Predicting State-Level Firearm Suicide Rates: A Machine Learning Approach Using Public Policy Data.

INTRODUCTION: Over 40,000 people die by suicide annually in the U.S., and firearms are the most lethal suicide method. There is limited evidence on the effectiveness of many state-level policies on reducing firearm suicide. The objective of this study was to identify public policies that best predict state-level firearm suicide rates. METHODS: Data from the Centers for Disease Control and Prevention's WONDER system and the State Firearm Law Database, a longitudinal catalog of 134 firearm safety laws, were analyzed. The analysis included 1,450 observations from 50 states spanning 1991-2019. An ElasticNet regression technique was used to analyze the relationship between the policy variables and firearm suicide rates. Nested cross-validation was performed to tune the model hyperparameters. The study data were collected and analyzed in 2023 and 2024. RESULTS: The optimized ElasticNet approach had a mean MSE of 2.07, which was superior to non-regularized and dummy regressor models. The most influential policies for predicting the firearm suicide rate on average included laws requiring firearm dealers that sell handguns to have a state license and laws requiring individuals to obtain a permit to purchase a firearm through an approval process that includes law enforcement, among others. CONCLUSIONS: On average, firearm suicide rates were lower in state-years that had each influential policy active. Notably, these analyses were ecological and non-causal. However, this study was able to use a supervised machine learning approach with inherent feature selection and many policy types to make predictions using unseen data (i.e., balancing Lasso and Ridge regularization penalties).

Botánicas Function as Health Care Safety Nets Among Hispanic American Immigrants: A Brief Report.

As the U.S. population becomes more racially/ethnically diverse, the Hispanic American immigrant population has slowly grown in recent years. In the face of anti-immigrant policies, limited access to care, fear of deportation, discrimination, stigmatization, poverty, and other stressors, Hispanic American immigrants seek services from botánicas for religious, spiritual, medical, and psychosocial health reasons, including the accessibility and affordability of services from folk practitioners in these herbal dispensaries. Hispanics are the primary consumers of herbal remedies and complementary and alternative medicines in the United States. The purpose of this article is to emphasize the critical role of botánicas in the health and wellness of Hispanic American immigrants. Recommendations for health professionals are provided in the care of Hispanic Americans who utilize folk, traditional, and herbal medicines for health and healing.

Utah Latina/o/x suicide decedents less likely to die by firearm, even in rural areas: examining population-wide data from the Utah Office of the Medical Examiner.

Introduction: Suicide death remains a significantly rarer event among Latina/o/x populations compared to non-Latina/o/x populations. However, the reasons why Latina/o/x communities experience relatively lower suicide rates are not fully understood. Critical gaps exist in the examination of Latina/o/x suicide death, especially in rural settings, where suicide death by firearm is historically more common within non-Latina/o/x populations. Method: We tested whether the prevalence of Latina/o/x firearm suicide was meaningfully different in urban and rural environments and from non-Latino/a/x decedents when controlling for age, sex, and a social deprivation metric, the Area Deprivation Index. Suicide death data used in this analysis encompasses 2,989 suicide decedents ascertained in Utah from 2016 to 2019. This included death certificate data from the Utah Office of the Medical Examiner on all Utah suicide deaths linked to information by staff at the Utah Population Database. Results: Compared to non-Latina/o/x suicide decedents, Latina/o/x suicide decedents had 34.7% lower adjusted odds of dying by firearm. Additionally, among the firearm suicide decedents living only in rural counties, Latina/o/x decedents had 40.5% lower adjusted odds of dying by firearm compared to non-Latina/o/x suicide decedents. Discussion: The likelihood of firearm suicide death in Utah differed by ethnicity, even in rural populations. Our findings may suggest underlying factors contributing to lower firearm suicide rates within Latina/o/x populations, e.g., aversion to firearms or less access to firearms, especially in rural areas, though additional research on these phenomena is needed.

Poverty and Suicidal Ideation Among Hispanic Mental Health Care Patients Leading up to the COVID-19 Pandemic.

