When a surgical procedure gets canceled, a child gains no health benefit, families' time off work and pre-op anxiety is in vain, and our not-for-profit children's hospital loses ~$1 per second. To understand cancellation, I needed to analyze thousands of patient records. Despite zero formal training, I learned to tidy and then visualize data – and even do geocoding and machine learning. Once we identified children at high risk, we could target additional support to their families. Furthermore, we showed that surgery cancellation contributes to health inequality. The R Studio/tidyverse ecosystem allows novices to do sophisticated analytics, and is helping us improve access to health care for the most disadvantaged children in our communities.
Talk by Nick Pratap
Full title: Novice to data scientist: how a pediatric anesthesiologist used R Studio to help disadvantaged kids access surgical care
