Dr. Wang leads the data analysis team in the Icahn Institute’s Center for Advanced Digital Health, a center of excellence to spearhead the research, development, and clinical application of next generation digital tools to improve healthcare and wellness. Its work directly supports the Icahn Institute’s vision to harness the digital universe of information to better diagnose, treat, and prevent disease.
Benefit from the fast evolving digital health technologies, we are facing a revolution on the type/scope of medical data for defining/characterizing health/disease phenotypes/outcomes. This rises pressing needs for tailored/adaptive new computational/analytical methods for modern epi/clinical studies (trials) based on digital devices/apps. Our team will develop and employ advanced data analysis methods to collect, explore, and extract insights from data collected from such digital health studies. We will assists research/business with casual inferences & observations with finding patterns, relationships in data. We will also build data driven pipelines to translate data into intelligence, solve a variety of business/research problems and enable business/research strategy.
Recently, Dr. Wang and her colleagues published results from a pioneering study of asthma patients in the U.S. conducted entirely via iPhone using the Apple ResearchKit framework and the Asthma Health app developed at Mount Sinai with collaborating organizations. The results demonstrated that this approach was successful for large-scale participant enrollment across the country, secure bi-directional data exchange between study investigators and app users, and collection of other useful information such as geolocation, air quality, and device data. The publication appears in Nature Biotechnology.
The Asthma Mobile Health Study was launched in March 2015, and in the first six months, the app was downloaded by nearly 50,000 iPhone users. The study included regular surveys to understand how asthma patients were affected by and treating their condition over time. A total of 7,593 people completed the electronic informed consent process and enrolled in the study. Eighty-five percent of them completed at least one survey, with a core group of 2,317 robust users who filled out multiple surveys during the course of the six-month study. Results were compared to existing asthma patient studies and to external factors as a control for the reliability of patient-reported data. For example, scientists were able to correlate increased daily asthma symptoms among participants in Washington State with an outbreak of wildfires at the time. Similar factors that could be corroborated in the patient data included pollen levels and heat. Data for commonly used asthma metrics, such as peak flow, matched what has been observed in other studies.
Yu-Feng Yvonne Chan, et al. The Asthma Mobile Health Study- a large-scale clinical observational study using ResearchKit. Nature Biotechnology. DOI: 10.1038/nbt.3826