Introduction: Suicide rates have risen in Hispanic communities since 2015, and poverty rates among Hispanics often exceed the national average. Suicidality is a complex phenomenon. Mental illness may not alone explain whether suicidal thoughts or behaviors will occur; it remains uncertain how poverty affects suicidality among Hispanic persons with known mental health conditions. Our objective was to examine whether poverty was associated with suicidal ideation among Hispanic mental healthcare patients from 2016 to 2019. Methods: We used de-identified electronic health record (EHR) data from Holmusk, captured using the MindLinc EHR system. Our analytic sample included 4,718 Hispanic patient-year observations from 13 states. Holmusk uses deep-learning natural language processing (NLP) algorithms to quantify free-text patient assessment data and poverty for mental health patients. We conducted a pooled cross-sectional analysis and estimated logistic regression models. Results: Hispanic mental health patients who experienced poverty had 1.55 greater odds of having suicidal thoughts in a given year than patients who did not experience poverty. Conclusion: Poverty may put Hispanic patients at greater risk for suicidal thoughts even when they are already receiving treatment for psychiatric conditions. NLP appears to be a promising approach for categorizing free-text information on social circumstances affecting suicidality in clinical settings.

Employee attitudes toward suicide prevention and Counseling on Access to Lethal Means: initial findings from an academic medical center implementing the Zero Suicide framework.

Introduction: Zero Suicide is a strategic framework designed to transform a healthcare system's suicide prevention activities. In 2020, University of Utah Health launched a Zero Suicide program and Counseling on Access to Lethal Means (CALM) training for its employees. In 2022, the healthcare system surveyed its workforce's attitudes toward suicide prevention and CALM. We sought to evaluate employees' attitudes and behaviors toward suicide prevention and CALM training following the launch of the Zero Suicide program. Methods: A Zero Suicide Workforce Survey was administered online through REDCap to all University of Utah Health employees. The analytic sample included 3,345 respondents. We used two-portion z-tests to compare the proportions of respondents who (1) completed CALM training and (2) did not yet complete the CALM training because they felt it was irrelevant to their position by different employee characteristics. Results: More than half of the respondents in the analytic sample were directly interacting with patients who may be at risk for suicide (57.6%). About 8.4% of the respondents had completed CALM training. Among those who had not yet completed CALM training, 9.5% indicated they did not think CALM was relevant to their job. Respondents knowledgeable about warning signs for suicide and respondents who were confident in their ability to respond when suspecting elevated suicide risk were significantly more likely to complete CALM training. Discussion: This evaluation provides important insights from the workforce of a large academic medical center implementing a Zero Suicide program, including insights on opportunities for improving program implementation and evaluation.

Identifying Rare Circumstances Preceding Female Firearm Suicides: Validating A Large Language Model Approach.

BACKGROUND: Firearm suicide has been more prevalent among males, but age-adjusted female firearm suicide rates increased by 20% from 2010 to 2020, outpacing the rate increase among males by about 8 percentage points, and female firearm suicide may have different contributing circumstances. In the United States, the National Violent Death Reporting System (NVDRS) is a comprehensive source of data on violent deaths and includes unstructured incident narrative reports from coroners or medical examiners and law enforcement. Conventional natural language processing approaches have been used to identify common circumstances preceding female firearm suicide deaths but failed to identify rarer circumstances due to insufficient training data. OBJECTIVE: This study aimed to leverage a large language model approach to identify infrequent circumstances preceding female firearm suicide in the unstructured coroners or medical examiners and law enforcement narrative reports available in the NVDRS. METHODS: We used the narrative reports of 1462 female firearm suicide decedents in the NVDRS from 2014 to 2018. The reports were written in English. We coded 9 infrequent circumstances preceding female firearm suicides. We experimented with predicting those circumstances by leveraging a large language model approach in a yes/no question-answer format. We measured the prediction accuracy with F1-score (ranging from 0 to 1). F1-score is the harmonic mean of precision (positive predictive value) and recall (true positive rate or sensitivity). RESULTS: Our large language model outperformed a conventional support vector machine-supervised machine learning approach by a wide margin. Compared to the support vector machine model, which had F1-scores less than 0.2 for most infrequent circumstances, our large language model approach achieved an F1-score of over 0.6 for 4 circumstances and 0.8 for 2 circumstances. CONCLUSIONS: The use of a large language model approach shows promise. Researchers interested in using natural language processing to identify infrequent circumstances in narrative report data may benefit from large language models.

Characterizing Female Firearm Suicide Circumstances: A Natural Language Processing and Machine Learning Approach.

