By Swanand Prabhutendolkar, Senior Vice President, CitiusTech
The healthcare landscape today is lightyears ahead of what it used to be a decade, or even five years ago. As the importance of user data continues to skyrocket, the concept of data democratisation has gained significant traction. The process aims to make health data more accessible and understandable to many users, regardless of their technical expertise.
This concept is gaining traction as it promises to transform healthcare delivery by empowering patients, clinicians, and researchers with the information they need to make informed decisions.
Need for data democratisation in healthcare
Data in healthcare is unstructured and fragmented. A lack of standardization in the storage of user information makes it difficult for information to travel through various verticals of the sector. This data needs to be distributed at scale, with many downstream apps coming into the picture demanding access. With many patients demanding self-service, ensuring easy access to the data has become a critical endeavour. All of this makes it difficult to maintain the sanctity of data while also ensuring appropriate de-identification measures are in place.
That’s where data democratisation in healthcare comes in – it is a pivotal movement aimed at making health data widely accessible. It seeks to resolve issues of fragmented and biased data sources, thereby enabling deeper analytics and improving clinical data quality. Data democratisation enhances transparency and accountability among healthcare stakeholders, challenges the traditional paternalistic model of medicine by empowering patients, and addresses data invisibility to ensure all patient populations are represented, reducing disparities in data access.
Challenges of data democratisation in healthcare
The path to data democratisation is fraught with obstacles.
● Unstructured data: The healthcare industry needs help with the unstructured nature of the data. Diverse systems, each with its unique format and standards, hinder seamless information exchange.
● Privacy: Another major challenge is ensuring data privacy while maintaining high-quality information. Technology innovators and non-health organisations seeking access to healthcare data face barriers, creating a dilemma between fostering innovation and safeguarding sensitive information. Striking the right balance is crucial for sustainable progress.
● Patient consent: Individuals today are more careful about sharing their data than ever before. A lack of clarity in data ownership, adds layers of complexity to the democratization process for both technology innovators and non-health organisations.
The right path forward
To navigate these challenges effectively, implementing strategic measures is paramount.
● Establish Strong Governance and Infrastructure: Establish strong governance for data and process management, which includes creating a culture that values data sharing and collaboration. This involves education, training, and providing the necessary tools to all stakeholders, irrespective of their domain expertise, as well as patients.
● Address privacy and security concerns: Develop standards for data sharing that comply with regulations like HIPAA and ensure robust security measures are in place to protect patient data from unauthorized access. It’s also important to foster a culture of trust among stakeholders by being transparent about how data is used and protected. Ensuring compliance with data protection laws and ethical guidelines is paramount.
● Empower patients with access to their data: Patient empowerment is critical to data democratisation. Strategies to achieve this include providing patients secure access to their health data and offering tools and resources to help them understand and use this information effectively. This empowers patients to take an active role in managing their health and making informed decisions about their care.
● Foster collaboration and interoperability: Collaboration among different stakeholders
in the healthcare ecosystem is essential for successful data democratisation. This involves creating an interoperable data market that facilitates seamless data exchange and integration across various healthcare platforms and systems. Encouraging collaboration between payers, providers, and patients can also help bridge gaps and improve the overall healthcare experience.
● Continuous monitoring and improvement: Finally, it’s important to continuously monitor the progress of data democratisation initiatives and make improvements based on feedback and evolving needs. This includes expanding the focus of data collection and reporting to include analytics and interpretation, as well as addressing any emerging challenges or barriers to data accessibility.
Future of data democratisation in healthcare
As we look into the future of data democratisation in healthcare, the ongoing debate between data mesh and data virtualisation signifies a crucial crossroads. The emergence of data mesh, with its emphasis on decentralised data architecture, and data virtualisation, streamlining data access through abstract layers, underscores the industry’s quest for the most effective approach. Both paradigms offer unique advantages, and the evolving landscape will witness a convergence that leverages the strengths of each.
Alternatively, ML and AI stand as potent allies in this data-driven evolution, accelerating data accessibility, and potentially revolutionising diagnostics, treatment strategies, and patient care. Through predictive analytics and personalised medicine, AI is poised to be a guiding force in the quest for better health outcomes.
The future of healthcare data democratisation envisions an ecosystem where data is not merely a commodity but a dynamic force propelling advancements in research, clinical practices, and patient-centric care. It is a future where data democratisation is not just a concept but the heartbeat of a healthier, more connected world.