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

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

COVID-19 community spread and consequences for prison case rates

Background COVID-19 and mass incarceration are closely intertwined with prisons having COVID-19 case rates much higher than the general population. COVID-19 has highlighted the relationship between incarceration and health, but prior work has not explored how COVID-19 spread in communities have influenced case rates in prisons. Our objective was to understand the relationship between COVID-19 case rates in the general population and prisons located in the same county. Methods Using North Carolina’s (NC) Department of Health and Human Services data, this analysis examines all COVID-19 tests conducted in NC from June-August 2020. Using interrupted time series analysis, we assessed the relationship between substantial community spread (50/100,000 detected in the last seven days) and active COVID-19 case rates (cases detected in the past 14 days/100,000) within prisons. Results From June-August 2020, NC ordered 29,605 tests from prisons and detected 1,639 cases. The mean case rates were 215 and 427 per 100,000 in the general and incarcerated population, respectively. Once counties reached substantial COVID-19 spread, the COVID-19 prison case rate increased by 118.55 cases per 100,000 (95% CI: -3.71, 240.81). Conclusions Community COVID-19 spread contributes to COVID-19 case rates in prisons. In counties with prisons, community spread should be closely monitored. Stringent measures within prisons (e.g., vaccination) and decarceration should be prioritized to prevent COVID-19 outbreaks

Impact of a community-based naloxone distribution program on opioid overdose death rates

Background: In August 2013, a naloxone distribution program was implemented in North Carolina (NC). This study evaluated that program by quantifying the association between the program and county-level opioid overdose death (OOD) rates and conducting a cost-benefit analysis. Methods: One-group pre-post design. Data included annual county-level counts of naloxone kits distributed from 2013 to 2016 and mortality data from 2000-2016. We used generalized estimating equations to estimate the association between cumulative rates of naloxone kits distributed and annual OOD rates. Costs included naloxone kit purchases and distribution costs; benefits were quantified as OODs avoided and monetized using a conservative value of a life. Results: The rate of OOD in counties with 1–100 cumulative naloxone kits distributed per 100,000 population was 0.90 times (95% CI: 0.78, 1.04) that of counties that had not received kits. In counties that received >100 cumulative kits per 100,000 population, the OOD rate was 0.88 times (95% CI: 0.76, 1.02) that of counties that had not received kits. By December 2016, an estimated 352 NC deaths were avoided by naloxone distribution (95% CI: 189, 580). On average, for every dollar spent on the program, there was $2742 of benefit due to OODs avoided (95$1,237, $4882). Conclusions: Our estimates suggest that community-based naloxone distribution is associated with lower OOD rates. The program generated substantial societal benefits due to averted OODs. States and communities should continue to support efforts to increase naloxone access, which may include reducing legal, financial, and normative barriers

Health care use among latinx children after 2017 executive actions on immigration

BACKGROUND: US immigration policy changes may affect health care use among Latinx children. We hypothesized that January 2017 restrictive immigration executive actions would lead to decreased health care use among Latinx children. METHODS: We used controlled interrupted time series to estimate the effect of executive actions on outpatient cancellation or no-show rates from October 2016 to March 2017 (“immigration action period”) among Latinx children in 4 health care systems in North Carolina. We included control groups of (1) non-Latinx children and (2) Latinx children from the same period in the previous year (“control period”) to account for natural trends such as seasonality. RESULTS: In the immigration action period, 114 627 children contributed 314 092 appointments. In the control period, 107 657 children contributed 295 993 appointments. Relative to the control period, there was an immediate 5.7% (95% confidence interval [CI]: 0.40%-10.9%) decrease in cancellation rates among all Latinx children, but no sustained change in trend of cancellations and no change in no-show rates after executive immigration actions. Among uninsured Latinx children, there was an immediate 12.7% (95% CI: 2.3%-23.1%) decrease in cancellations; however, cancellations then increased by 2.4% (95% CI: 0.89%-3.9%) per week after immigration actions, an absolute increase of 15.5 cancellations per 100 appointments made. CONCLUSIONS: There was a sustained increase in cancellations among uninsured Latinx children after immigration actions, suggesting decreased health care use among uninsured Latinx children. Continued monitoring of effects of immigration policy on child health is needed, along with measures to ensure that all children receive necessary health care

State Medical Board Policy and Opioid Prescribing: A Controlled Interrupted Time Series

