Research
The impact of the COVID-19 pandemic on treatment for domestic violence injuries: evidence from medical claims
Review of Economics of the Household
With Lauren Gilbert and Lauren Schechter. Previous studies have observed heterogeneous changes in domestic violence-related 911 calls, police incident reports, and arrests at the onset of the COVID-19 pandemic. In this study, we use a large-scale medical claims database with coverage of over 100 million patients to examine the impact on domestic violence victims’ use of emergency department care for their injuries in the early weeks of the pandemic compared to the corresponding weeks in previous years. We find a 23–35% decrease in utilization of emergency medical services by domestic violence victims between March and June of 2020. Based on this finding, it is essential to use caution when using medical claims to measure domestic violence in future research covering this time period. Decreases in care utilization also have important implications for the detection, screening, and treatment of domestic violence injuries during future public health crises.
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The Emerging Infrastructure of US Firearms Injury Data
Preventive Medicine
With Catherine Barber and Philip J. Cook. For every fatal shooting in the United States, detailed information from reports of coroners or medical examiners, police departments, and other sources is recorded in the National Violent Death Reporting System. There is no such system in place for nonfatal shootings, which far outnumber fatalities. We discuss additional reforms needed to generate timely, accurate, publicly accessible data from hospitals and police.
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Measuring gun violence in police data sources: transitioning to NIBRS
Injury Epidemiology
The majority of gun violence in the United States does not result in physical injury and therefore cannot be completely measured using hospital data. To measure the full scope of gun violence, the nation’s crime reporting systems that collect police reports of crimes committed with a firearm are vital. However, crime data reporting conventions may underestimate gun violence in the U.S. This paper compares crime data sources to assess underestimation of gun violence.
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Estimating Nonfatal Firearm Injury Locations using Natural Language Processing and Machine Learning Methods
JAMA Network-Open
This cross-sectional study of 22 years of data from the National Electronic Injury Surveillance System Firearm Injury Surveillance Study used natural language processing of unstructured medical text combined with machine learning models to classify the location of nonfatal gunshot injuries. Contrary to existing national estimates of these injuries that indicate they occur most often in homes, this analysis found that these injuries occur most often in the street or highway.
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A comparative analysis of crime guns
The Russell Sage Foundation Journal of the Social Sciences
With Megan E. Collins, Thomas L. Scott and Charles F. Wellford. Information is limited on how firearms move from legal possession to illegal possession and use in criminal activities, largely because of data collection capacity and a lack of recent, exhaustive recovery data across jurisdictions. This article includes both an analysis of firearms trace data and prisoner interviews across multiple jurisdictions: New Orleans, Louisiana, Prince George’s County, Maryland, and Chicago, Illinois. Findings indicate that recoveries and trace successes vary across jurisdictions and by type of crime.
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Sources of guns to dangerous people: what we learn by asking them
Preventive Medicine
With Philip J. Cook and Harold A. Pollack. This paper contributes original empirical data on the gun transactions that arm offenders in Chicago. Conducted in the fall of 2013, data come from of an open-ended survey of 99 inmates of Cook County Jail that focused on a subset of violence-prone individuals with access to firearms. Respondents obtain most of their guns from their social network of personal connections. Rarely is the proximate source either direct purchase from a gun store, or theft.
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