3 Ways to Harness AI in Healthcare Market Research: A New Era of Insights

3)     Patient Journey Mapping – How and When Should You Target?

Mapping the patient journey is vital for understanding how patients interact with and experience healthcare services and determining when to engage them effectively.

Traditional methods of patient journey mapping involve analyzing claims data, which present only a linear clinical journey, or conducting qualitative primary market research which captures more of the emotional journey.

However, these methods can be linear and fail to capture the complexity of modern patient behaviors. Incorporating AI into this analysis offers a dynamic approach, analyzing real-time data from various touchpoints, including insight on health-related search queries (to reveal patient concerns, symptoms most often researched, interest in specific treatments), website visits, social listening, and healthcare service usage. AI technology can aggregate insights on a large variety of patient experiences from these resources, and enable you to more accurately modify a patient journey map for each unique patient segment. This is especially helpful for gathering data for rare disease patients, or for difficult-to-recruit patient populations as it allows you to gather insights from a much large sample than what is achievable through traditional market research methods

AI-enhanced patient journey mapping can highlight key moments when patients are most receptive to engagement, for example, it can identify patterns indicating when patients are likely to seek information about new treatments or schedule appointments. It can also identify critical external factors that can lead to vastly different experiences and health outcomes for different patient segments. By understanding these nuances and touchpoints, healthcare companies can ensure they reach patients at the most critical times, and develop added services for their patient support programs, to better support and enhance the overall patient experience.

Augmenting Traditional Research Methods

While AI offers significant advantages, it is not meant to replace traditional market research methods but to augment them. Traditional methods provide foundational knowledge and context, while AI adds depth and precision. The integration of AI with traditional research creates a more robust framework for decision-making.

While leveraging AI has many benefits, it is also important to protect against risk by using Enterprise AI solutions with enhanced security and privacy measures. Such solutions are crucial when handling confidential information and can be configured to comply with specific privacy regulations (e.g. GDPR, HIPAA). Models on enterprise platforms can also be trained on specialized data, allowing the AI to better understand and generate industry-specific or company-specific language, thereby enhancing its relevance and accuracy compared to publicly available solutions.

By leveraging AI, we can uncover hidden patterns and correlations, providing insights that complement the quantitative and qualitative data gathered through traditional research. This synergy between AI and traditional methods leads to a more comprehensive understanding of the market. As the healthcare landscape continues to evolve, the use of AI in market research will be a key driver of innovation and success.