical information should only be available to those interested in the patient’s medical care. Nonetheless, based on Househ et al. (2018), the information may be available to health personnel who do not need it, or to third parties who may use it to inflict physical, emotional or financial harm on the patient. Therefore, to the clinical objectives of a system should be added security features that allow guaranteeing the improvement of care, accessing information in a timely manner, and protecting confidentiality through access restriction.
It is not possible to build a completely secure system; it is only possible to minimize their vulnerability by maximizing access restrictions. The responsibility for maintaining the security of the big data system rests with the designers and their administrators as well as the users: doctors, nurses or other hospital staff. The adequate use of a computer-aided prediction or diagnosis system depends on the fulfilment of its clinical objectives, i.e. the correct interpretation of the data and the recognition of its limits in the decision-making, this action, exercised by the appropriate user (authorized and trained personnel) in conjunction with compliance with high safety standards, maintains the privacy and confidentiality of the patient (Butler et al., 2018).
However, the harmony between system, user and security is not defined at the time of the implementation or use of computers. The flexible and changing nature of the clinical exercise indicates that strict observation of the computational applications must be exercised before its implementation and during its use in clinical practice. This strict observation is the basis of the evaluation. Lastly, the continuity, modification or suspension of a big data system depends on the results of the evaluation. Therefore, the evaluation of the applications of the big data is the fundamental pillar on which lies the demonstration of its errors or its virtues.
Leung et al., (2020) concluded that big data is significantly endowed with a kind of novelty that is productive and empowering yet constraining and overbearing. With the burgeoning power of Big Data techniques and technologies, we can now make more accurate predictions and potentially better decisions in dealing with health epidemics. At the same time, however, one cannot fail to notice the ethical challenges and dilemmas it has created among organizations, experts, and the society at large. More decisive actions can be taken by the various governing bodies to checkmate the utilization of big data analytics in various organizational levels to tackle these ethical challenges.
References
Househ, M., Grainger, R., Petersen, C., Bamidis, P., & Merolli, M. (2018). Balancing Between Privacy and Patient Needs for Health Information in the Age of Participatory Health and Social Media: A Scoping Review. Yearbook of medical informatics.
Butler, J. M., Becker, W. C., & Humphreys, K. (2018). Big data and the opioid crisis: balancing patient privacy with public health. The Journal of Law, Medicine & Ethics, 46(2), 440–453.
Leung, K. T. Y., Antoś Dembicz, & Anne Stevenson. (2020). Exploring Ethical Dilemma in Big Data Analytics: A Literature Review. Technium: Romanian Journal of Applied Sciences and Technology, 2(5), 43–48. Retrieved from https://techniumscience.com/index.php/technium/article/view/891
Yogarajan, V., Mayo, M., & Pfahringer, B. (2018). Privacy protection for health information research in New Zealand district health boards. The New Zealand medical journal, 131(1485), 19–26.
Ehrenstein, V., Nielsen, H., Pedersen, A. B., Johnsen, S. P., & Pedersen, L. (2017). Clinical epidemiology in the era of big data: new opportunities, familiar challenges. Clinical epidemiology, 9, 245.
