As healthcare organisations continue to digitise their operations, the need to protect sensitive patient data becomes more pressing. The two common methods for data protection are data masking and data de-identification. While both techniques aim to protect sensitive data, they differ in their approach and effectiveness. In this blog, we will explore the differences between data masking and data de-identification and their relevance in healthcare.<\/p>\n\n\n\n
What is Data masking? The purpose of data masking is to suppress i.e. masking most of the directly identifying attributes. Data masking is commonly used by organisations such as finances to reduce the risk of data breaches. <\/p>\n\n\n\n However, data masking has limitations when it comes to the protection of sensitive healthcare data, as it does not provide complete anonymity. This is why data-processed masking techniques often require strict access control and data sharing may not be granted without consent.<\/p>\n\n\n\n What is Data De-identification? De-identified data can be used for research, analysis, and other purposes without the risk of exposing patient information. The purpose of de-identification is to ensure that data is not re-identifiable, even when combined with other information.<\/p>\n\n\n\n Masking and de-identification in healthcare<\/strong><\/p>\n\n\n\n While both techniques have their place in healthcare, understanding the difference between the two is crucial for choosing the right approach in any given situation. Data de-identification might be the preferred approach when:<\/strong><\/p>\n\n\n\n So what\u2019s better?<\/strong> If you\u2019re looking for a high level of anonymity and protection from re-identification, data de-identification is superior as it removes all direct and indirect identifiers from sensitive data. Data masking can be used to mask directly identifying information about individuals but it does not provide complete anonymity as the individual can be identified with enough effort and resources. <\/p>\n\n\n\n While both masking and de-identification have their place, it’s useful to know when to use each approach for safeguarding data privacy, all while maintaining data usefulness. <\/p>\n\n\n\n Orion Health’s Orchestral De-identify <\/strong><\/p>\n\n\n\n Orion Health’s De-identify can help you extract insights while maintaining the security and privacy of your patient data. It is specifically designed for the healthcare industry, with a focus on patient privacy and compliance with regulatory requirements. <\/p>\n\n\n\n Why pick Orion Health’s De-identify?<\/strong><\/p>\n\n\n\n Interested in finding out more about how Orion Health’s De-identify can help you protect patient privacy, ensure compliance and save time and resources? <\/em><\/strong><\/p>\n\n\n\n
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Data masking is a technique that involves obscuring sensitive data, sometimes replacing it with fictitious data to protect someone’s identity. For instance, replacing a patient\u2019s name with a pseudonym or replacing their identifiers such as medical record number or Social Security Number with hashed or other random numbers. <\/p>\n\n\n\n
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Data de-identification on the other hand involves not only removing all identifiable information but also transforming other indirectly identifiable information such as postal code, ethnicity or rare diseases to protect minor grouped individuals\u2019 privacy. Once all identifiers are removed, the data is considered de-identified and can be used for research, analysis, and other purposes without the need for patient consent.<\/p>\n\n\n\n
Let\u2019s look at a few examples:
Data masking might be the preferred approach when:<\/strong><\/p>\n\n\n\n\n
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