What difference does Medical Affairs make? Exploring new ways of measuring impact

In an era where pharmaceutical companies are under increasing pressure to demonstrate the value of their activities, the role of Medical Affairs has never been more critical – or more scrutinized. Yet while the importance of Medical Affairs is widely acknowledged, measuring the tangible impact of its initiatives is a complex challenge.

Working at the intersection of science, medicine, and strategy, Medical Affairs is uniquely positioned to bridge gaps between innovation and patient care. It engages across the entire product lifecycle: shaping clinical trial design, driving real-world evidence generation, informing treatment guidelines, and addressing unmet patient and HCP needs through a scientific evidence-based approach. With this wide-ranging remit comes an increasing level of accountability; more and more, the focus is not what Medical Affairs does, but what difference it makes. Here, we explore some novel approaches to addressing this critical issue.

Why measuring the impact of Medical Affairs is a challenge

The challenge of measuring the impact of Medical Affairs activities stems from the inherent complexity of the function’s mandate. Unlike sales or marketing, which are often evaluated based on direct commercial metrics, Medical Affairs operates in a less easily quantifiable domain: advancing scientific understanding, shaping clinical practice, and improving patient outcomes.

Several factors contribute to this challenge:

• Long-term outcomes: The ultimate goals of Medical Affairs, such as improved patient outcomes or better-informed treatment decisions, often unfold over years. Linking long-term (multi-year) outcomes back to specific activities over shorter-term (typically annual) business planning cycles can be difficult.

• Multi-faceted influence: Medical Affairs initiatives often target a wide range of stakeholders, including HCPs, regulators, and patients. Demonstrating measurable impact across such diverse audiences is inherently complex.

• Attribution challenges: The healthcare ecosystem is shaped by myriad external factors – regulatory changes, competing interventions, and evolving clinical evidence – that complicate the attribution of outcomes to Medical Affairs efforts.

Given these challenges, it is tempting for companies to fall back on process-oriented metrics (e.g., number of medical education sessions conducted, or publications disseminated). These outputs are important, but they don’t answer the critical question: What difference did these activities make?

Learning from other sectors

To overcome these challenges, Medical Affairs can look to frameworks from other industries that have faced similar obstacles in measuring impact. Two such approaches – Theory of Change (ToC) and Contribution Analysis (CA) – have proven effective in fields like international development and public health, where outcomes are long-term, multi-factorial, and difficult to isolate.

Theory of Change

ToC is a planning and evaluation framework that maps the pathway from activities to long-term outcomes. By explicitly defining the causal steps – inputs, activities, outputs, outcomes, and impact – ToC provides a clear structure for understanding how specific interventions are expected to create change. Importantly, it also highlights the assumptions and external factors that may influence the process.

In a Medical Affairs context, ToC might involve:

• Mapping an expected causal chain showing how HCP education sessions lead to increased awareness of clinical best practice, which in turn can influence changes in prescribing behavior, which in turn contributes to improved patient outcomes.

• Identifying the assumptions underpinning these links (e.g., that HCPs will apply the knowledge gained) and the external variables that could influence success (e.g., reimbursement policies).

Contribution Analysis

While ToC focuses on planning, CA is an evaluation tool designed to assess whether, and to what extent, an intervention contributed to observed outcomes. It is particularly suited to complex settings, where multiple factors are at play and definitive causation is difficult to establish.

CA involves systematically gathering and analyzing evidence to confirm whether an intervention plausibly contributed to its intended outcomes. A key feature is grading the evidence to assess its strength, considering factors such as consistency, credibility of causal links, and counterfactual scenarios.

For example, in Medical Affairs, CA could be used to evaluate to what extent an increase in biomarker testing rates among oncologists was driven by educational workshops or by other external influences, such as regulatory changes.

Measuring impact: a path forward

As Medical Affairs teams continue to expand their role in advancing science and improving patient outcomes, the ability to measure and demonstrate impact will be critical to their success. Borrowing proven methodologies from other industries, such as ToC and CA, offers a path forward. These frameworks can help Medical Affairs functions to:

• Design initiatives that are strategically aligned with measurable outcomes.

• Evaluate the effectiveness of their efforts in a structured, credible way.

• Communicate the value they bring to stakeholders with confidence.

By adopting robust, evidence-based approaches to measuring impact, Medical Affairs can further elevate its influence and demonstrate its indispensable role in driving better health outcomes.

Coming Soon: Prime’s White Paper on measuring the impact of Medical Affairs

To help Medical Affairs professionals put these concepts into practice, we will be releasing a White Paper early next year. This in-depth guide will delve into ToC and CA, providing practical examples of how these frameworks can be implemented in a Medical Affairs setting.

Get in touch to be the first to receive a copy of this White Paper, and join us in reimagining how we measure the impact of Medical Affairs.

Author: Mikko Figura Senior Director, Integrated Communications Strategy, Prime