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AI Implementation in Healthcare: The Conundrum of Data Privacy by the DPDP Act

Abhishek Mishra

The acceptance of AI has surged in recent times, with its potential applications in healthcare being immense. In diagnostics, AI algorithms can analyze vast amounts of diagnostic points, and automated technology to perform biochemical tests with minimal human intervention, ensuring accuracies and faster result generation of medical imaging data, such as X-rays and MRI scans, with greater precision and speed. In predictive analytics, AI uses patient data, medical histories, and environmental factors to forecast patient outcomes, readmission rates, and even disease outbreaks. AI has also had a significant impact on drug discovery, drug adherence, and personalized medicine, thereby improving the efficiency and economics of the pharmaceutical industry. 

However, these advancements in AI rely heavily on large datasets and often contain sensitive personal health information. 

In this respect, compliance with regulations regarding the protection of personal data like the Digital Personal Data Protection (DPDP) Act becomes quite indispensable for ensuring that the processing of patient data is done responsibly. The DPDP Act 2023 is a legislative framework designed to regulate the processing of digital personal data, ensuring a balance between an individual's rights to privacy and the legitimate requirements of entities to process data for lawful purposes. 

Figure 1: The DPDP Act and its effects on Data. Image credit: Designed by author.  

 

How the DPDP Act Affects AI in Healthcare 

The said Act puts a regulatory force on the processing of digital personal data by any entity in India and thus affects how healthcare organizations and AI developers process sensitive information related to patients. Key aspects of the Act and its implications in driving healthcare by AI are discussed below:  

1. Data Fiduciaries and Processors in AI 

Under the DPDP Act, healthcare institutions along with AI companies are likely to fall under the category of Data Fiduciaries when handling patient data. AI algorithms may analyze, store, or process this data for purposes such as diagnosis or treatment. The Act mandates that any processing of personal data must be done with proper consent or must be based on legitimate grounds such as medical treatment. It is the responsibility of the institution to ensure that proper consent is obtained and recorded in compliance with the Act.  

AI-powered systems should be designed in such a way that personal data is processed for a specific purpose in a lawful manner and effectively secured. 

A case Study:

A healthcare company is leveraging AI-powered predictive analytics to improve consultations for healthcare providers by analysing HMIS data and patient health records. This company aims to enhance the accuracy of diagnoses, personalized treatment plans, and overall patient outcomes. As the startup handles sensitive health information, it must ensure full compliance with the Digital Personal Data Protection (DPDP) Act, 2023.

Steps to ensure compliance: The company must implement mechanisms to obtain and record patient consent before using health data for AI analysis, ensuring compliance with the lawful basis of processing data.

 

2. Consent and Data Processing 

Another key principle of the DPDP Act involves explicit consent by the patient prior to the processing of data. Those AI solutions that need patient data for processing should ensure that due consent about the usage of patient data is fully informed. This may involve sharing how AI algorithms will analyze a patient's health data for diagnosis, personalized treatment, or predictions. 

The mechanism of Consent Manager within the DPDP Act makes them capable of managing and reviewing their data consents, hence adding some transparency to it. Regarding AI systems, this would mean designing tools to incorporate consent management into the workflow. 

Steps to ensure compliance: In the above case study, the company should build user-friendly consent management tools that allows patients to review how their data will be used and provide consent for specific AI applications to ensure that consent is fully informed.

 

3. Data Minimisation and Purpose Limitation 

In healthcare, AI systems must be explicitly designed in accordance with the principles of data minimization and purpose limitation according to the DPDP Act, meaning only collecting and processing data is required to serve the purpose intended. This ensures that if data is shared or reused, it is not misused without explicit and concerted consent from the patient. 

For instance, artificial intelligence examining MRI scans for tumor diagnosis should not repurpose the information for any other intended research without re-taking the patients' consent. 

Steps to ensure compliance: Ensure that the AI systems only collect and use patient data relevant to the intended health insights, and refrain from repurposing the data without fresh consent.

 

4. Data Security and Breach Notification 

The AI systems shall ensure that proper data security measures are implemented under the DPDP Act by encrypting the data, implementing multi-factor authentication, and other precautions to keep sensitive health data out of unauthorized access or breach. 

Because healthcare providers have an obligation to inform the appropriate authorities and affected parties at the earliest in case of any data breach, an AI system should be designed to have mechanisms for the detection and reporting of breaches. 

Steps to ensure compliance: The company should set up robust systems for breach detection, with immediate reporting mechanisms in place to notify authorities and affected patients in case of a breach.

 

5. Rights of Data Principals 

The Data Principals, in this case, the patients under the DPDP Act, shall have rights to seek access, correction, or erasure of their personal data. In AI-driven healthcare systems, mechanisms should be provided for the patient to exercise these rights easily. For example, if a patient wants his health data deleted, the AI systems should ensure that the data is immediately deleted from all its related databases. 

Moreover, AI solutions need to be transparent in decision-making. In case any AI system comes up with a clinical recommendation or diagnosis regarding a situation, the patient has all the rights to understand how his or her data was involved in arriving at such a decision. 

Steps to ensure compliance: Ensure that patients can easily request for data deletion or corrections via the platform and implement transparent algorithms that explain how AI-derived recommendations are made.

 

6. Cross-Border Data Transfers 

Artificial intelligence systems in healthcare often need collaboration across borders for data analysis or research work. Under the DPDP Act, transfer of personal data across borders is restricted unless permitted by the Central Government. Any healthcare provider using AI tools hosted outside India or collaborating with a foreign entity would fall under the regulations regarding permissions from the authorities before transferring the data across the border. 

Steps to ensure compliance: Seek necessary permissions from the Central Government before transferring any patient data outside India, ensuring that cross-border collaborations are legally approved. 

By adhering to these steps, the startup will align its AI healthcare services with the regulatory requirements of the DPDP Act, ensuring both patient trust and legal compliance.