INTRODUCTION: Since 2005, female firearm suicide rates increased by 34%, outpacing the rise in male firearm suicide rates over the same period. The objective of this study was to develop and evaluate a natural language processing pipeline to identify a select set of common and important circumstances preceding female firearm suicide from coroner/medical examiner and law enforcement narratives. METHODS: Unstructured information from coroner/medical examiner and law enforcement narratives were manually coded for 1,462 randomly selected cases from the National Violent Death Reporting System. Decedents were included from 40 states and Puerto Rico from 2014 to 2018. Naive Bayes, Random Forest, Support Vector Machine, and Gradient Boosting classifier models were tuned using 5-fold cross-validation. Model performance was assessed using sensitivity, specificity, positive predictive value, F1, and other metrics. Analyses were conducted from February to November 2022. RESULTS: The natural language processing pipeline performed well in identifying recent interpersonal disputes, problems with intimate partners, acute/chronic pain, and intimate partners and immediate family at the scene. For example, the Support Vector Machine model had a mean of 98.1% specificity and 90.5% positive predictive value in classifying a recent interpersonal dispute before suicide. The Gradient Boosting model had a mean of 98.7% specificity and 93.2% positive predictive value in classifying a recent interpersonal dispute before suicide. CONCLUSIONS: This study developed a natural language processing pipeline to classify 5 female firearm suicide antecedents using narrative reports from the National Violent Death Reporting System, which may improve the examination of these circumstances. Practitioners and researchers should weigh the efficiency of natural language processing pipeline development against conventional text mining and manual review.

Critical gaps in understanding firearm suicide in Hispanic communities: demographics, mental health, and access to care.

Suicide rates increased by 26.7% among Hispanics from 2015 to 2020, driven at least in part by highly lethal firearm suicide deaths. However, there are critical gaps in characterizing firearm suicide risks and prevention opportunities in Hispanic communities. We examined Hispanic adult firearm suicide decedents reported through the National Violent Death Reporting System from 2013-2019, focusing on demographic characteristics, firearm choices, suicidal thoughts/behaviors, mental health, and mental health treatment, compared with non-Hispanic adult firearm suicide decedents. Only 13.8% of Hispanic firearm suicide decedents were known to be undergoing treatment for a mental health or substance use problem prior to death, compared to 18.8% of non-Hispanic firearm suicide decedents. On average, Hispanic firearm suicide decedents were significantly less likely than non-Hispanic firearm suicide decedents known to have been treated for a mental health or substance use problem. These results may underscore the critical need for public health agencies and policymakers to promote initiatives integrating mental health screening into medical care, reducing mental health stigma among Hispanics, and expanding mental health treatment capacity in Hispanic communities.

We examined Hispanic adult firearm suicide decedents reported through the National Violent Death Reporting System from 2013­2019, focusing on demographic characteristics, firearm choices, suicidal thoughts and behaviors, mental health, and mental health treatment, compared with non-Hispanic adult firearm suicide decedents. We found key differences in demographic characteristics, firearm choices, and known history of suicidal thoughts and behaviors, mental ill health, and mental health treatment between Hispanic and non-Hispanic adult firearm suicide decedents. One key finding from this study was that Hispanic adult firearm suicide decedents were significantly less likely than non-Hispanic adult firearm suicide decedents known to be undergoing treatment for mental health or substance use problems prior to death. Additionally, compared with non-Hispanic decedents, Hispanic decedents were more likely to have a known history of suicidal thoughts/plans and suicide attempts. Handguns were used in three-fourths (74.9%) of non-Hispanic firearm suicide deaths but more than 8 in 10 (81.9%) Hispanic firearm suicide deaths. These results may indicate opportunities for public health agencies and policymakers to promote initiatives integrating mental health screening into primary medical care, reducing mental health stigma among Hispanics, and expanding mental health treatment capacity in Hispanic communities.

A Machine Learning Approach to Predicting Higher COVID-19 Care Burden in the Primary Care Safety Net: Hispanic Patient Population Size a Key Factor.

