Olivier Humblet, PhD
Using technology and data science to improve population health and prevent disease
My current work focuses on the ways in which technology and data science can be used to improve population health and prevent disease. This field is evolving rapidly due to the development of new technologies for collecting and utilizing health data. New sensors allow monitoring of health outcomes and health behaviors. Electronic health records collect information about health outcomes and medical care in a format that increasingly can be shared and used for research. New database technology allows the storage of huge datasets of varied data types, while new analytic tools allow this data to be mined more efficiently than was previously possible. Smartphones enable information to be continuously collected from people, and also delivered back to them in real time. Meanwhile, the need to find more effective ways to maintain and improve health âincluding new technology, as well as other social interventions and policy changesâ is driven by the challenges of a rapidly aging population and rising obesity rates, as well as new health care incentives for both disease prevention and more effective, less expensive treatment.
Evolution while in the Health and Society Scholar program
The Health and Society Scholar program has been a unique opportunity to extend my training across multiple disciplines and research areas. I entered the program with methodological expertise in epidemiology and biostatistics, and substantive interests in asthma and environmental pollution. And while I continued to pursue my previous research while in the program (e.g. Humblet et al, 2013), I also enjoyed the freedom to pursue my new interest in health technology, Big Data, and mHealth. This included attending health technology conferences; reviewing the literature regarding new developments in this area; acquiring new analytic skills; and developing a research collaboration with Asthmapolis, a health technology startup founded by cohort 4 scholar David Van Sickle.
One outcome of this intellectual exploration was a commentary article in the journal Big Data, exploring the potential role that Big Data can play in preventing disease and improving population health. This article was co-authored with fellow Health and Society Scholar Meredith Barrett and several program faculty members (Barrett, Humblet et al, 2013; in press).
A second outcome was the research resulting from collaboration with Asthmapolis. Asthmapolis has developed an asthma sensor that snaps onto metered-dose inhalers and passively captures the time, location and GPS coordinates of inhaler use by communicating with a smartphone. All data are uploaded in real-time to a remote server. In this project I analyzed inhaler data from Louisville, Kentucky, in order to discover correlations between the number of asthma exacerbations on each day and various environmental triggers of asthma including air pollution, meteorology (e.g. temperature, humidity), and pollen counts. This sensor has the potential to improve population health by helping patients identify triggers for their asthma, allowing physicians to monitor patients’ medication compliance and asthma severity, and making feasible the real-time monitoring of asthma exacerbations at the community level.
After completing the Health and Society Scholars program I will join Asthmapolis as VP of Data.
Barrett, MA*; Humblet, O*; Hiatt, RA; Adler, N. Big Data and Disease Prevention: From Quantified Self to Quantified Communities. Big Data [in press; *co-first authors]
Humblet O, Korrick SA, Williams PL, Sergeyev O, Emond C, Birnbaum LS, Burns
JS, Altshul LM, Patterson DG Jr, Turner WE, Lee MM, Revich B, Hauser R. Genetic modification of the association between peripubertal dioxin exposure and pubertal onset in a cohort of Russian boys. Environmental Health Perspectives. 2013 Jan;121(1):111-7.
Olivier Humblet, PhD