Firearm violence and associated factors among young adults presenting to emergency departments in three cities: Baseline results from Project SPARK.

OBJECTIVE: Recent shifts in U.S. violence dynamics call for updated violence epidemiology among general emergency department (ED) samples of young adults. Using baseline data from a multi-site longitudinal study of firearm violence prediction, we describe violence rates and associated factors. METHODS: Staff approached age 18-24 entrants to Level-1 trauma centers in three cities (Flint, Seattle, Philadelphia; 7/2021-5/2023). Consenting participants completed a survey including validated measures of violence experience, firearm-related behaviors, substance use, mental health symptoms, peer/parental/familial behaviors, community violence, and attitudes/norms. We described the sample and examined factors associated with firearm assault (victimization/aggression, including threats). RESULTS: Across sites, 1506 participants enrolled (41.7. % Black; 33.6 % White; 61.4. % female). Half of participants self-reported past-six-month violent victimization and/or aggression; non-partner violence, and violent victimization were most common. Over half of participants self-reported high-risk substance use, and over half screened positive for post-traumatic stress disorder, depression, and/or anxiety. About 14.4 % self-reported past-six-month firearm assault, and 5.9 % self-reported firearm violence (excluding threats). Adjusted analysis showed community violence exposure was most strongly associated with firearm assault; each one-point-increase corresponded to a 13.7 % (95 %CI: 10.4 %-16.9 %) absolute increase in firearm assault prevalence. Drug misuse, mental health symptoms, firearm carrying, retaliatory attitudes, prosocial attitudes, and family conflict were also associated with firearm assault. CONCLUSIONS: Violence, including firearm assault, is common among young adults entering urban EDs, and is associated with several psychosocial factors. High rates of substance use and mental health symptoms underscore this as a high-need population. Leveraging this information could help tailor interventions and optimize resource allocation.

Emergency Medicaid enrollment after traumatic injury predicts long-term health care utilization.

BACKGROUND: Injured patients have high rates of uninsurance, which is associated with worse outcomes. Insurance linkage programs that connect patients to Medicaid coverage can prevent catastrophic costs for patients. Less is known about the long-term impact of insurance enrollment. We examined health care utilization for previously uninsured patients, hypothesizing that newly insured patients postinjury would use health care more than those remaining uninsured. METHODS: We linked institutional trauma registry data to the electronic medical record to identify injured patients aged 18 to 64 years from 2017 to 2021. Patients admitted without insurance and then retroactively insured (RI) during hospitalization were compared with patients with preestablished Medicaid (Medicaid insured [MI]) and those remaining uninsured. We compared demographic and injury characteristics and future health care utilization, including hospitalizations, emergency department (ED) visits, and clinic visits, among groups at 30 days and 12 months postinjury. Patient-reported outcomes (PROs) 6 months after injury were compared by group for a subset of patients participating in an ongoing study of long-term PROs. RESULTS: We compared 494 RI patients with 1,706 MI and 148 uninsured patients. Retroactively insured patients were younger, more likely to have penetrating injuries, and longer hospitalization than other groups. There was a significant increase in ED and clinic visits and hospital admissions at 30 days and 12 months between RI and uninsured patients (p < 0.001). Using multivariable logistic regression, RI was associated with higher future ED utilization, hospital admissions, and specialist visits at 30 days and 12 months compared with uninsured patients. Of the 265 patients with 6-month PROs, Medicaid coverage was not associated with any significant difference in physical function or anxiety. CONCLUSION: Patients enrolled in insurance postinjury are more likely to use health care in the future than patients without insurance, but the downstream effects are less clear. Health insurance is a necessary step but not independently sufficient to optimize care and improve health outcomes. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level IV.

Feedback and Financial Incentives for Reducing Cell Phone Use While Driving: A Randomized Clinical Trial.

