November 28, 2018
Clinical trials and research play a pivotal role in highlighting the most suitable therapeutic strategies for the prevention and cure of a vast array of the novel or previously untreatable diseases. Clinical trials and research involve the collection of samples and associated patient data to test the safety and effectiveness of a novel drug or treatment to minimize detrimental effects, ensuring a more successful outcome. One of the biggest challenges that modern-day clinical researchers face is the breach of patient data security. Every year there are millions of personal health information breaches across the world.
The breach of patients' clinical data can lead to serious criminal frauds such as fake IDs and forged documents. Leaked medical information can be used illegally to acquire medical insurances and prescription drugs. In order to combat these breaches, strict regulations, privacy laws and directive guidelines are laid down by the government for clinical research laboratories. Some of these regulations, such as US Health Information Portability and Accountability Act (HIPAA), require the data holders to undergo de-identification of the patient data before disclosing it to a third-party researcher.
How does De-identification work?
De-identification of a patient data refers to the obscuring of any personally identifiable health information that may lead to the disclosure of the identity of an individual patient. The main goal behind the de-identification of patient data is to maintain the anonymity of the patient and to prevent or restrict the correlation of an individual patient to the available information. The next step in this process is data-anonymization that leads to severing all links and ties between a de-identified data and the progenitor data from which it originated. The responsibility of data de-identification and anonymization lies with the data holders who share it with third-party researchers for clinical trials or clinical research.
There are multiple methods to achieve data de-identification and anonymization, all of which are based on minimizing the association of a set of data with a patient or a group of patients. Some of the common methods include masking of characters wherein some characters in a word are masked, randomization wherein identifiers are replaced with random obsolete values, data shuffling wherein information is shuffled between records to protect identity, using pseudonyms and aliases to maintain anonymity, blurring to reduce data precision, etc. All these methods aim at removing, replacing or encoding important elements of the data that could possibly disclose Protected Health Information (PHI).
Data de-identification and anonymization emphasizes on safeguarding the privacy of patients. It is important to understand that the effect of a patient data breach goes deeper than an economic crisis and can divulge sensitive information that could potentially lead to social boycott and stigmatization of individual patients. Maintaining a patient's anonymity not only protects their right to privacy but also helps curb data breach and identity theft.
The bottom line is that clinical research is carried out to study the patient safety and should by no means challenge it by leading to a breach of millions of patient records. In a digitized world, it is of utmost importance to encrypt data which is being transferred and referred to as well as to anonymize this data so as to protect the identity of the patients participating in the clinical trials.