Prediction summary

The U.S. population is becoming older and more medically complex. According to the CDC, 6 in 10 U.S .adults have a chronic disease. Clinicians will segment their patient population into subgroups by factors like treatment history, social determinants of health, and genetic makeup—and they'll want evidence specific to those groups.

In addition, personalized and precision medicine will continue to become more common, thus increasing the need for nuanced evidence. Precision diagnostics and treatment require highly specific data, so clinicians will increasingly leverage pharmacogenomic and biomarker data to inform treatment selection. Clinical communities will progressively turn to evidence and information that helps them assess how a specific patient may benefit from a specific treatment.

Implications for life sciences

In the future, clinicians will demand more nuanced and specific evidence to support decision-making. They will expect their life sciences partners to generate evidence, via clinical trials and real-world evidence studies, that account for a broader range of patient subpopulations and complexities.

Life sciences leaders must understand how customers will rethink what they mean by “patient population” and how that is evolving, which will have implications on customer engagement strategies. Key accounts, market access, medical affairs, and other customer-facing functions may need to reenvision customer engagement, market engagement, and activation strategies to account for a more complex and diverse range of patient “populations” that clinicians serve. MSLs, sales reps, and other field staff may need additional upskilling to better diagnose and assess local health care ecosystem and patient population dynamics, allowing them to provide more tailored insight to customers.

Questions for life sciences leaders to consider

• How are we leveraging technology to grant clinicians access to this more-tailored information both inside and outside of the care setting?
• How should our data collection strategy adapt for market dynamics like site-of-care shifts to gather the data necessary to provide localized insights?
• How will we educate stakeholders across the ecosystem on how to interpret and apply novel, nuanced information?
• How can we better equip provider organizations with tools and resources to integrate localized data into clinical decision-making?
• Who are potential cross-industry collaborators for my organization to partner with to develop new customer engagement, market engagement, and activation strategies?

Prediction summary

Traditionally, clinicians follow treatment algorithms that take a binary approach to diagnosis and treatment based on whether patients reach broadly accepted threshold of disease.

But today, advances in technology and delivery models are generating a wealth of patient data that can lead to a more dynamic approach to diagnosis and treatment decision-making. Data from wearable devices, remote patient monitoring, and innovations in diagnostics provide real-time and longitudinal insight that allows clinicians to monitor patient progress and disease progression in real time. These increases in available data, and the decisions that can be made using this data, will accelerate in the next 10 years.

The next 10 years will see a significant growth in health technology and data integration. As a result, clinical diagnosis and decision-making will evolve to a more dynamic process that looks holistically at the patient.

Implications for life sciences

As diagnosis and treatment become more dynamic and less binary, clinicians will need help understanding which patients are best suited for a therapy and at what point in their journey. Life sciences leaders can leverage their expertise on specific treatments and therapeutic areas (TAs) to help clinicians with this increased complexity. With potentially more opportunities for intervention, clinicians will have more questions about products, TAs, and patients. Life sciences leaders must prepare their teams to answer an influx of clinical questions and provide more ongoing, consistent support.

Life sciences leaders can leverage the increased use of RPM and real-time data collection to share evidence with clinicians that helps assess when and how to treat patients. And life sciences can step into the critical role of helping clinicians use patient data effectively. Many provider organizations already sit on a ton of patient data (and that amount will grow significantly), but they lack the technological capability, capacity, or expertise to generate actionable insights from the data. Provider organizations and clinicians may be open to opportunities for collaborative partnerships for evidence generation with their life sciences partners to address their specific market and population concerns.

Questions for life sciences leaders to consider

• How would new data types and sources change the patient journey for our products? How do we support both the early adopters and laggards?
• How should clinical trial design evolve in anticipation of clinicians taking a more dynamic approach to decision-making?
• How can we partner with digital health and tech companies driving this change to communicate novel data to clinicians?
• How can we help clinical societies integrate new data into guidelines?
• Who must we engage to address the potential inequities surrounding increased data collection and utilization?