Importance: Handheld phone use while driving is a major factor in vehicle crashes. Scalable interventions are needed to encourage drivers not to use their phones. Objective: To test whether interventions involving social comparison feedback and/or financial incentives can reduce drivers' handheld phone use. Design, Setting, and Participants: In a randomized clinical trial, interventions were administered nationwide in the US via a mobile application in the context of a usage-based insurance program (Snapshot Mobile application). Customers were eligible to be invited to participate in the study if enrolled in the usage-based insurance program for 30 to 70 days. The study was conducted from May 13 to June 30, 2019. Analysis was completed December 22, 2023. Interventions: Participants were randomly assigned to 1 of 6 trial arms for a 7-week intervention period: (1) control; (2) feedback, with weekly push notification about their handheld phone use compared with that of similar others; (3) standard incentive, with a maximum $50 award at the end of the intervention based on how their handheld phone use compared with similar others; (4) standard incentive plus feedback, combining interventions of arms 2 and 3; (5) reframed incentive plus feedback, with a maximum $7.15 award each week, framed as participant's to lose; and (6) doubled reframed incentive plus feedback, a maximum $14.29 weekly loss-framed award. Main Outcome and Measure: Proportion of drive time engaged in handheld phone use in seconds per hour (s/h) of driving. Analyses were conducted with the intention-to-treat approach. Results: Of 17 663 customers invited by email to participate, 2109 opted in and were randomized. A total of 2020 drivers finished the intervention period (68.0% female; median age, 30 [IQR, 25-39] years). Median baseline handheld phone use was 216 (IQR, 72-480) s/h. Relative to control, feedback and standard incentive participants did not reduce their handheld phone use. Standard incentive plus feedback participants reduced their use by -38 (95% CI, -69 to -8) s/h (P = .045); reframed incentive plus feedback participants reduced their use by -56 (95% CI, -87 to -26) s/h (P < .001); and doubled reframed incentive plus feedback participants reduced their use by -42 s/h (95% CI, -72 to -13 s/h; P = .007). The 5 active treatment arms did not differ significantly from each other. Conclusions and Relevance: In this randomized clinical trial, providing social comparison feedback plus incentives reduced handheld phone use while individuals were driving. Trial Registration: ClinicalTrials.gov Identifier: NCT03833219.

Fatal and Nonfatal Firearm Injury Rates by Race and Ethnicity in the United States, 2019 to 2020.

BACKGROUND: Racial disparities in firearm injury death in the United States are well established. Less is known about the magnitude of nonfatal and total firearm injury. OBJECTIVE: To combine health care data with death certificate data to estimate total firearm injuries in various racial and ethnic groups. DESIGN: Retrospective, cross-sectional study. SETTING: Fatal injury data were collected from the Centers for Disease Control and Prevention. Data on nonfatal injuries were collected from the Nationwide Emergency Department Sample (NEDS), a 20% stratified sample of U.S. emergency department visits, weighted to provide national estimates for the United States, 2019 to 2020. PARTICIPANTS: All firearm injuries and deaths in the United States. INTERVENTION: Race and ethnicity were classified into 5 mutually exclusive categories: Asian or Pacific Islander, Black, Hispanic, Native American, and White. International Classification of Diseases, 10th Revision codes were used to classify firearm injury intent. MEASUREMENTS: Incidence of fatal and nonfatal injury in the U.S. population and case-fatality ratios (CFRs). RESULTS: There were 252 376 total firearm injuries, including 84 908 deaths from firearm injures. Of all firearm injuries, 37.8% were unintentional, 37.3% were assault related, 21.0% were self-harm, and 1.3% were law enforcement associated. Self-harm had the highest CFRs (90.9% overall). Unintentional injuries accounted for just 1021 (1.2%) deaths but 94 433 (56.4%) of nonfatal injuries. Rates of self-harm were highest among White persons (11.0 per 100 000 population in 2020) followed by Native Americans (8.6 per 100 000). Rates of assault were highest among Black persons (70.1 per 100 000), as were unintentional injuries (56.1 per 100 000). LIMITATION: Findings are limited by the accuracy of discharge coding in NEDS, particularly regarding injury intent and patient race and ethnicity. CONCLUSION: From 2019 to 2020, the total burden of firearm injuries amounts to an average of 1 injury every 4 minutes and 1 death every 12 minutes in the United States. Racial disparities in firearm injury death are mirrored in nonfatal injury. PRIMARY FUNDING SOURCE: None.

Health Care Use Among Patients Retroactively Insured via a Hospital-Based Insurance Linkage Program.

