Comparative Effectiveness Research (CER) is defined as the generation and synthesis of evidence that compares the benefits and harms of different prevention and treatment methods. This is becoming an important field in informing health care providers about the best treatment for individual patients. Currently, the two major approaches in conducting CER are observational studies and randomized clinical trials. These approaches, however, often suffer from either scalability or cost issues. In this paper, we propose a third approach of conducting CER by utilizing online personal health messages, e.g., comments on online medical forums. The approach is effective in resolving the scalability and cost issues, enabling rapid de- ployment of system to identify treatments of interests, and developing hypotheses for formal CER studies. Moreover, by utilizing the demographic information of the patients, this approach may provide valuable results on the preferences of different demographic groups. Demographic information is extracted using our high precision automated demographic extraction algorithm. This approach is capable of extracting more than 30% of users' age and gender information. We conducted CER by utilizing personal health messages on breast cancer and heart disease. We were able to generate statiatically valid results, many of which have already been validated by clinical trials. Others could become hypothesis to be tested in future CER research.