Suicide typologies among Medicaid beneficiaries, North Carolina 2014-2017.

BACKGROUND: There is a well-established need for population-based screening strategies to identify people at risk of suicide. Because only about half of suicide decedents are ever diagnosed with a behavioral health condition, it may be necessary for providers to consider life circumstances that may also put individuals at risk. This study described the alignment of medical diagnoses with life circumstances by identifying suicide typologies among decedents. Demographics, stressful life events, suicidal behavior, perceived and diagnosed health problems, and suicide method contributed to the typologies. METHODS: This study linked North Carolina Medicaid and North Carolina Violent Death Reporting System (NC-VDRS) data for analysis in 2020. For suicide decedents from 2014 to 2017 aged 25-54 years, we analyzed 12 indicators of life circumstances from NC-VDRS and 6 indicators from Medicaid claims, using a latent class model. Separate models were developed for men and women. RESULTS: Most decedents were White (88.3%), with a median age of 41, and over 70% had a health care visit in the 90 days prior to suicide. Two typologies were identified in both males (n = 175) and females (n = 153). Both typologies had similar profiles of life circumstances, but one had high probabilities of diagnosed behavioral health conditions (45% of men, 71% of women), compared to low probabilities in the other (55% of men, 29% of women). Black beneficiaries and men who died by firearm were over-represented in the less-diagnosed class, though estimates were imprecise (odds ratio for Black men: 3.1, 95% confidence interval: 0.8, 12.4; odds ratio for Black women: 5.0, 95% confidence interval: 0.9, 31.2; odds ratio for male firearm decedents: 1.6, 95% confidence interval: 0.7, 3.4). CONCLUSIONS: Nearly half of suicide decedents have a typology characterized by low probability of diagnosis of behavioral health conditions. Suicide screening could likely be enhanced using improved indicators of lived experience and behavioral health.

Association Between Medical Diagnoses and Suicide in a Medicaid Beneficiary Population, North Carolina 2014-2017.

BACKGROUND: Firearms are used in about half of U.S. suicides. This study investigated how various medical diagnoses are associated with firearm and nonfirearm suicide. METHODS: We used a case-control design including n = 691 North Carolina Medicaid beneficiaries who died from suicide between 1 January 2014 and 31 December 2017 as cases. We selected a total of n = 68,682 controls (~1:100 case-control ratio from North Carolina Medicaid member files using incidence density sampling methods). We linked Medicaid claims to the North Carolina Violent Death Reporting System to ascertain suicide and means (firearm or nonfirearm). We matched cases and controls on number of months covered by Medicaid over the past 36 months. Analyses adjusted for sex, race, age, Supplemental Security Income status, the Charlson Comorbidity Index, and frequency of health care encounters. RESULTS: The case-control odds ratios for any mental health disorder were 4.2 (95% confidence interval [CI]: 3.3, 5.2) for nonfirearm suicide and 2.2 (95% CI: 1.7, 2.9) for firearm suicide. There was effect measure modification by sex and race. Behavioral health diagnoses were more strongly associated with nonfirearm suicides than firearm suicide in men but did not differ substantially in women. The association of mental health and substance use diagnoses with suicides appeared to be weaker in Blacks (vs. non-Blacks), but the estimates were imprecise. CONCLUSION: Behavioral health diagnoses are important indicators of risk of suicide. However, these associations differ by means of suicide and sex, and associations for firearm-related suicide are weaker in men than women.

Characterizing Opioid Overdoses Using Emergency Medical Services Data : A Case Definition Algorithm Enhanced by Machine Learning.