OBJECTIVE: Over 25% of the 27 million uninsured individuals in the United States are eligible for Medicaid. Many hospitals have insurance linkage programs that assist eligible patients with enrollment, but little is known about the impact of these programs on care utilization. This research assessed health care utilization and health outcomes among patients enrolled in Medicaid via a hospital-based insurance linkage program. METHODS: This retrospective cohort study included adults aged 18-64 admitted to the hospital from 2016 to 2021. Those who obtained insurance retroactively via insurance linkage (RI) were compared with those who presented with Medicaid (MI) or remained uninsured (UI). The primary outcome was the presence of at least one visit with a primary care provider (PCP) in the 12 months following index admission. Secondary outcomes included having an assigned PCP, ED revisits, and hospital readmissions. For patients with diabetes and hypertension, 12-month hemoglobin A1c (HbA1c) and blood pressure (BP) readings were tracked. RESULTS: Of 3882 patients admitted with no insurance, 2905 (74.8%) were enrolled in insurance (RI). In multivariable analysis, RI patients were 14% more likely (OR 1.14, p = 0.020) to have completed at least one PCP visit by 12 months after index admission compared to those with preexisting Medicaid (MI), and uninsured patients were 29% less likely (OR 0.71, p = 0.003). MI and RI patients also had more ED revisits (p < 0.001) and greater 12-month reductions in blood pressure (p < 0.001) compared with uninsured patients. CONCLUSION: Hospital-based insurance linkage reached three-quarters of uninsured patients and was associated with increased utilization of acute and outpatient health care services. An acute care encounter represents an opportunity to connect patients to insurance, a key step toward improving their health outcomes.

Association between patient-reported onset-to-door time and mortality in patients hospitalized with COVID-19 disease.

INTRODUCTION: Timely hospital presentation and treatment are critical for recovery from coronavirus disease (COVID-19). However, the relationship between symptom onset-to-door time and key clinical outcomes, such as inpatient mortality, has been poorly understood due to the difficulty of retrospectively measuring symptom onset in observational data. This study examines the association between patient-reported symptom onset-to-door time (ODT) and mortality among patients hospitalized and treated for COVID-19 disease. METHODS: We conducted a retrospective cohort study of emergency department (ED) encounters of patients with COVID-19 disease who were hospitalized and received remdesivir and/or dexamethasone between March 1, 2020, and March 1, 2022. The exposure was patient-reported ODT in days. The outcome of interest was inpatient mortality, including referral to hospice care. We used multivariable logistic regression to examine the association between ODT and mortality while adjusting for patient characteristics, hospital sites, and seasonality. We tested whether severe illness on hospital presentation modified the association between ODT and mortality. Severe illness was defined by Emergency Severity Index triage level 1 or 2 and hypoxia (SpO2 < 94%). RESULTS: Of the 3451 ED hospitalizations included, 439 (12.7%) resulted in mortality, and 1693 (49.1%) involved patients with severe illness on hospital presentation. Greater ODT was significantly associated with lower odds of inpatient mortality (adjusted odds ratio (AOR) = 0.96, 95% CI = 0.93-1.00, P = 0.023). There was a statistically significant interaction between ODT and severe illness at hospital arrival on mortality, suggesting the negative association between ODT and mortality specifically pertained to patients who were not severely ill upon ED presentation (AOR = 0.93, 95% CI = 0.87-1.00, P = 0.035). The adjusted probability of mortality was significantly lower for non-severely ill, hospitalized patients who presented on days 8-14 (5.2%-3.3%) versus days 0-3 (9.4%-7.5%) after symptom onset. CONCLUSION: More days between symptom onset and hospital arrival were associated with lower mortality among hospitalized patients treated for COVID-19 disease, particularly if they did not have severe illness at ED presentation. However, onset-to-door time was not associated with mortality among hospitalized patients with severe illness at ED presentation. Collectively, these results suggest that non-severely ill COVID-19 patients who require hospitalization are less likely to decompensate with each passing day without severe illness. These findings may continue to guide clinical care delivery for hospitalized COVID-19 patients.

Trends in Before Medically Advised Discharges for Patients With Opioid Use Disorder, 2016-2020.

This study examines discharge trends for opioid-related admissions from 2016-2020 with a focus on admissions with opioid use disorder and an injection-related infection.

Identifying Patient Characteristics Associated With Opioid Use to Inform Surgical Pain Management.