Introduction: In March 2016, the Centers for Disease Control and Prevention issued opioid prescribing guidelines for chronic noncancer pain. In response, in April 2016, the North Carolina Medical Board launched the Safe Opioid Prescribing Initiative, an investigative program intended to limit the overprescribing of opioids. This study focuses on the association of the Safe Opioid Prescribing Initiative with immediate and sustained changes in opioid prescribing among all patients who received opioid and opioid discontinuation and tapering among patients who received high-dose (>90 milligrams of morphine equivalents), long-term (>90 days) opioid therapy. Methods: Controlled and single interrupted time series analysis of opioid prescribing outcomes before and after the implementation of Safe Opioid Prescribing Initiative was conducted using deidentified data from the North Carolina Controlled Substances Reporting System from January 2010 through March 2017. Analysis was conducted in 2019–2020. Results: In an average study month, 513,717 patients, including patients who received 47,842 high-dose, long-term opioid therapy, received 660,912 opioid prescriptions at 1.3 prescriptions per patient. There was a 0.52% absolute decline (95% CI= −0.87, −0.19) in patients receiving opioid prescriptions in the month after Safe Opioid Prescribing Initiative implementation. Abrupt discontinuation, rapid tapering, and gradual tapering of opioids among patients who received high-dose, long-term opioid therapy increased by 1% (95% CI= −0.22, 2.23), 2.2% (95% CI=0.91, 3.47), and 1.3% (95% CI=0.96, 1.57), respectively, in the month after Safe Opioid Prescribing Initiative implementation. Conclusions: Although Safe Opioid Prescribing Initiative implementation was associated with an immediate decline in overall opioid prescribing, it was also associated with an unintended immediate increase in discontinuations and rapid tapering among patients who received high-dose, long-term opioid therapy. Better policy communication and prescriber education regarding opioid tapering best practices may help mitigate unintended consequences of statewide policies

Association of Restrictive Housing During Incarceration With Mortality After Release

Importance: Restrictive housing, otherwise known as solitary confinement, during incarceration is associated with poor health outcomes. Objective: To characterize the association of restrictive housing with reincarceration and mortality after release. Design, Setting, and Participants: This retrospective cohort study included 229 274 individuals who were incarcerated and released from the North Carolina prison system from January 2000 to December 2015. Incarceration data were matched with death records from January 2000 to December 2016. Covariates included age, number of prior incarcerations, type of conviction, mental health treatment recommended or received, number of days served in the most recent sentence, sex, and race. Data analysis was conducted from August 2018 to May 2019. Exposures: Restrictive housing during incarceration. Main Outcomes and Measures: Mortality (all-cause, opioid overdose, homicide, and suicide) and reincarceration. Results: From 2000 to 2015, 229 274 people (197 656 [86.2%] men; 92 677 [40.4%] white individuals; median [interquartile range (IQR)] age, 32 years [26-42]), were released 398 158 times from the state prison system in North Carolina. Those who spent time in restrictive housing had a median (IQR) age of 30 (24-38) years and a median (IQR) sentence length of 382 (180-1010) days; 84 272 (90.3%) were men, and 59 482 (63.7%) were nonwhite individuals. During 130 551 of 387 913 incarcerations (33.7%) people were placed in restrictive housing. Compared with individuals who were incarcerated and not placed in restrictive housing, those who spent any time in restrictive housing were more likely to die in the first year after release (hazard ratio [HR], 1.24; 95% CI 1.12-1.38), especially from suicide (HR, 1.78; 95% CI, 1.19-2.67) and homicide (HR, 1.54; 95% CI, 1.24-1.91). They were also more likely to die of an opioid overdose in the first 2 weeks after release (HR, 2.27; 95% CI, 1.16-4.43) and to become reincarcerated (HR, 2.16; 95% CI, 1.99-2.34). Conclusions and Relevance: This study suggests that exposure to restrictive housing is associated with an increased risk of death during community reentry. These findings are important in the context of ongoing debates about the harms of restrictive housing, indicating a need to find alternatives to its use and flagging restrictive housing as an important risk factor during community reentry

Hurricane Florence and suicide mortality in North Carolina: A controlled interrupted time-series analysis