OBJECTIVES: Tracking nonfatal overdoses in the escalating opioid overdose epidemic is important but challenging. The objective of this study was to create an innovative case definition of opioid overdose in North Carolina emergency medical services (EMS) data, with flexible methodology for application to other states' data. METHODS: This study used de-identified North Carolina EMS encounter data from 2010-2015 for patients aged >12 years to develop a case definition of opioid overdose using an expert knowledge, rule-based algorithm reflecting whether key variables identified drug use/poisoning or overdose or whether the patient received naloxone. We text mined EMS narratives and applied a machine-learning classification tree model to the text to predict cases of opioid overdose. We trained models on the basis of whether the chief concern identified opioid overdose. RESULTS: Using a random sample from the data, we found the positive predictive value of this case definition to be 90.0%, as compared with 82.7% using a previously published case definition. Using our case definition, the number of unresponsive opioid overdoses increased from 3412 in 2010 to 7194 in 2015. The corresponding monthly rate increased by a factor of 1.7 from January 2010 (3.0 per 1000 encounters; n = 261 encounters) to December 2015 (5.1 per 1000 encounters; n = 622 encounters). Among EMS responses for unresponsive opioid overdose, the prevalence of naloxone use was 83%. CONCLUSIONS: This study demonstrates the potential for using machine learning in combination with a more traditional substantive knowledge algorithm-based approach to create a case definition for opioid overdose in EMS data.

State firearm laws, race and law enforcement-related deaths in 16 US states: 2010-2016.

The aim of this study was to assess the association between state firearm legislation and law enforcement-related deaths (LEDs) and its modification by race. We used secondary data from an ecological cohort of 16 states (2010 to 2016), using the National Violent Death Reporting System (NVDRS), the State Firearm Law Database and additional public sources. Poisson regression with generalised estimating equations and inverse probability of exposure weights to account for time-varying confounding were used to quantify the association. LEDs were also disaggregated by race (Black vs non-Black). A total of 1593 LEDs took place during the 6-year study period. After adjusting for confounders, the IRR among non-Blacks was 0.48 (95% CI 0.26 to 0.89) and 1.53 (95% CI 0.93 to 2.54) among Blacks. Our findings highlight the fact that increased firearm provisions may decrease rates of LED among non-Black American individuals-an association not observed among Black Americans.

Estimating the association between mental health disorders and suicide: a review of common sources of bias and challenges and opportunities for US-based research.

PURPOSE OF REVIEW: The purpose of this review is to 1) illuminate prevalent methodological approaches and estimates of association between mental health diagnoses and suicide from the meta-analytic literature; 2) discuss key internal and external validity concerns with these estimates; and 3) highlight some of the unique attributes and challenges in US-based suicide research and opportunities to move the evidence base forward. RECENT FINDINGS: Globally, there is considerable variability in measures of association between mental health disorders and suicide and a growing debate over methodological approaches to this research. A high suicide incidence makes the US an outlier, and the decentralized nature of US administrative data poses a unique challenge to data linkage that could otherwise advance this research. SUMMARY: We offer methodological considerations for future research and discuss opportunities made possible by the recent expansion of the US National Violent Death Reporting System to a nationwide registry.

Association of State Firearm Legislation With Female Intimate Partner Homicide.

INTRODUCTION: The aim of this study was to assess the association between state firearm legislation and female intimate partner homicide. METHODS: In 2017, the authors conducted a secondary data analysis of 16 states from 2010 to 2014, using data from the National Violent Death Reporting System, the State Firearm Law Database, and additional public sources. Poisson regression analyses quantified the association between the number of state restrictive firearm legislative provisions and the female population-based intimate partner homicide rate. For etiologic reasons, intimate partner homicide was disaggregated into homicide-suicide (intimate partner homicide followed by perpetrator suicide) and homicide-only intimate partner homicide (intimate partner homicide in the absence of perpetrator suicide). RESULTS: There were 1,693 female intimate partner homicide deaths in the 16 states during 2010-2014; 67% were homicide-only intimate partner homicide. The number of state-level legislative provisions related to firearm restrictions ranged from four (Alaska) to 95 (Massachusetts). The intimate partner homicide rate in states with zero to 39 provisions was 1.16 per 100,000 person years (95% CI=1.10, 1.22) and in states with >40 provisions was 0.68 per 100,000 person years (95% CI=0.61, 0.72). The incidence of female intimate partner homicide was 56% lower in states with ≥40 legislative provisions (adjusted incidence rate ratio=0.44, 95% CI=0.28, 0.68), relative to states with zero to 39 provisions. This protective association was stronger for homicide-only intimate partner homicide than homicide-suicide intimate partner homicide. CONCLUSIONS: More state-level restrictive firearm legislation is associated with a lower rate of female intimate partner homicides.