Objective: Balancing surgical pain management and opioid stewardship is complex. Identifying patient-level variables associated with low or no use can inform tailored prescribing. Methods: A prospective, observational study investigating surgical procedures, prescription data, and patient-reported outcomes at an academic health system in Pennsylvania. Surgical patients were consented following surgery, and prospective data were captured using automated text messaging (May 1, 2021-February 29, 2022). The primary outcome was opioid use. Results: Three thousand six hundred three (30.2%) patients consented. Variation in patient reported used included 28.1% of men reported zero use versus 24.3% of women, 20.5% of Black patients reported zero use versus 27.2% of white patients. Opioid-naïve patients reported more zero use as compared with chronic use (29.7% vs 9.8%). Patients reporting higher use had more telephone calls and office visits within 30 days but no change in emergency department utilization or admissions. Higher discharge pain score was associated with higher use. In the adjusted analysis, opioid use relative to the guideline, higher use was associated with age, male sex, obesity, discharge pain score, and history of mental health disorder. In the adjusted model, younger age and being opioid-naïve to be associated with low to zero use across procedures. Conclusions: Younger age, being opioid-naïve, and lower discharge pain score are associated with low or no postoperative opioid use. These characteristics can be used by clinicians to help tailor opioid prescribing to specific patients to reduce the risk of prolonged exposure and unused `ts in the community.

Association of Urine Fentanyl Concentration With Severity of Opioid Withdrawal Among Patients Presenting to the Emergency Department.

BACKGROUND AND AIMS: Fentanyl is involved in most US drug overdose deaths and its use can complicate opioid withdrawal management. Clinical applications of quantitative urine fentanyl testing have not been demonstrated previously. The aim of this study was to determine whether urine fentanyl concentration is associated with severity of opioid withdrawal. DESIGN: This is a retrospective cross-sectional study. SETTING: This study was conducted in 3 emergency departments in an urban, academic health system from January 1, 2020, to December 31, 2021. PARTICIPANTS: This study included patients with opioid use disorder, detectable urine fentanyl or norfentanyl, and Clinical Opiate Withdrawal Scale (COWS) recorded within 6 hours of urine drug testing. MEASUREMENTS: The primary exposure was urine fentanyl concentration stratified as high (>400 ng/mL), medium (40-399 ng/mL), or low (<40 ng/mL). The primary outcome was opioid withdrawal severity measured with COWS within 6 hours before or after urine specimen collection. We used a generalized linear model with γ distribution and log-link function to estimate the adjusted association between COWS and the exposures. FINDINGS: For the 1127 patients in our sample, the mean age (SD) was 40.0 (10.7), 384 (34.1%) identified as female, 332 (29.5%) reported their race/ethnicity as non-Hispanic Black, and 658 (58.4%) reported their race/ethnicity as non-Hispanic White. For patients with high urine fentanyl concentrations, the adjusted mean COWS (95% confidence interval) was 4.4 (3.9-4.8) compared with 5.5 (5.1-6.0) among those with medium and 7.7 (6.8-8.7) among those with low fentanyl concentrations. CONCLUSIONS: Lower urine fentanyl concentration was associated with more severe opioid withdrawal, suggesting potential clinical applications for quantitative urine measurements in evolving approaches to fentanyl withdrawal management.

Frequency and Trends of Pre-Pandemic Surge Periods in U.S. Emergency Departments, 2006-2019.

OBJECTIVES: To quantify the frequency, outside of the pandemic setting, with which individual healthcare facilities faced surge periods due to severe increases in demand for emergency department (ED) care. DESIGN: Retrospective cohort study. SETTING: U.S. EDs. PATIENTS: All ED encounters in the all-payer, nationally representative Nationwide Emergency Department Sample from the Healthcare Cost and Utilization Project, 2006-2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Frequency of surge periods defined as ED months in which an individual facility ED saw a greater than 50% increase in ED visits per month above facility-/calendar month-specific medians. During 2006-2019, 3,317 U.S. EDs reported 354,534,229 ED visits across 142,035 ED months. Fifty-seven thousand four hundred ninety-five ED months (40.5%) during the study period had a 0% to 50% increase in ED visits that month above facility-specific medians and 1,952 ED months (1.4%) qualified as surge periods and had a greater than 50% increase in ED visits that month above facility-specific medians. These surge months were experienced by 397 unique facility EDs (12.0%). Compared with 2006, the most proximal pre-pandemic period of 2016-2019 had a notably elevated likelihood of ED-month surge periods (odds ratios [ORs], 2.36-2.84; all p < 0.0005). Compared with the calendar month of January, the winter ED months in December through March have similar likelihood of an ED-month qualifying as a surge period (ORs, 0.84-1.03; all p > 0.05), while the nonwinter ED months in April through November have a lower likelihood of an ED-month qualifying as a surge period (ORs, 0.65-0.81; all p < 0.05). CONCLUSIONS: Understanding the frequency of surges in demand for ED care-which appear to have increased in frequency even before the COVID-19 pandemic and are concentrated in winter months-is necessary to better understand the burden of potential and realized acute surge events and to inform cost-effectiveness preparedness strategies.

