Health Systems Innovation (HSI) Lunchtime Seminar Series with Professor Colin Fogarty
- Health Management Seminar
- On Campus Event
11:45am - 1:00pm
E62 - 550
Transparent methods for causal inference in observational studies: a case study on severe sepsis mortality in the ICU
Severe sepsis, defined as a systematic inflammatory response to infection that is accompanied by acute organ dysfunction. is a leading cause of morbidity and mortality worldwide. A critical decision along the hospital pathway for patients presenting with severe sepsis is whether to admit the patient to an intensive care unit (ICU), or rather to an appropriate hospital ward. Through data from the University of Pennsylvania hospital system, we assess the causal effect of admission to the ICU versus to a hospital ward on mortality for severe sepsis patients. Using this data set as a case study, we highlight more generally the importance of transparent research methods as a means of facilitating critical discussion about a study's findings. Methods fitting this description are presented for (i) identifying regions of "similarity" between the groups being compared; (ii) correcting for biases due to differences in measured covariates; and (iii) assessing the robustness of a study's findings to hidden biases.
Professor Fogarty is an Assistant Professor of Operations Research and Statistics at the MIT Sloan School of Management. His research interests lie in the design and analysis of observational studies.
He received his AB in statistics from Harvard University and his PhD in statistics from the Wharton School of the University of Pennsylvania. Bio►