The controversy surrounding recent high-profile police shootings (e.g., Michael Brown in Ferguson, Missouri; Laquan McDonald in Chicago) has prompted inquiry into the possible existence of bias in officers’ use-of-force decisions. Using a balanced mix of shoot/don’t shoot cases from a large municipal police department in the Southwestern United States, this study analyzed the effect of suspect race on officers’ decisions to shoot—while accounting for other theoretically relevant factors. Findings suggest that Black suspects were not disproportionately the target of police shootings; Black suspects were approximately one third as likely to be shot as other suspects. This finding challenges the current bias narrative and is consistent with the other race-related findings in recently published research.
We analyze a set of 207 Dallas Police Department officer-involved shooting incidents in reference to 1,702 instances in which officers from the same agency drew their firearms but did not shoot at the suspect. We find that situational factors of whether the suspect was armed and whether an officer was injured were the best predictors of the decision to shoot. We also find that African Americans are less likely than Whites to be shot. It is important to collect data on encounters in which weapons are and are not discharged. Analyses examining only shootings is fundamentally limited in assessing racial bias.
Background: A key first step in optimising COVID-19 patient outcomes during future case-surges is to learn from the experience within individual hospitals during the early stages of the pandemic. The aim of this study was to investigate the extent of variation in COVID-19 outcomes between National Health Service (NHS) hospital trusts and regions in England using data from MarchÀJuly 2020. Methods: This was a retrospective observational study using the Hospital Episode Statistics administrative dataset. Patients aged 18 years who had a diagnosis of COVID-19 during a hospital stay in England that was completed between March 1st and July 31st, 2020 were included. In-hospital mortality was the primary outcome of interest. In secondary analysis, critical care admission, length of stay and mortality within 30 days of discharge were also investigated. Multilevel logistic regression was used to adjust for covariates. Findings: There were 86,356 patients with a confirmed diagnosis of COVID-19 included in the study, of whom 22,944 (26.6%) died in hospital with COVID-19 as the primary cause of death. After adjusting for covariates, the extent of the variation in-hospital mortality rates between hospital trusts and regions was relatively modest. Trusts with the largest baseline number of beds and a greater proportion of patients admitted to critical care had the lowest in-hospital mortality rates. Interpretation: There is little evidence of clustering of deaths within hospital trusts. There may be opportunities to learn from the experience of individual trusts to help prepare hospitals for future case-surges.
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