As we approach
2025
, the trajectory is clear:
Health
care
and
life
sciences
are steadily laying the groundwork for sustained transformation and innovation. There will be no sudden disruption, no major pivot, yet focused efforts to build agile, resilient organisations.
SAS
predicts the coming year will be defined by continued integration of
health
systems, modernisation of technology, and an increasingly active role of patients and consumers in directing their
care
in industries shaped by regulation and public trust.
Health
care
and
life
sciences
experts from global data and
AI
leader
SAS
shared their thoughts on the current and future state of the industries.
Targeted
AI
applications drive expanded
AI
usage.
Health
care
organisations and pharmaceutical companies will explore new ways to implement
AI
-driven insights at every level, from patient
care
personalisation to faster drug development cycles, with a focus on expanded use of
AI
in targeted areas of the ecosystem. As
AI
proves its own value in a variety of ecosystem-specific settings, we expect to see increased governance and directives for the use of
AI
from CIOs, CTOs, regulators and industry leaders in the form of company-specific
AI
playbooks.
Alyssa Farrell, Director, Global
Health
Care
&
Life
Sciences
Industry Marketing,
SAS
Generative
AI
reaches the inner workings of the clinical trial. Due to sophisticated digitisation and standardisation techniques, clinical trial protocols now allow use of
AI
for high-quality information extraction and generation to help facilitate the development of innovative therapies. Applying generative
AI
to clinical trials will lead to inclusion of underserved populations, faster submissions, and overall acceleration of new clinical trial models and approaches.
Mark Lambrecht, Senior Director,
Health
Care
&
Life
Sciences
Advisory,
SAS
Health
care
and pharma converge. Pharma and
health
care
are working more closely than ever, using data and shared insights to drive innovation in patient
care
and treatment development. In
2025
, this convergence is no longer experimental – it will be foundational to how these industries operate. However, data interoperability will remain the primary challenge for these traditionally siloed industries. Ensuring that data flows freely and securely across systems will be a critical focus in the year ahead to move toward tangible convergence. For patients, this means more cohesive
health
experiences where
care
delivery and medical advancements are intertwined.
Gail Stephens, Vice President,
Health
and
Life
Sciences
,
SAS
Technology takes centre stage. Despite extraordinary advances, many parts of the
health
care
technology stack remain fragmented and outdated and the need for a digital overhaul is unavoidable.
Health
care
organisations, from hospitals to research labs, must reimagine their infrastructure, embracing solutions that modernise and integrate the various systems on which they rely. But even with the right tools, financial investment will be paramount. For the industry to benefit from the promise of
AI
, substantial resources must be directed toward infrastructure, prioritising data integrity, security and usability.
Steve Kearney, Global Medical Director,
SAS
Payers tap technology to help strengthen the public
health
framework. After years in a state of public
health
emergency due to COVID-19, we will see payers and public
health
vow to keep communication more open than it has been in the past. Data sharing is key to this effort, and increases in interoperability are enabling payers and public
health
to speak the same language. Advancements in technology, such as
AI
-driven analytics and real-time data exchanges, will further streamline collaboration and decision-making. Expect to see more shared accountability evolve through the standardisation of metrics and shared investments to make healthier populations.
Amanda Barefoot, MHA, Managing Director,
Health
Care
&
Life
Sciences
Solutions,
SAS
Citizens and consumers push to get smart
health
tech. In response to the European
Health
Data Space proposed regulation, hospitals will seek the ability to exchange patient
health
data across borders securely to drive outcomes and new research paradigms. This functionality will open a
health
-tech revolution, resulting in interesting
health
consumer apps reaching the market with a mix of wearable data and patients’ historical and current
health
states. Patients, members, citizens, etc., will start to demand smarter usage of their own healthcare data.
Christian Hardahl, EMEA
Health
Care
Industry Leader,
SAS
Data management remains a priority. Robust data management will once again emerge as a critical priority, driven by the increasing complexity of data, regulatory requirements and the growing recognition of not only the value of data assets but also the value of clean, quality data. Organisations will look to enhance data management practices through cloud-based data and
AI
platforms that seamlessly connect data across the enterprise (e.g., clinical data, real-world data, commercial customer data) and boost productivity through automation in the cleansing, quality, and mastering steps. This will lead to accelerated timelines and processes, while increasing patient-centricity throughout the pharmaceutical
life
cycle.
Brittany Shriver, Head of
Life
Sciences
Industry Consulting,
SAS
Globalisation of public
health
reaches beyond historical barriers of opposition. Government
health
agencies will seek innovation and technological modernisation by examining the progress of those who are successful and deploying projects with universal geographic applicability. Likewise, ingenuity will drive novel uses of analytic technology in government
health
. Convening of public, private and education sectors will generate new ways to detect, model and anticipate diseases that threaten the stability of human
health
.
Meg Schaeffer, National Public
Health
Advisor and Epidemiologist,
SAS
AI
-driven automation transforms clinical work
life
. In clinical work, there will be a significant focus on reimagining processes and automating repetitive tasks using
AI
and natural language processing. This will result in an improved clinical work
life
where time and expertise is valued and clinicians are offered the opportunity to practise at the top of their licence versus spending time on tasks that take them away from the patient.
Heather Hallett, RN,
Health
Care
Executive Advisor,
SAS
Learn more about
SAS
’ analytics and
AI
solutions for
health
care
(
sas
.com/healthcare) and
life
sciences
(
sas
.com/lifesciences).
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