Privacy-enhancing technologies are driving innovation in the public and healthcare sectors globally. From national statistics offices that use the tools to collect better data to pharmaceutical companies, these technologies are driving the innovation in data analytics according to experts. With various other technology innovations getting implemented to perform operations in the healthcare sector, data security challenges are also increasing. As healthcare data has become more and more accessible with digitally interconnected systems, the need to ensure safety and security of that data has become a top priority as well. To balance innovations and data privacy, the new Indian government has recently put into effect the Digital Personal Data Protection Act, 2023.

“Law to protect data privacy is important and hence, in articulating DPDPA, the spirit of Organization for Economic Co-operation and Development (OECD) guidance is also followed where it outlines that data privacy should be recognized as the global minimum standard for privacy and data protection”, mentioned Dr. kembai Srinivasa Rao, Adjunct Professor, Institute of Insurance and Risk Management to the media.

Maintaining data privacy becomes imperative amidst widespread technology integration in the healthcare segment. There has also been emergence of health-tech solution providers who specialize on balancing innovation with data privacy In order to achieve the optimum level of data governance, here are some of the methods that need to be followed by organizations at large.

Compliance with Regulations

Health Insurance Portability and Accountability Act (HIPAA) resembles the regulatory standards that are set in the US regarding protection of all kinds of patient information. Mandates have been set to ensure data integrity and confidentiality. It also allows for the availability of electronic protected health information (ePHI) at all times. General Data Protection Regulation (GDPR) is a similar set of regulatory standards that are set in the European Union (EU) for the governance and protection of public data that includes healthcare information as well.

It is primary for organizations to keep complete knowledge of the regulatory standards of the country they are operational in. Only by having complete knowledge on the subject will they be able to properly implement it in their systems and ensure that data privacy is not harmed. 

Ensuring Data Encryption and Security

Encryption of data enables healthcare technology providers in safe storage of data and seamless interoperability as well. Be it static data or be it in transit, encryption ensures that there are no data breaches at all. In case any unauthorized person enters the system, they will not be able to harm the data or take it without the right keys.

In this regard, Healthcare data management systems and applications make use of various secured protocols for communication called as the Transport Layer Security (TLS) and Secure Sockets Layer (SSL) through which all kinds of transmissions are done over large scale data networks.

Maintaining Anonymity and De-identification

Making patient data anonymous eliminates the risk of data theft by removing information related to the personal details of the patient. This helps systems in secure storage of sensitive health data yet does not allow for re-identification of the patient. De-identification of data also prevents masking of data through indirect identification factors like zip codes and social security numbers. 

De-identifies data sets are subject to stricter standards and regulatory compliances in order to avoid the minimum risks for re-identification. Sensitive healthcare data is prone to cyber-attacks and data theft which is why maintaining anonymity in data always helps health-tech systems in structuring data and mitigates risks at the same time.

Data Minimization

Input of a lot of data is also a problem in maintaining and structuring data. There is a lot of data that goes unused like the personal details of the patient. Data minimization refers to the practice of collecting only the required amount of data from the patient and creating health records. The broader idea behind this is to provide complete data privacy to patients and ensuring data protection.

Data minimization can be called as the cornerstone in data protection. To give an example, there are specific standards in the GDPR that encourages the very practice of exercising data protection principles and prohibits the usage and collection of huge amounts of redundant data that are difficult to organize and prioritize.

Regular Audits and Assessments

It is compulsory that health-tech systems undergo audits at regular intervals to ensure that all the electronic health records (ECRs) are secured and protected. There are also patient information systems in place with a different kind of data infrastructure and framework. These are different from the data sets that are collected in the ERP systems of healthcare institutions. To summarize, each of these systems required individual audits for error detection and risk mitigation.

Regular audits and assessment of systems in the healthcare industry is important because of the high level of sensitivity associated with the data. Various technology partners have emerged over the years that provide the required technology support in implementing and maintaining health-tech systems and avoid data breaches.

With the technology environment changing rapidly, it is hard to say whether the current systems will never be prone to any data threats in the future. Various advanced IT innovations have emerged over the years that have tried to provide the optimum level of data security and many innovations are under R&D and to be introduced to the industry in the years to come.