Patient and clinician perspectives of a remote monitoring program for COVID-19 and lessons for future programs.

COVID Watch is a remote patient monitoring program implemented during the pandemic to support home dwelling patients with COVID-19. The program conferred a large survival advantage. We conducted semi-structured interviews of 85 patients and clinicians using COVID Watch to understand how to design such programs even better. Patients and clinicians found COVID Watch to be comforting and beneficial, but both groups desired more clarity about the purpose and timing of enrollment and alternatives to text-messages to adapt to patients' preferences as these may have limited engagement and enrollment among marginalized patient populations. Because inclusiveness and equity are important elements of programmatic success, future programs will need flexible and multi-channel human-to-human communication pathways for complex clinical interactions or for patients who do not desire tech-first approaches.

How Physician Self-Perceptions Affect the Impact of Peer Comparison Feedback on Opioid Prescribing.

Peer comparison feedback is a promising strategy for reducing opioid prescribing and opioid-related harms. Such comparisons may be particularly impactful among underestimating clinicians who do not perceive themselves as high prescribers relative to their peers. But peer comparisons could also unintentionally increase prescribing among overestimating clinicians who do not perceive themselves as lower prescribers than peers. The objective of this study was to assess if the impact of peer comparisons varied by clinicians' preexisting opioid prescribing self-perceptions. Subgroup analysis of a randomized trial of peer comparison interventions among emergency department and urgent care clinicians was used. Generalized mixed-effects models were used to assess whether the impact of peer comparisons, alone or combined with individual feedback, varied by underestimating or overestimating prescriber status. Underestimating and overestimating prescribers were defined as those who self-reported relative prescribing amounts that were lower and higher, respectively, than actual relative baseline amounts. The primary outcome was pills per opioid prescription. Among 438 clinicians, 54% (n = 236) provided baseline prescribing self-perceptions and were included in this analysis. Overall, 17% (n = 40) were underestimating prescribers whereas 5% (n = 11) were overestimating prescribers. Underestimating prescribers exhibited a differentially greater decrease in pills per prescription compared to nonunderestimating clinicians when receiving peer comparison feedback (1.7 pills, 95% CI, -3.2 to -0.2 pills) or combined peer and individual feedback (2.8 pills, 95% CI, -4.8 to -0.8 pills). In contrast, there were no differential changes in pills per prescription for overestimating versus nonoverestimating prescribers after receiving peer comparison (1.5 pills, 95% CI, -0.9 to 3.9 pills) or combined peer and individual feedback (3.0 pills, 95% CI, -0.3 to 6.2 pills). Peer comparisons were more impactful among clinicians who underestimated their prescribing compared to peers. By correcting inaccurate self-perceptions, peer comparison feedback can be an effective strategy for influencing opioid prescribing.

Disparities in emergency department and urgent care opioid prescribing before and after randomized clinician feedback interventions.

