Clinical research (see FAQs, below) is constantly evolving in pursuit of new drugs, therapies, devices, and diagnostic methods. Digital technologies, artificial intelligence, and connected data play an increasing role in accelerating better outcomes for patients and driving research inclusivity. The ability to integrate research data, as well as genomic data, with health records presents exciting opportunities for people working in this field. For genomics in particular, this aspect is, as yet, underutilized in the clinical arena, but is nonetheless underway.

The following two trends (Nos 5 and 6 in our series of articles exploring the healthcare trends for 2026) discuss these topics in more detail.

Trend 5: From separate studies to embedded protocols: A new era for clinical research 

The clinical research landscape is undergoing a paradigm shift that will drive greater operational efficiency. It is moving from siloed, standalone studies to embedded protocols directly integrated into enterprise Electronic Medical Record (EMR) platforms.  

Historically, clinical trials operated parallel to clinical care, creating redundant documentation and significant clinician burden. However, we have started to see some benefit of leveraging centralized and comprehensive patient data within EMRs to build research cohorts and design protocols that align seamlessly with care delivery1. 

Harmonizing research and trial design with clinical workflow can help streamline regulatory compliance and ensure data quality without disrupting daily operations. This “embedded” approach has started to represent a new standard where research is digital, patient-centric, and an intrinsic part of the therapeutic process rather than an administrative add-on2 .

How will integration with EMR platforms impact economics, research recruitment and inclusivity? 

Beyond operational efficiency, the integration of real-time patient eligibility screening addresses two critical challenges: speed to trial and inclusivity.

Automated screening tools within the EMR allow for the identification of eligible patients at the point of care. This significantly accelerates recruitment timelines and ensures broader inclusivity. How? By systematically evaluating all patients rather than relying on provider memory3 or risking selection bias in the randomization of the research treatments. 

Also, by broadening inclusivity, the data can be applied directly to the entire population. This means that the research generates a higher quality of data, and the study results avoid having to be extrapolated to be used for general treatment guidelines.

Another benefit of this model is that it has the potential to economically transform clinical research into a financial asset for health systems. This helps to offset broader operational costs – see FAQs, below, for examples.

How will precision medicine speed up clinical decisions and how do global regulations differ?

The rise of precision medicine (see FAQs, below) is the technological linchpin of this new era. It will be driven by advanced genetics modules in major EMR platforms like Epic (Genomics Module) and Meditech (Expanse Genomics).

These modules allow clinicians to order genetic tests and receive discrete results directly within the EMR. In turn, this facilitates personalized care and immediate matching to biomarker-driven trials6 .

While this technology advances rapidly, regulatory frameworks regarding consent remain a hurdle. This is especially so in the United States where fragmented data ownership and strict opt-in requirements complicate recruitment.

In contrast, regions like the UK and the UAE (specifically Dubai) are moving faster toward centralized, government-led genomic initiatives that streamline consent and data access7.  

Despite these challenges, the trajectory is clear: the convergence of clinical care and research via EMR integration is delivering a future where every patient interaction is a potential opportunity for medical advancement. 

What questions should leaders ask about the integration of clinical research with EMRs? 

  • How do we scale and operationalize the embedding of clinical research into the EMR in a way that does not compromise clinical workflow or increase clinician burden? 
  • What capabilities and governance do we need to reliably identify, include, and manage patients in EMR‑embedded randomized controlled trials (RCTs) at the point of care? 
  • What other opportunities do we have in the encounter, point of care to better engage our patients?   
  • How can we position clinical research as a strategic financial asset to strengthen organizational sustainability? 
  • Are we ready to implement and scale precision medicine workflows, including genomic data integration, across our EMR environment? 
  • How will we navigate differing consent, privacy, and regulatory frameworks as data‑driven and genomic research accelerates?  

Trend 6 : GENOMICS as the next frontier in medicine: Improving healthcare with genomic data 

Genomics (see FAQs, below) will be at the core of the next frontier in medicine. It offers significant potential to drive profound improvements in prevention, diagnosis, and treatment tailored to an individual’s genetic profile. 

