Community engagement and HIV research in the age of big data: Building a framework and tools for best practices

Big data science is becoming more prominent in many fields, including HIV. Data science utilizes electronic data already collected from multiple health sources, including administrative health data, i.e. data produced at each encounter with the healthcare system for administrative or billing purposes. Historically, active participation by People Living with HIV (PLHIV) has been pivotal to HIV research. However, data science has largely excluded PLHIV participation. It is established that community engagement is a matter of ethics and improved science, and it is problematic that this practice is underdeveloped in data science. Knowledge creation through data science brings two important shifts from traditional community-engaged research: data are typically not collected for research purposes, and opportunity for research collaboration comes after data collection. There is a need to develop new ways to engage people with lived/living experience in this form of research. This project brings together a team of older adults living with HIV, data scientists, clinicians and social scientists. We will examine how to authentically engage community members in data science while piloting community-led administrative data research. Our research investigates rates of survival from, and recurrence of, cardiovascular events among PLHIV compared to people without HIV in BC. Research about recurrence of cardiovascular events for PLHIV, particularly in Canada, is lacking. 

The goal is to build a framework for researchers to engage community in data science for improved health outcomes among PLHIV in BC and British Columbians generally. We also hope to help reframe big data science research from an extractive to a collaborative process for more impactful research elsewhere.