Healthcare privacy is a central ethical concern when using big data in healthcare. This becomes more pressing with vast amounts of personal information widely accessible electronically. The foremost requirement should be with protecting the name and personal details of the patient.
Privacy and consent
The requirements of a standard business data ethics framework need to be adapted for a public health context (as opposed to a commercial context). The privacy of data is a significant concern, and one that increases in the context of big data. For electronic health records, as an example, there are strict laws governing what can and cannot be done in most countries. As the use of big data expands, the conditions for responsible data collection and processing at a global scale must be clear.
This means the use of digitally available data and algorithms for prediction and surveillance, especially where the identification of people is possible, needs to be processed in a responsible manner, in compliance with data-protection regulations and Digital Transformation and Regulatory Considerations with due respect for privacy and confidentiality. Not only will this place a pharmaceutical or healthcare organization at odds with national or supranational legislation (as the chapter in this book on data privacy clearly outlines) it will prove counterproductive in terms of future data acquisition attempts in that failing to handle data responsibly will undermine public trust.
Methodological robustness
Methodology is evolving and requires constant adaptation to avoid false identification of outbreaks that could cause harm.
Legitimacy
As an example, digital disease detection needs codes of best practice to meet ethical requirements as well as clear communication to the public to prevent hype.
Data protection is also a problem associated with big data, but according. This can be partly addressed where data is restricted to large groups and does not go down to “individual level”. This makes it possible to compare large groups by minimizing any data protection problems.
In particular, pharmaceutical companies and healthcare organizations need to have in place an ethics policy. Such a policy should be agreed and rolled out prior to undertaking any big data analytics that involve the use if patient data. As an example, this means having data rendered pseudonymous before analysis begins.
