A multi-dataset analysis of equity in the treatment of patients with Acute Myocardial Infarction (AMI) in the Intensive Care Unit (ICU)
From left: Purity Mugambi (Computer Science), Rachel 'Rae' Walker (Nursing), Joohyun Chung (Nursing), Stephanie Carreiro (Emergency Medicine) and Madalina 'Ina' Fiterau Brostean (Computer Science).
In this work, clinicians and data scientists come together to determine whether there is inequity in treatment of patients who experienced heart attack, known medically as Acute Myocardial Infarction (AMI), and who were hospitalized in the Intensive Care Unit (ICU). Health inequity is often a consequence of social injustices/biases such as racism, ableism, classism, sexism, and fatphobia, integrating into healthcare systems. This team aims to identify whether differences in treatment of patient subgroups cannot be explained by anything else other than the patients’ ethnicity/race, and/or, sex. The multidisciplinary team in this project brings together expertise on identifying patients diagnosed with AMI, defining a standard treatment regimen patients should have received to manage AMI and pain. Confounding variables that affect how those treatments are given are determined and considered in the analysis. The proposed theoretical framework identifies inequality by employing computational tools and statistical models to extract and quantify the differences in treatments provided to the various pre-identified patient subgroups in the study cohort. Findings from this work will be useful in applying for external grants to extend the work beyond the current patient cohort, and the three datasets under study. Additionally, they will inform and caution researchers and other stakeholders of the inequities in treatments inherent in the datasets studied.