Introduction: The federal government legislated supplemental funding to support community health centers (CHCs) in response to the COVID-19 pandemic. Supplemental funding included standard base payments and adjustments for the number of total and uninsured patients served before the pandemic. However, not all CHCs share similar patient population characteristics and health risks. Objective: To use machine learning to identify the most important factors for predicting whether CHCs had a high burden of patients diagnosed with COVID-19 during the first year of the pandemic. Methods: Our analytic sample included data from 1342 CHCs across the 50 states and D.C. in 2020. We trained a random forest (RF) classifier model, incorporating 5-fold cross-validation to validate the RF model while optimizing the model's hyperparameters. Final performance metrics were calculated following the application of the model that had the best fit to the held-out test set. Results: CHCs with a high burden of COVID-19 had an average of 65.3 patients diagnosed with COVID-19 per 1000 patients in 2020. Our RF model had 80.9% accuracy, 80.1% precision, 25.0% sensitivity, and 98.1% specificity. The percentage of Hispanic patients served in 2020 was the most important feature for predicting whether CHCs had high COVID-19 burden. Conclusions: Findings from our RF model suggest patient population race and ethnicity characteristics were most important for predicting whether CHCs had a high burden of patients diagnosed with COVID-19 in 2020, though sensitivity was low. Enhanced support for CHCs serving large Hispanic patient populations may have an impact on addressing future COVID-19 waves.

Examining the policy effects of Arizona's 2016 pre-emption law on firearm suicide rates in the greater Tucson area: an observational study.

OBJECTIVE: In 2016, Arizona enacted SB 1487 to nullify Tucson's ordinance permitting the municipality to destroy confiscated and forfeited firearms and instead require the firearms to be resold to the public through an auctioneer. Our objective was to examine whether firearm suicide rates increased in Pima County (greater Tucson area) relative to other Arizona counties following the enactment of Arizona's 2016 pre-emption law. DESIGN: An observational study of a natural policy experiment. We used a difference-in-differences approach to estimate the effects of Arizona enacting SB 1487 on firearm suicide rates in Pima County. Our statistical analyses adjusted for county-level differences in population demographics (age, gender and race) and unemployment rates, as well as a proxy for firearm availability and mental health professional shortage area status. SETTING: 9 Arizona counties from 2014 to 2019. PARTICIPANTS: A policy group was constructed using Pima County (Tucson area) observations. A comparison group was created using data from eight other Arizona counties. 54 county-year observations were analysed. INTERVENTION: SB 1487, which pre-empted Tucson law and allowed firearms that were seized/surrendered to law enforcement to be recirculated instead of destroyed. OUTCOMES AND MEASURES: Annual rates of firearm and non-firearm suicides per 100 000 persons extracted from the Centers for Disease Control and Prevention WONDER system. RESULTS: Over the study period, comparison group counties had an average of 14.87 firearm suicides per 100 000 persons per year, compared with 11.56 firearm suicides per 100 000 persons per year in Pima County. A 1.13 increase in Pima County's firearm suicides per 100 000 persons coincided with the enactment of Arizona's 2016 pre-emption law, relative to comparison group counties over the same period. CONCLUSIONS: SB 1487 was associated with higher firearm suicide rates in Pima County relative to other areas not targeted by the law, assuming fewer firearms were destroyed and more firearms re-entered the greater Tucson area through 2019.

Impact of state-level training requirements for medical providers on receipt of preventive oral health services for young children enrolled in Medicaid.

OBJECTIVES: Young children enrolled in Medicaid make few dental visits and have high rates of tooth decay. To improve access to care, state Medicaid programs have enacted policies encouraging nondental providers to deliver preventive oral health services (POHS) in medical offices. Policies vary by state, with some states requiring medical providers to obtain training prior to delivering POHS. Our objective was to test whether these training requirements were associated with higher rates of POHS for Medicaid-enrolled children <6 years. METHODS: This study took advantage of a natural experiment in which policy enactment occurred across states at different times. We used Medicaid Analytic eXtract enrollment and claims data, public policy data, and Area Health Resource Files data. We examined an unweighted sample of 8,711,192 (45,107,240 weighted) Medicaid-enrolled children <6 years in 38 states from 2006 to 2014. Multivariable logistic regression models estimated the odds a child received POHS in a calendar year. Results are presented as adjusted probabilities. RESULTS: Five or more years after policy enactment, the probability of a child receiving POHS in medical offices was 10.7 percent in states with training requirements compared to 5.0 percent in states without training requirements (P = 0.01). Findings were similar when receipt of any POHS in medical or dental offices was examined 5 or more years post-policy-enactment (requirement = 42.5 percent, no requirement = 33.6 percent, P < 0.001). CONCLUSIONS: Medicaid policies increased young children's receipt of POHS and at higher rates in states that required POHS training. These results suggest that oral health training for nondental practitioners is a key component of policy success.

Preventing Adolescent and Young Adult Suicide: Do States With Greater Mental Health Treatment Capacity Have Lower Suicide Rates?

