In the digital era leveraging integration frameworks to realise big data’s potential will be a game changer for patient analytics

We are in a promising digital age marked by a proliferation of specialised technologies, new platforms and data sets.

These tools are powerful components of patient-centric trials and are redefining the way we execute clinical research to improve outcomes through a variety of use cases – from patient journey analytics to site identification, patient finding, predictive modelling and brand strategy.

The way we integrate and interrogate the disparate sources, and newly available data, is the key to obtaining a complete view of the patient and generating meaningful insights that inform strategies to better reach, engage and support them with improved experiences, education and services.

Here, we outline the potential for holistic data to connect us with patients and the ways sponsors can ensure they realise that potential through agile integration frameworks.

Data plays a pivotal role in the pharmaceutical industry and there has been an explosion of tools and technologies aimed at gathering it.

The number and type of available healthcare data sets are growing at an exponential pace, which has shifted the topography of the landscape.

Now, with mountains of data in disparate sources, including clinical, claims, EMR, Rx, payer, provider, DHT and social determinants of health (SDOH), the primary challenge has shifted from the generation of this vital data to its efficient integration.

Integrating these myriad data sources into a single, validated and responsive data set provides opportunities for deeper insights and optimised analyses that can benefit clinical research stakeholders at all levels.

Linking and layering robust data helps us generate multidimensional patient profiles, identify and understand underserved patient populations and enables a more granular view of their journeys.

This allows us to identify barriers and opportunities to engage and support them at multiple levels, from improved messaging to patients at recruitment through customised support services during trials.

Comprehensive and granular data analysis is also impacting patient-centred trial design at multiple stages, as these insights inform decisions around optimised protocols, the assembly of digital health technologies and other solutions that minimise patient burden.

Data-driven patient-centricity improves diversity, minimises burden, supports engagement and compliance for participation in clinical trials.

Selecting the best-fit and most impactful solutions also benefits sponsors by optimising the allocation of resources and avoids wasting time and expenses on irrelevant solutions.

The wide array of data must be integrated with high fidelity in order to provide relevant and actionable insights that help realise the true value within all this data.

Maintaining this quality for robust data sets requires a holistic integration strategy that matches patient data collected across all key health touchpoints from early phase through commercialisation to better understand the interrelationships within the patient journey.

This process is complicated by the many different types of data, varying consent, data latency and levels of completeness as it is integrated into a single source for analysis.

It is important that sponsors have an agile integration framework that can accommodate these challenges and clearly and accurately link patients across data sets in order to maximise the opportunities for insight generation.

When linked, data from sources like claims, patient services, wearables, digital therapeutics, diagnostics, websites, audience activations and SDOH are all important facets that open deeper insights with the broadest potential for application.

Sponsors with significant experience interpreting integrated data sets may maximise agility by performing their own analyses, however those who are taking their first steps down this path are well advised to secure expertise from trusted partners in this space.

As data-driven strategies evolve, sponsors will continue to find innovative ways to leverage data throughout development and beyond.

Currently, integrated data analysis is informing patient-centric designs, enhanced study startup and site identification, predictive modelling and commercialisation among many other uses.

As novel applications continue to emerge and brand strategies shift – sponsors’ data strategies must be flexible enough to support these and any future pivots.

Developing an agile data integration strategy starts with a strong foundation, comprised of three key tiers: a tokenisation engine, patient master, and patient and consumer data assets.

The tokenisation engine is the core of the strategy as it is the mechanism by which we de-identify patient data and turn it into encrypted tokens.

It is important to remember that not all tokens are equal, however, as they are directly dependent on the quality and completeness of the original data.

In addition to quality, compliance and consent are primary considerations for tokenised data and an investment in stringent privacy reviews will ensure compliance and avoid costly mistakes and potential delays.

The patient master is critical for linking patient data from end to end to facilitate more holistic analysis. It is the only way to validate the tokens and is the mechanism through which we can generate a single, consistent patient identifier.

The ability to link data, however, is also dependent upon the quality and completeness of the data sets themselves.

Curating the right data sets is an important aspect of a successful data integration strategy and, by extension, a partner with access to curated patient and consumer data assets will best enable insights that facilitate improved trials, relationships with patients and overall outcomes.

The digital age is here to stay and it is vital that sponsors are ready to capitalise on the data boom and translate the benefits to patients.

An important component in this success is being intentional with data integration strategies and formal frameworks to ensure data is captured and linked across the development continuum to provide seamless insights from molecule to market.

These strategies must be reflexive to allow sponsors to accommodate the constant evolution in the industry as we innovate the ways in which we collect and apply data to optimise clinical trials, build relationships with patients, and enhance the experience and outcomes.

Data integration frameworks that aren’t built to pivot for dynamic use cases will reduce sponsors’ visibility into the patient healthcare journey, healthcare providers, sites of care and payer controls – and ultimately impact their decision-making.

Rick Rosenthal is Vice President, Symphony Health, ICON and Paula Fullman is Vice President, Symphony Health, ICON. Go to iconplc.com/symphony