Precision medicine (where treatments are informed by genomic information alongside clinical and lifestyle data) is already influencing care in areas such as psychiatry, pain management, oncology and rare & chronic diseases. 

Where is sequencing at scale currently underway?

National and international initiatives have built a foundation of genomic assets that link genetic variation to longitudinal health outcomes at population scale.

  • In the United Kingdom, the UK Biobank has sequenced the whole genomes of approximately 500,000 volunteers, making it one of the largest integrated genomic and clinical datasets in the world and enabling research across a wide range of diseases and health outcomes [8]. 
  • Genomics England’s 100,000 Genomes Project has sequenced tens of thousands of NHS patients with cancer or rare diseases, illustrating how genomic data can inform clinical decisions and research simultaneously  [9] . 
  • Across the United States, the All of Us Research Program has released whole-genome sequencing data for over 245,000 participants, with a goal of exceeding one million [10]. 

Why has the use of genomic datasets stalled? 

Despite these expansive datasets, genomic information is still underutilized when it comes to routine clinical care.

A study of genomic screening in Pennsylvania found that among 24 major biobanks with linked genomic and electronic health record data, only 6 (25%) were returning potentially medically actionable genomic results to participants. Three-quarters of large genomic repositories with clinical links were not using that data to inform individuals about actionable health risks, even when such findings could prompt prevention or early intervention [11]. 

This is consistent with broader global analyses and policy discussions. The Global Alliance for Genomics and Health (GA4GH), an international policy body, has underscored that although millions of people worldwide have undergone genomic testing in a research setting, many potentially clinically actionable findings are not routinely returned or used to improve health outcomes [12]. 

These findings illustrate the chasm between data availability and its translation into preventive health measures or clinical decision support.  Several structural and operational factors contribute to this underutilization: 

  • Disconnects between genomic data analysis pipelines and electronic patient records create technical, semantic and workflow barriers to translating genomic insight into care [13]. 
  • Whilst sequencing technology has advanced significantly from 2003 when the first genome sequenced cost $2.3 billion to less than $1,000 today, the cost per test for Whole Genome Sequencing, in addition to all of the auxiliary costs (labor, storage, data science etc.), is still prohibitive for widespread adoption in routine clinical care  [14].

How is the approach to genomics evolving in 2026? 

We see a trend emerging – connected genomics. 

 This year, health systems will prioritize pilots and service models that explore how genomic data can practically function as part of routine healthcare in two main ways: 

  • Operational utility – DNA sequences will be integrated with electronic patient records to routinely deliver actionable insight. Working with digital partners, health systems will connect their data and provide higher quality, more personalized care to the populations they serve. 
  • Health economics – genomic medicine looks expensive when viewed from the singular lens of healthcare but exceptional value for money when whole system benefit is calculated. To prove the total value of genomic-led care, a broad range of datasets (employment, productivity, benefit claims, unpaid caregiving etc.) will need to be connected. Health systems will collaborate with local authorities and governments to align investment with local and national priorities.  

What questions should leaders ask about genomics?

  • Do we have the right foundation for integrating genomic data with health records? 
  • How do I work securely and safely with other providers and authorities to prove the total patient value of genomic medicine? 
  • How can I ensure that genomic services are equitable with a consistent level of care across locations? 
  • Can we easily capture informed consent for analyzing patient genomic data to improve health outcomes? 
  • Is my organization ready to secure and protect this data?  

Ultimately, in 2026, the digital foundations will be built for genomic services that are equitable, accessible and useful for all. 

This is the third and final article in our series exploring the healthcare trends for 2026. In this series we have seen how healthcare is entering a new phase where individual innovations are converging into true system level transformation.

Our articles argue that:

  • Prevention first models are emerging as the backbone of modern care, enabled by early detection, continuous monitoring, and the ability to manage complexity at scale. As this shift takes hold, expectations around engagement are rising: patients now look for consumer grade experiences, intuitive digital pathways, and communication that reflects their personal context. 
  • The landscape of care delivery is expanding. Virtual care is maturing into fully realized hospital-at-home models, increasing access while relieving pressure on traditional infrastructure.
  • In parallel, genomics is accelerating as CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) technologies meet AI, unlocking unprecedented precision across prevention, diagnosis, and treatment. 
  • Today’s clinical advances are happening against a backdrop of financial pressure, pushing organizations to pursue bold efficiency strategies-from advanced automation to AI-enabled resource optimization.
  • Clinical research is evolving, moving from siloed, static studies to embedded, real-time protocols woven directly into everyday workflows. 