PURPOSE: Youth suicide is increasing at a significant rate and is the second leading cause of death for adolescents. There is an urgent public health need to address the youth suicide. The objective of this study is to determine whether adolescents and young adults residing in states with greater mental health treatment capacity exhibited lower suicide rates than states with less treatment capacity. METHODS: We conducted a state-level analysis of mental health treatment capacity and suicide outcomes for adolescents and young adults aged 10-24 spanning 2002-2017 using data from Centers for Disease Control and Prevention, U.S. Bureau of Labor Statistics, Federal Bureau of Investigation, and other sources. Multivariable linear fixed-effects regression models tested the relationships among mental health treatment capacity and the total suicide, firearm suicide, and nonfirearm suicide rates per 100,000 persons aged 10-24. RESULTS: We found a statistically significant inverse relationship between nonfirearm suicide and mental health treatment capacity (p = .015). On average, a 10% increase in a state's mental health workforce capacity was associated with a 1.35% relative reduction in the nonfirearm suicide rate for persons aged 10-24. There was no significant relationship between mental health treatment capacity and firearm suicide. CONCLUSIONS: Greater mental health treatment appears to have a protective effect of modest magnitude against nonfirearm suicide among adolescents and young adults. Our findings underscore the importance of state-level efforts to improve mental health interventions and promote mental health awareness. However, firearm regulations may provide greater protective effects against this most lethal method of firearm suicide.

Examining the Relationship Between COVID-19 Prevalence and Depression Care at Community Health Centers: Assessing 2020 Data.

OBJECTIVE: The author examined associations between COVID-19 prevalence at community health centers (CHCs) and the percentage of eligible CHC patients who had ongoing depression care documented in 2020. METHODS: Using 2020 Uniform Data System data, the author analyzed 1,113 CHCs in the 50 U.S. states (representing 26,865,015 total patients). Multivariable linear regression models were used to examine associations between COVID-19 prevalence and the percentage of patients who screened positive for depression and had follow-up depression care documented at CHCs in 2020. RESULTS: On average, each increase of 1 percentage point in COVID-19 prevalence within a CHC patient population was independently associated with a 0.47-percentage point decrease of eligible patients with a follow-up depression care plan documented in 2020. CONCLUSIONS: Findings appear to be consistent with recent evidence indicating disruptions in health care delivery coinciding with the COVID-19 pandemic. This observation is concerning given the history of mental health disparities experienced by patients with lower incomes.

Early Data on Predictors of COVID-19 Treatment Frequency at Community Health Centers.

INTRODUCTION: Federally-funded community health centers (CHCs) serve on the front lines of the COVID-19 pandemic, providing essential COVID-19 testing and care for vulnerable patient populations. Overlooked in the scholarly literature is a description of how different characteristics and vulnerabilities shaped COVID-19 care delivery at CHCs in the first year of the pandemic. Our research objective was to identify organization- and state-level factors associated with more or fewer COVID-19 care and testing visits at CHCs in 2020. METHODS: Multilevel random intercept regression models examined associations among organization and state-level predictor variables and the frequency of COVID-19 care and testing visits at CHCs in 2020. The study sample included 1267 CHCs across the 50 states and the District of Columbia. RESULTS: The average CHC provided 932 patient visits for COVID-19-related care in 2020. Yet, the CHC's role in delivering COVID-19 services proved as diverse as the populations and localities CHCs serve. For example, after adjusting for other factors, each percentage-point increase in a CHC's Hispanic patient population size was associated with a 1.3% increase in the frequency of patient visits for COVID-19 care in 2020 (P < .001). Serving a predominantly rural patient population was associated with providing significantly fewer COVID-19-related care visits (P = .002). Operating in a state that enacted a mask-wearing policy in 2020 was associated with a 26.2% lower frequency of COVID-19 testing visits at CHCs in 2020, compared to CHCs operating in states without mask-wearing policies (P = .055). CONCLUSIONS: In response to the pandemic, the federal government legislated funding to help CHCs address challenges associated with COVID-19 and provide services to medically-underserved patient populations. Policymakers will likely need to provide additional support to help CHCs address population-specific vulnerabilities affecting COVID-19 care and testing delivery, especially as highly contagious COVID-19 variants proliferate (eg, Delta and Omicron).

Impact of the Affordable Care Act Medicaid expansion on oral surgery delivery at community health centers: an observational study.

