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Abstract
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he study by Hsu and colleagues1 used a state hospitalization database to determine the rate of nonfatal firearm injury hospitalizations in New York State from 2005 to 2016. They found the overall rate of nonfatal firearm injury hospitalizations to be 18.4 hospitalizations per 100 000 population, noting significant county-level differences in incidence based on demographics, urbanicity, and changes in incidence over time. The study by Hsu et al1 contributes to an increasing effort to improve the quality of firearm injury data in the US. Firearm injury data have been problematic, as there is no nationwide comprehensive public health data set that provides accurate surveillance or robust descriptions of nonfatal firearm injuries. Many of the limitations of existing data sources are highlighted in the recent report, "First report of the expert panel on firearms data infrastructure: the state of firearms data in 2019," published by the NORC at the University of Chicago.2 Many of the data sets used to determine national estimates of firearm injury and hospitalization are flawed by using small sample sizes to generate probability estimates, undersampling trauma centers, which treat most firearm injuries in the US, and using inaccurate or miscategorized causes of injury in administrative coding.
While we are fortunate to have accurate fatal firearm injury data reported by the Centers for Disease Control and Prevention's Web-based Injury Statistics Query and Reporting System and National Violent Death Reporting System, which provide robust data to describe the risks and circumstances surrounding such injuries, the lack of simultaneous systems and accurate rates of nonfatal firearm injury is very limiting, given that most firearm injuries due to assault and unintentional firearm injuries are nonfatal.3 To inform our understanding of the burden of firearm injury and develop and evaluate strategies to control it, we must have access to epidemiologic data for both fatal and nonfatal firearm injuries.
Some states have invested in robust hospitalization databases or state inpatient databases to track hospital encounters for all payers, which provides an opportunity to assess detailed state-level firearm hospitalization rates. The study by Hsu and colleagues1 used state-level data from the New York Statewide Planning and Research Cooperative System to report rates of hospital encounters for nonfatal firearm injuries from 2005 to 2016. Although perhaps limited by the use of administrative and billing data and minimal reporting on intent, such a system allows for assessment of incidence over time with the ability to stratify rates based on demographics and geographic areas (ie, counties). These data can then be used to assess associations between firearm injury rates and county-level characteristics, such as income, which Hsu et al1 explored. They found notable fluctuations in the rates based on the year, with significantly higher rates for men, Black individuals, and individuals living in large metropolitan areas and counties with lower median household incomes. Although the intent behind the injury was not reported and is a limitation here, other studies have reported the fatality rate at 5% for unintentional injury and 20% for assaults, compared with 85% for suicide attempts, leading the reader to infer that most of the reported injuries reported in the database were due to assault, especially since children younger than 15 years were excluded.3 The findings of Hsu et al1 are reflective of what is reported in the literature regarding populations that are more likely to experience firearm injuries, including Black men and individuals in urban areas. They also found that 10.7% of individuals who have experienced an initial firearm injury experience a second firearm injury.3,4
Hsu et al1 observed significant variation in firearm injury incidence and changes in incidence over time among counties. This is important to note, and this is a valuable aspect of state databases or any data set that has the ability to report the county, city, or zip code of residence or location of injury. As more data emerge about the association of social determinants of health, such as unemployment, income inequality, social capital, social mobility, and community investment in social welfare, with firearm injury risk it is imperative that such investigations assess how these differ and change over time relative to firearm injury incidence, as such changes may be associated with difference between communities and provide more opportunity for targeted prevention efforts at the macro level.5 While only income level was explored in the study by Hsu et al,1 county- or zip code-level linkages to other social determinants of health or indices of disparity that are more inclusive of multiple elements of disadvantage or inequality could be further explored to better understand these differences appreciated at the county level, or even at neighborhood level, given that these may vary dramatically within counties...
Language: en |