Prediction summary

Technological advances throughout history have changed how clinicians learn, absorb, and apply information to patient care. And now those advances are coming at a pace never before seen. Today's medical breakthroughs can be disseminated almost as quickly as they are generated. Gone are the days when a clinician would have to be exposed to new medical technology during their education or practice to employ it. Now, clinicians are in constant communication with the greater medical community through journals, online clinician communities, social media, etc. Unfortunately, this is leading to information overload, as clinicians try to stay on top of the torrent of medical knowledge and innovation to provide the best care possible.

Clinicians can no longer rely on memory alone to keep track of constantly evolving guidance and treatment options. The future of clinical decision-making will be enabled by technology. Routine, evidence-backed decisions will be automated. This will free up clinician time, allowing highly trained practitioners to leverage their expertise and experience on more complex patient decisions and in spaces where evidence is not yet clear.

Implications for life sciences

The increased use of digital tools and technology in clinical decision-making will create new opportunities and challenges for life sciences leaders. Digital tools will provide a new channel for life sciences to reach their customers and share evidence on a large scale, going beyond traditional channels (e.g., journals, conferences). Life sciences leaders will also have more opportunities to embed their evidence at the point of care, which may accelerate the uptake of new innovations in treatment and diagnostics. Life sciences leaders may be able to leverage data from such platforms to understand what type of evidence and insight resonates with clinicians.

To ensure evidence and insight is embedded in tech solutions, life sciences leaders will need to engage with digital health companies and technology solutions providers. Such engagement will require heightened collaboration across medical affairs, marketing, and digital strategy colleagues to ensure the right information is placed in the right channels.

Additionally, with an influx of tools and technologies entering medical education and clinical decision support, life sciences leaders will need to evolve their medical education programs to meet clinician needs. This will involve engaging and educating customers in a dynamic, personalized way, going a step beyond traditional presentations and continuing medical education (CME) activities.

Life sciences leaders need to be careful about maintaining insight into clinician needs. As evidence is increasingly integrated into digital tools and shared outside of one-on-one interactions, life sciences companies may lose visibility into the questions, insights, or reactions clinicians have.

Questions for life sciences leaders to consider

• What will it take for this trend to translate to quicker adoption of new evidence?
• What parts of the clinical decision-making process can be automated without major change management to deliver high value to clinicians?
• How often does my organization reassess policies and procedures for data-sharing to keep pace with device proliferation?
• How does my organization demonstrate the value-add of new tech solutions to clinical leadership?

Prediction summary

The constant influx of medical information, coupled with physician burnout and limited capacity, is causing clinicians to have less and less time to stay up to date on the latest medical evidence and apply that evidence to patient care. As a result, clinicians will demand new formats and channels of medical evidence to help them quickly digest, interpret, and translate complex information into real-time, individualized decisions. Clinicians will increasingly turn to peers in online clinician communities to understand evolving medical consensus and receive patient-specific guidance on treatment decisions. These communities will be an important part of decision-making alongside point-of-care clinical decision support (CDS) tools.

Implications for life sciences

As clinicians increasingly value new and different evidence, life sciences leaders may need to rethink how they share evidence. They must generate evidence or share information that helps clinicians become better at their jobs, and evidence must have a clear, “so what” and tangible impact. This may require placing an increased focus on innovative evidence types such as visual abstracts, image-based information, plain language summaries, and more.

Life sciences organizations must view online clinician communities as both a channel in their omnichannel communication and engagement strategies as well as a source for insights and evidence. This will require organizations to:

1. Identify prominent channels in which conversations exist for their products

2. Create a strategy to evolve from social listening to integrating insights from these communities

3. Assess how insights from digital platforms can augment product lifecycle strategy

4. Collaborate across functions to leverage these communities to their potential

Questions for life sciences leaders to consider

• How do we diversify the channels and voices we engage with to meet the increasingly digital nature of medical consensus and evidence circulation?
• How do we ensure a cross-functional approach to channels and content types across medical and commercial?
• What partnerships do we need to meet clinician demand for more digestible, practical content?
• What is our strategy to engage new influence brokers such as digital opinion leaders?