BACKGROUND: Unmet oral health needs routinely affect low-income communities. Lower-income adults suffer a disproportionate share of dental disease and often cannot access necessary oral surgery services. The Affordable Care Act (ACA) Medicaid expansion created new financial opportunities for community health centers (CHCs) to provide mission-relevant services in low-income areas. However, little is understood in the literature about how the ACA Medicaid expansion impacted oral surgery delivery at CHCs. Using a large sample of CHCs, we examined whether the ACA Medicaid expansion increased the likelihood of oral surgery delivery at expansion-state CHCs compared to non-expansion-state CHCs. METHODS: Exploiting a natural experiment, we estimated Poisson regression models examining the effects of the Medicaid expansion on the likelihood of oral surgery delivery at expansion-state CHCs relative to non-expansion-state CHCs. We merged data from multiple sources spanning 2012-2017. The analytic sample included 2054 CHC-year observations. RESULTS: Compared to the year prior to expansion, expansion-state CHCs were 13.5% less likely than non-expansion-state CHCs to provide additional oral surgery services in 2016 (IRR = 0.865; P = 0.06) and 14.7% less likely in 2017 (IRR = 0.853; P = 0.02). All else equal, and relative to non-expansion-state CHCs, expansion-state CHCs included in the analytic sample were 8.7% less likely to provide oral surgery services in all post-expansion years pooled together (IRR = 0.913; P = 0.01). CONCLUSIONS: Medicaid expansions can provide CHCs with opportunities to expand their patient revenue and services. However, whether because of known dental treatment capacity limitations, new competition, or coordination with other providers, expansion-state CHCs in our study sample were less likely to provide oral surgery services on the margin relative to non-expansion-state CHCs following Medicaid expansion.

Community Health Centers Maintained Initial Increases in Medicaid Covered Adult Patients at 5-Years Post-Medicaid-Expansion.

The Affordable Care Act (ACA) Medicaid expansion created new financial opportunities for community health centers (CHCs) providing primary care in medically-underserved communities. However, beyond evidence of initial policy effects, little is understood in the scholarly literature about whether the ACA Medicaid expansion affected longer-lasting changes in CHC patient insurance mix. This study's objective was to examine whether the ACA Medicaid expansion was associated with lasting increases in the annual percentage of adult CHC patients covered by Medicaid and decreases in the annual percentage of uninsured adult CHC patients at expansion-state CHCs, compared to non-expansion-state CHCs. This observational study examined 5353 CHC-year observations from 2012 to 2018 using Uniform Data System data and other national data sources. Using a 2-way fixed-effects multivariable regression approach and marginal analysis, intermediate-term policy effects of the Medicaid expansion on annual CHC patient coverage outcomes were estimated. By 5-years post-expansion, the Medicaid expansion was associated with an overall average increase of 11.7 percentage points in the percentage of adult patients with Medicaid coverage at expansion-state CHCs, compared to non-expansion-state CHCs. Among expansion-state CHCs, 39.8% of adult patients were predicted to have Medicaid coverage 5-years post-expansion, compared to 19.0% of non-expansion-state adult CHC patients. A state's decision to expand Medicaid was similarly associated with decreases in the annual percentage of uninsured adult CHC patients. Primary care operations at CHCs critically depend on patient Medicaid revenue. These findings suggest the ACA Medicaid expansion may provide longer-term financial security for expansion-state CHCs, which maintain increases in Medicaid-covered adult patients even 5-years post-expansion. However, these financial securities may be jeopardized should the ACA be ruled unconstitutional in 2021, a year after CHCs experienced new uncertainties caused by COVID-19.

The Firearm Suicide Crisis: Physicians Can Make a Difference.

Firearm suicide receives relatively little public attention in the United States, however, the United States is in the midst of a firearm suicide crisis. Most suicides are completed using a firearm. The age-adjusted firearm suicide rate increased 22.6% from 2005 to 2017, and globally the US firearm suicide rate is 8 times higher than the average firearm suicide rate of 22 other developed countries. The debate over how to solve the firearm suicide epidemic tends to focus on reducing the firearm supply or increasing access to behavioral health treatment. Ineffectual federal firearm control policies and inadequate behavioral health treatment access has heightened the need for primary care physicians to play a more meaningful role in firearm suicide prevention. We offer suggestions for how individual physicians and the collective medical community can take action to reduce mortality arising from firearm suicide and firearm deaths.