A shared data approach more accurately represents the rates and patterns of violence with injury assaults

Linking emergency care and police department data to strengthen timely information on violence-related paediatric injuries

BACKGROUND

Combined ED and police department (PD) data have improved violence surveillance in the UK, enabling significantly improved prevention. We sought to determine if the addition of emergency medical service (EMS) data to ED data would contribute meaningful information on violence-related paediatric injuries beyond PD record data in a US city.

METHODS

Cross-sectional data on self-reported violence-related injuries of youth treated in the ED between January 2015 and September 2016 were combined with incidents classified by EMS as intentional interpersonal violence and incidents in which the PD responded to a youth injury from a simple or aggravated assault, robbery or sexual offence. Nearest neighbour hierarchical spatial clustering detected areas in which 10 or more incidents occurred during this period (hotspots), with the radii of the area being 1000, 1500, 2000 and 3000 ft. Overlap of PD incidents within ED&EMS hotspots (and vice versa) was calculated and Spearman's r tested statistical associations between the data sets, or ED&EMS contribution to PD violence information.

RESULTS

There were 935 unique ED&EMS records (ED=381; EMS=554). Of these, 877 (94%) were not in PD records. In large hotspots >2000 ft, ED&EMS records identified one additional incident for every three in the PD database. ED and EMS provided significant numbers of incidents not reported to PD. Significant correlations of ED&EMS incidents in PD hotspots imply that the ED&EMS incidents are as pervasive across the city as that reported by PD. In addition, ED and EMS provided unique violence information, as ED&EMS hotspots never included a majority (>50%) of PD records. Most (676/877; 77%) incidents unique to ED&EMS records were within 1000 ft of a school or park.

CONCLUSIONS

Many violence locations in ED and EMS data were not present in PD records. A combined PD, ED and EMS database resulted in new knowledge of the geospatial distribution of violence-related paediatric injuries and can be used for data-informed and targeted prevention of violence in which children are injured-especially in and around schools and parks.

Implementation and initial analysis of Cardiff Model data collection procedures in a level I trauma adult emergency department

OBJECTIVES

Our understanding of community violence is limited by incomplete information, which can potentially be resolved by collecting violence-related injury information through healthcare systems in tandem with prior data streams. This study assessed the feasibility of implementing Cardiff Model data collection procedures in the emergency department (ED) setting to improve multisystem data sharing capabilities and create more representative datasets.

DESIGN

Information collection fields were incorporated into the ED electronic health record (EHR), which gathered additional information from patients reporting assaultive injuries. ED nurses were surveyed to evaluate implementation and feasibility of information collection. Logistic regression was performed to determine associations between missing location information and patient demographic data.

SETTING

60-bed academic level I trauma adult ED in a large Midwestern city.

PARTICIPANTS

2648 patients screened positive for assault injuries between 2017 and 2020. 198 patients were omitted due to age outside the range served by this ED. Unselected inclusion of 150 ED nurses was surveyed.

MAIN OUTCOME MEASURES

Main outcomes include nursing staff survey responses and ORs for providing complete injury information across various patient demographics.

RESULTS

Most ED nurses believed that information collection aligned with the hospital's mission (92%), wanted information collection to continue (88%), did not believe that information collection impacted their workflow (88%), and reported taking under 1 min to screen and document violence information (77%). 825 patients (31.2%) provided sufficient information for geospatial mapping. Likelihood of providing complete location information was significantly associated with patient gender, race, arrival means, accompaniment, trauma type and year.

CONCLUSIONS

It is feasible to implement information collection procedures about location-based, assault-related injuries through the EHR in the adult ED setting. Nurses reported being receptive to collecting information. Analyses suggest patient-level and time variables impact information collection completeness. The geospatial information collected can greatly improve preexisting law enforcement and emergency medical systems datasets.

Measuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004-2014

PURPOSE

Commonly-used violence surveillance systems are biased towards certain populations due to overreporting or over-scrutinized. Hospital discharge data may offer a more representative view of violence, through use of proxy codes, i.e. diagnosis of injuries correlated with violence. The goals of this paper are to compare the trends in violence in Minnesota, and associations of county-level demographic characteristics with violence rates, measured through explicitly diagnosed violence and proxy codes. It is an exploration of how certain sub-populations are overrepresented in traditional surveillance systems.

METHODS

Using Minnesota hospital discharge data linked with census data from 2004 to 2014, this study examined the distribution and time trends of explicit, proxy, and combined (proxy and explicit) codes for child abuse, intimate partner violence (IPV), and elder abuse. The associations between county-level risk factors (e.g., poverty) and county violence rates were estimated using negative binomial regression models with generalized estimation equations to account for clustering over time.

RESULTS

The main finding was that the patterns of county-level violence differed depending on whether one used explicit or proxy codes. In particular, explicit codes suggested that child abuse and IPV trends were flat or decreased slightly from 2004 to 2014, while proxy codes suggested the opposite. Elder abuse increased during this timeframe for both explicit and proxy codes, but more dramatically when using proxy codes. In regard to the associations between county level characteristics and each violence subtype, previously identified county-level risk factors were more strongly related to explicitly-identified violence than to proxy-identified violence. Given the larger number of proxy-identified cases as compared with explicit-identified violence cases, the trends and associations of combined codes align more closely with proxy codes, especially for elder abuse and IPV.

CONCLUSIONS

Violence surveillance utilizing hospital discharge data, and particularly proxy codes, may add important information that traditional surveillance misses. Most importantly, explicit and proxy codes indicate different associations with county sociodemographic characteristics. Future research should examine hospital discharge data for violence identification to validate proxy codes that can be utilized to help to identify the hidden burden of violence.

Criminal punishment and violent injury in Minnesota

BACKGROUND

Violence is one of the leading causes of injury and death in the United States. One-way society attempts to eliminate violence is through criminal punishment. Yet, in many contexts, punishment fails to reduce violence and may cause other harms. Current research on violence often suffers from same-source bias which can produce spurious associations. This study assesses the associations of different forms of criminal punishment (monetary sanctions, incarceration, and probation) with violent injuries in two unique datasets.

METHODS

This study examines a unique combination of hospital discharge data and court administrative data, two Minnesota county-level data sources. First, we assess the spatial distribution of the three criminal punishment variables and two violent injury variables, violent injury overall and violent injury in children by county from 2010 to 2014, using Moran's I statistic and Local Indicators of Spatial Autocorrelation. Then we assess the association of criminal punishment on violent injury and child abuse injury using a two-way fixed effects panel models.

RESULTS

Child abuse injuries are relatively rare in our data but are significantly concentrated geographically, unlike violent injuries which are more dispersed throughout Minnesota. Incarceration and probation are significantly geographically concentrated in similar regions while monetary sanctions are not geographically concentrated. We find a link between probation loads and violent injury, specifically, with a 1 day increase in per capita probation supervision associated with a 0.044 increase in violent injury incidence per 1000 people. In contrast, monetary sanctions and incarceration loads have little association with either violent injury or child abuse injury incidence.

CONCLUSIONS

Criminal punishment is intended to reduce harm in society, but many argue that it may bring unintended consequences such as violence. This study finds that county-level probation has a modest positive association with county-level violent injury rates, but monetary sanctions and incarceration are less associated with violence injury rates. No measure of criminal punishment was associated with a reduction in violence. This study addresses a gap in previous literature by examining the association of punishment and violence in two unrelated datasets. High rates of criminal punishment and violent injury are both urgent public health emergencies. Further individual-level investigation is needed to assess potential links.