Aggregating personal health messages for scalable comparative effectiveness research

Jason H.D. Cho, Vera Q.Z. Liao, Yunliang Jiang, Bruce R. Schatz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publication2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013
Pages907-916
Number of pages10
DOIs
StatePublished - Nov 28 2013
Event2013 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013 - Wshington, DC, United States
Duration: Sep 22 2013Sep 25 2013

Publication series

Name2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013

Other

Other2013 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013
CountryUnited States
CityWshington, DC
Period9/22/139/25/13

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Keywords

  • Design
  • Experimentation
  • Human factors

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering
  • Health Informatics

Cite this

Cho, J. H. D., Liao, V. Q. Z., Jiang, Y., & Schatz, B. R. (2013). Aggregating personal health messages for scalable comparative effectiveness research. In 2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013 (pp. 907-916). (2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013). https://doi.org/10.1145/2506583.2512363