OBJECTIVES: Racial and ethnic minorities receive opioid prescriptions at lower rates and dosages than White patients. Though opioid stewardship interventions can improve or exacerbate these disparities, there is little evidence about these effects. We conducted a secondary analysis of a cluster-randomized controlled trial conducted among 438 clinicians from 21 emergency departments and 27 urgent care clinics. Our objective was to determine whether randomly allocated opioid stewardship clinician feedback interventions that were designed to reduce opioid prescriptions had unintended effects on disparities in prescribing by patient race and ethnicity. METHODS: The primary outcome was likelihood of receiving a low-pill prescription (low ≤10 pills, medium 11-19 pills, high ≥20 pills). Generalized mixed-effects models were used to determine patient characteristics associated with low-pill prescriptions during the baseline period. These models were then used to determine whether receipt of a low-pill prescription varied by patient race or ethnicity during the intervention period between usual care and three opioid stewardship interventions: (1) individual audit feedback, (2) peer comparison feedback, and (3) combined (individual audit + peer comparison) feedback. RESULTS: Compared with White patients, Black patients were more likely to receive a low-pill prescription during the baseline (adjusted odds ratio [OR] 1.18, 95% confidence interval [CI] 1.06-1.31, p = 0.002) and intervention (adjusted OR 1.43, 95% CI 1.07-1.91, p = 0.015). While combined feedback was associated with an overall increase in low-pill prescriptions as intended (adjusted OR 1.89, 95% CI 1.28-2.78, p = 0.001), there were no significant differences in treatment effects of any of the interventions by patient race and ethnicity. CONCLUSIONS: Combined individual audit and peer comparison feedback was associated with fewer opioid pills per prescription equally by patient race and ethnicity. However, the intervention did not significantly close the baseline disparity in prescribing by race.

The impact of Illinois' comprehensive handheld phone ban on talking on handheld and handsfree cellphones while driving.

INTRODUCTION: Distracted driving has been linked to multiple driving decrements and is responsible for thousands of motor-vehicle fatalities annually. Most U.S. states have enacted restrictions on cellphone use while driving, the strictest of which prohibit any manual operation of a cellphone while driving. Illinois enacted such a law in 2014. To better understand how this law affected cellphone behaviors while driving, associations between Illinois' handheld phone ban and self-reported talking on handheld, handsfree, and any cellphone (handheld or handsfree) while driving were estimated. METHODS: Data from annual administrations of the Traffic Safety Culture Index from 2012-2017 in Illinois and a set of control states were leveraged. The data were cast into a difference-in-differences (DID) modeling framework, which compared Illinois to control states in terms of pre- to post-intervention changes in the proportion of drivers who self-reported the three outcomes. Separate models for each outcome were fit, and additional models were fit to the subset of drivers who talk on cellphones while driving. RESULTS: In Illinois, the pre- to post-intervention decrease in the drivers' probability of self-reporting talking on a handheld phone was significantly more extreme than that of drivers in control states (DID estimate -0.22; 95% CI -0.31, -0.13). Among drivers who talk on cellphones while driving, those in Illinois exhibited a more extreme increase in the probability of talking on a handsfree phone while driving than those control states (DID estimate 0.13; 95% CI 0.03, 0.23). CONCLUSIONS: These results suggest that Illinois' handheld phone ban reduced talking on handheld phones while driving among study participants. They also corroborate the hypothesis that the ban promoted substitution from handheld to handsfree phones among drivers who talk on the phone while driving. PRACTICAL APPLICATIONS: These findings should encourage other states to enact comprehensive handheld phone bans to improve traffic safety.

How have firearm laws changed in states with unexpected decreases or increases in firearm homicide, 1990-2019?

Background: Firearm violence is one of the leading preventable causes of death and injury in the United States and is on the rise. While policies regulating access to firearms offer opportunities to prevent firearm-related deaths, an understanding of the holistic impact of changing state firearm policies on firearm homicide rates over the last 30 years is limited. Objectives: To identify US states that showed unexpected decreases and increases in firearm homicide rates and summarise their firearm policy changes in the last three decades. Methods: We analysed changes in firearm homicide rates by US state and county from 1990 to 2019. We triangulated across three estimation approaches to derive state rankings and identify the top and bottom three states which consistently showed unexpected decreases (low outliers) and increases (high outliers) in firearm homicide rates. We summarised firearm policy changes in state outliers using the RAND State Firearm Law Database. Results: We identified New York, District of Columbia, and Hawaii as low state outliers and Delaware, New Jersey, and Missouri as high state outliers. Low state outliers made more restrictive firearm policy changes than high state outliers, which covered a wider range of policy types. Restrictive changes in high state outliers primarily targeted high-risk populations (e.g., prohibited possessors, safe storage). Specific legislative details, such as the age threshold (18 vs 21 years old) for firearm minimum age requirements, also emerged as important for differentiating low from high state outliers. Conclusions: While no firearm law change emerged as necessary or sufficient, an accumulation of diverse restrictive firearm policies may be key to alleviating the death toll from firearm homicide.