Background Natural disasters are associated with increased mental health disorders and suicidal ideation; however, associations with suicide deaths are not well understood. We explored how Hurricane Florence, which made landfall in September 2018, may have impacted suicide deaths in North Carolina (NC). Methods We used publicly available NC death records data to estimate associations between Hurricane Florence and monthly suicide death rates using a controlled, interrupted time series analysis. Hurricane exposure was determined by using county-level support designations from the Federal Emergency Management Agency. We examined effect modification by sex, age group, and race/ethnicity. Results 8363 suicide deaths occurred between January 2014 and December 2019. The overall suicide death rate in NC between 2014 and 2019 was 15.53 per 100 000 person-years (95% CI 15.20 to 15.87). Post-Hurricane, there was a small, immediate increase in the suicide death rate among exposed counties (0.89/100 000 PY; 95% CI -2.69 to 4.48). Comparing exposed and unexposed counties, there was no sustained post-Hurricane Florence change in suicide death rate trends (0.02/100 000 PY per month; 95% CI -0.33 to 0.38). Relative to 2018, NC experienced a statewide decline in suicides in 2019. An immediate increase in suicide deaths in Hurricane-affected counties versus Hurricane-unaffected counties was observed among women, people under age 65 and non-Hispanic black individuals, but there was no sustained change in the months after Hurricane Florence. Conclusions Although results did not indicate a strong post-Hurricane Florence impact on suicide rates, subgroup analysis suggests differential impacts of Hurricane Florence on several groups, warranting future follow-up

Innovations in suicide prevention research (INSPIRE): a protocol for a population-based case–control study

Background Suicide deaths have been increasing for the past 20 years in the USA resulting in 45 979 deaths in 2020, a 29% increase since 1999. Lack of data linkage between entities with potential to implement large suicide prevention initiatives (health insurers, health institutions and corrections) is a barrier to developing an integrated framework for suicide prevention. Objectives Data linkage between death records and several large administrative datasets to (1) estimate associations between risk factors and suicide outcomes, (2) develop predictive algorithms and (3) establish long-term data linkage workflow to ensure ongoing suicide surveillance. Methods We will combine six data sources from North Carolina, the 10th most populous state in the USA, from 2006 onward, including death certificate records, violent deaths reporting system, large private health insurance claims data, Medicaid claims data, University of North Carolina electronic health records and data on justice involved individuals released from incarceration. We will determine the incidence of death from suicide, suicide attempts and ideation in the four subpopulations to establish benchmarks. We will use a nested case–control design with incidence density-matched population-based controls to (1) identify short-term and long-term risk factors associated with suicide attempts and mortality and (2) develop machine learning-based predictive algorithms to identify individuals at risk of suicide deaths. Discussion We will address gaps from prior studies by establishing an in-depth linked suicide surveillance system integrating multiple large, comprehensive databases that permit establishment of benchmarks, identification of predictors, evaluation of prevention efforts and establishment of long-term surveillance workflow protocols

Development and validation of an electronic health records-based opioid use disorder algorithm by expert clinical adjudication among patients with prescribed opioids

Background: In the US, over 200 lives are lost from opioid overdoses each day. Accurate and prompt diagnosis of opioid use disorders (OUD) may help prevent overdose deaths. However, international classification of disease (ICD) codes for OUD are known to underestimate prevalence, and their specificity and sensitivity are unknown. We developed and validated algorithms to identify OUD in electronic health records (EHR) and examined the validity of OUD ICD codes. Methods: Through four iterations, we developed EHR-based OUD identification algorithms among patients who were prescribed opioids from 2014 to 2017. The algorithms and OUD ICD codes were validated against 169 independent “gold standard” EHR chart reviews conducted by an expert adjudication panel across four healthcare systems. After using 2014–2020 EHR for validating iteration 1, the experts were advised to use 2014–2017 EHR thereafter. Results: Of the 169 EHR charts, 81 (48%) were reviewed by more than one expert and exhibited 85% expert agreement. The experts identified 54 OUD cases. The experts endorsed all 11 OUD criteria from the Diagnostic and Statistical Manual of Mental Disorders-5, including craving (72%), tolerance (65%), withdrawal (56%), and recurrent use in physically hazardous conditions (50%). The OUD ICD codes had 10% sensitivity and 99% specificity, underscoring large underestimation. In comparison our algorithm identified OUD with 23% sensitivity and 98% specificity. Conclusions and relevance: This is the first study to estimate the validity of OUD ICD codes and develop validated EHR-based OUD identification algorithms. This work will inform future research on early intervention and prevention of OUD