Managing Principal Mei Sheng Duh
Howard Birnbaum: Mei, can you describe how these Internet and social media data relate to traditional data ?
Mei Sheng Duh: Social media chats and patient forum postings belong to “numerator-based” data, which contrast with traditional health economics and outcomes research data, such as insurance claims data or electronic medical records data, that are “denominator-based.” To illustrate the challenges with numerator-based data, consider the example of an anti-obesity drug that was withdrawn from the market in 2010 based on safety concerns raised by the FDA. In a study of Internet postings, we found that online patients were younger than their FDA MedWatch counterparts and that online ratings were actually higher for this anti-obesity drug than for many safe drugs. This suggests that Internet data can have a high degree of responder bias and potentially lead to spurious conclusions if the underlying data are not viewed with caution.
Howard Birnbaum: There are different data sources in China for health care research. Eric, what has your experience been in China?
Eric Wu: We have used a variety of data sources to conduct health economics and outcomes research and have published or presented our research findings. For example, multi-center EMR data provide rich information on clinical and economic outcomes, including diagnosis, treatment, lab results, results from other exams, as well as costs. The data can be used to address a wide range of research questions.