Across every one of these shifts, one principle remains essential: technology only succeeds when change management protects and elevates the human side of care. 

As Google CEO Sundar Pichai once said: the future of AI lies not in replacing people, but in amplifying human ability. Nowhere is this more relevant than in healthcare. AI becomes a catalyst for better care when it enhances the irreplaceable strengths of human judgment, empathy, and trust. 

At Capgemini, we are preparing our clients for this new era as an AI-empowered, end-to-end advisory and transformation partner. By connecting these trends – clinical, operational, financial, and experiential – we help healthcare organizations translate disruption into measurable outcomes: safer and more accessible care, better experiences for patients and clinicians, and sustainable cost structures that support long term system resilience. 

Sources:

[1] The National Institutes of Health (NIH). “Electronic health records to facilitate clinical research.” PubMed Central. Accessed 2024. 

[2] Oracle. “9 Top Benefits of EHR Systems: Enhancing Data Management and Research Efficiency.” Oracle Health. Accessed 2025. 

[3] Morgan Lewis. “Key Considerations for Foreign Clinical Trials When Looking Abroad.” Morgan Lewis Publications. 2025. 

[4] Mass General Brigham. “2024 Financial Results: Research and Academic Revenue Growth.” Mass General Brigham Newsroom. Dec 2024. 

[5] Meditech. “MEDITECH Expanse Genomics and GenomOncology integration drives targeted cancer treatments at Frederick Health.” Meditech News. Feb 2025. 

[6] Valley Children’s Healthcare. “Integrating Precision Genomics into Epic for Better Patient Outcomes.” Valley Children’s Impact Report. 2025. 

[7] Exeltis. “Clinical Trials in Europe vs. the US: Processes and Key Differences.” Exeltis Clinical Insights. 2025. 

[8]         H. Lee, W. Kim, N. Kwon, C. Kim, S. Kim, and J.-Y. An, ‘Lessons from national biobank projects utilizing whole-genome sequencing for population-scale genomics’, Genom. Inform., vol. 23, no. 1, p. 8, Mar. 2025, doi: 10.1186/s44342-025-00040-9. 

[9]         ‘100,000 Genomes Project’, Genomics England. Accessed: Jan. 15, 2026. [Online]. Available: https://www.genomicsengland.co.uk/initiatives/100000-genomes-project 

[10]       H. Lee, W. Kim, N. Kwon, C. Kim, S. Kim, and J.-Y. An, ‘Lessons from national biobank projects utilizing whole-genome sequencing for population-scale genomics’, Genom. Inform., vol. 23, no. 1, p. 8, Mar. 2025, doi: 10.1186/s44342-025-00040-9. 

[11]       J. M. Savatt et al., ‘Genomic Screening at a Single Health System’, JAMA Netw Open, vol. 8, no. 3, p. e250917, Mar. 2025, doi: 10.1001/jamanetworkopen.2025.0917. 

[12]       A. C. F. Lewis, B. M. Knoppers, and R. C. Green, ‘An international policy on returning genomic research results’, Genome Med, vol. 13, p. 115, July 2021, doi: 10.1186/s13073-021-00928-5. 

[13]       A. J. Robertson, A. J. Mallett, Z. Stark, and C. Sullivan, ‘It Is in Our DNA: Bringing Electronic Health Records and Genomic Data Together for Precision Medicine’, JMIR Bioinform Biotechnol, vol. 5, p. e55632, June 2024, doi: 10.2196/55632. 

[14] ‘The Cost of Genomics: Economic Challenges in Genetic Medicine’, Genomic Medicine Network. Accessed: Mar. 20, 2026. [Online]. Available: https://www.genomicmedicinenetwork.com/news/the-cost-of-genomics-economic-challenges-in-genetic-medicine/