Unlocking Patient Insights in HEOR Through Netnography: A Scalable Qualitative Research Method

In health economics and outcomes research (HEOR), understanding the patient experience in their own words is vital. While traditional methods such as interviews, focus groups, and structured surveys remain foundational, they can be time-consuming, resource-intensive, and often constrained by limitations such as sample size, recall bias, or restricted generalizability. Desk research approaches such as literature reviews offer less logistical challenges but lack the depth and nuance that those with lived experiences can provide.

In this context, ”Netnography” is emerging as a powerful and efficient approach for capturing the patient experience in a more naturalistic and scalable manner.

What Is Netnography?

Netnography is a qualitative research method adapted from ethnography, designed to explore the experiences, preferences, and values of individuals through their interactions with online communities. It involves the analysis of user-generated content across digital platforms such as forums, social media, blogs, and online patient communities. This methodology allows researchers to explore how people speak about their health and treatment journeys when they are not being prompted by a researcher offering insight that is often more candid, emotionally rich, and contextually grounded.

Types of Netnographic Approaches

There are two main approaches to netnography:

• Passive (Observational): Unobtrusive analysis of existing conversations in public online spaces, without engaging with participants. This preserves the natural flow of dialogue and is particularly useful in early-stage research.
• Participatory (Interactive): Active engagement with online communities where researchers may post questions or join discussions to explore topics in greater depth.

Applications in HEOR and Preference Research

Our team has extensive expertise in qualitative methodologies, both as standalone research and within mixed-methods frameworks. Qualitative work plays a crucial role in valuation studies such as discrete choice experiments (DCEs) and time trade-off (TTO) assessments. In these contexts, qualitative data provide a foundation for understanding what matters most to patients and how they frame decisions about health trade-offs.

Netnographic research can enhance this process by offering access to authentic, unfiltered patient narratives, which can guide the selection of relevant attributes and language for subsequent quantitative research instruments in a resource-efficient approach.

Benefits of Netnography for Patient-Centric Research

One of the key advantages of netnography is its efficiency. By leveraging existing online discussions, researchers can bypass lengthy recruitment and data collection phases, enabling the rapid generation of insights. This approach is particularly valuable for accessing perspectives from traditionally hard to reach populations, such as those living with rare diseases or socially stigmatized conditions. Because patients often turn to digital platforms to openly discuss frustrations, treatment limitations, and gaps in care with others who have shared experience, netnography is especially effective in identifying unmet needs.

In addition, the continuous nature of online dialogue means that netnographic research can capture evolving views in real time, whether in response to new treatments, or changes in the healthcare landscape. Unlike traditional methods that require waiting for events to conclude before initiating recruitment, netnography allows researchers to observe reactions as experiences unfold.

As netnographic data is organically generated, they often highlight concerns and priorities that structured methods may overlook. In doing so the data provides a natural entry point for early-phase research and can help ensure that follow-on studies, including large-scale DCEs and TTOs, are built on a robust understanding of the patient perspective.

Ethical Considerations in Netnography

Despite its utility and growing usage, there have been many discussions about the ethics of netnography which center on the nature of ‘public’ and ‘private’ spaces online. There is a large body of literature discussing these challenges and while difference in opinions exist, a general consensus is that netnography must be conducted with strong ethical oversight with decisions made on a case-by-case basis. A central concern is that individuals participating in online discussions may not realize that their contributions could be analyzed for research purposes. To address this, researchers must take care to protect the anonymity of individuals whose posts are analyzed, avoid collecting or presenting any identifiable information, and ensure that their research is reviewed and approved by an appropriate ethics body. Data collection must comply with privacy regulations such as the General Data Protection Regulation (GDPR) or local equivalents, and researchers must work within the terms and conditions of the websites or forums from which they are collecting data.

Enhancing Netnography with AI Tools

Alongside this emerging method, there have been progressions in the language processing capabilities of Artificial Intelligence (AI); both in generic platforms and specific qualitative data analysis packages. Used in conjunction with netnography, which captures large volumes of rich qualitative data, AI tools offer the potential to support manual approaches to efficiently process and analyze patient perspectives.  By combining the authenticity of patient-generated content with the analytical power of AI, Putnam can deliver comprehensive and agile understanding of patient experiences, identifying key themes, emotional tone, and emerging patterns of experience across therapeutic areas at both scale and pace.

Conclusion: Real-World Relevance at Scale

Netnography is a valuable addition to our HEOR research capacity. It offers a scalable, cost-effective, and richly descriptive method for bringing the patient voice to the forefront of economic evaluation. By grounding preference studies and valuation models in the language and lived experiences of patients themselves, netnography ensures that health economics remains anchored in real-world relevance.  Interested in applying netnography to your next HEOR study? Get in touch with our expert team.