Few Prison Systems Release Individual Death Data: Death in Custody Reporting Act Completeness, Speed, and Compliance.

The United States has one of the largest incarcerated populations per capita. Prisons are dangerous environments, with high in-prison and postrelease mortality. The Death in Custody Reporting Acts (DCRAs) of 2000 and 2013 require deaths of people in correctional custody or caused by law enforcement to be reported to the Bureau of Justice Assistance. These deaths must be reported within 3 months of the death and include 10 required fields (eg, age, cause of death). There is no public reporting requirement. Our Third City Mortality project tracks near-real-time data about individual deaths released publicly and prison system metadata, including data completeness and release speed, across (N = 54) US state, federal (N = 2; Bureau of Prisons, Immigration and Customs Enforcement), Washington, District of Columbia, and Puerto Rico prison systems. Twenty-one (38%) systems release no individual death data; 13 systems release incomplete data slower than 1 year; 19 release timely, but incomplete, death data; and only one system (Iowa) releases complete and timely data. Incomplete, untimely, public prison mortality data limit protective community responses and epidemiology.

Intimate partner violence and suicide mortality: a cross-sectional study using machine learning and natural language processing of suicide data from 43 states.

INTRODUCTION: Intimate partner violence (IPV) is associated with suicidal ideation, yet it remains unclear how often IPV precipitates suicide mortality. To overcome limitations with national data, we applied novel methods to: (1) document the prevalence of IPV-related suicide in the USA and (2) identify correlates for IPV-related suicide. METHODS: Using National Violent Death Reporting System data (NVDRS, 2015-2019, n=1 30 550), we recorded IPV circumstances (yes/no) by leveraging prior textual reviews of death narratives and applying a validated natural language processing tool. We could not systematically differentiate IPV perpetration versus victimisation given limited details in NVDRS. Logistic regression compared IPV-related suicides with referent group suicides (no evidence of IPV), stratified by sex. RESULTS: 7.1% of suicides were IPV related (n=9210), most were isolated suicide events (82.8%, n=7625; ie, not homicide suicide). There were higher odds of IPV circumstances when the decedent had civil legal problems (aOR for men: 3.6 (3.3 to 3.9), aOR for women: 2.6 (2.2 to 3.2)), criminal legal problems (aOR men: 2.3 (2.2 to 2.5), aOR for women: 1.7 (1.4 to 2.1)), or used a firearm (aOR men: 1.9 (1.8 to 2.0), aOR for women: 1.9 (1.7 to 2.1)). There were lower odds of IPV circumstances when the decedent had a current mental health problem (aOR men: 0.7 (0.7 to 0.8), aOR for women: 0.7 (0.6 to 0.8)). CONCLUSIONS: IPV circumstances contribute to a notable proportion of suicides. IPV-related suicides are distinct from other suicide deaths. Targeted suicide screening and intervention in IPV settings may be beneficial for prevention.

Tying Overdose Data to Action: North Carolina's Opioid and Substance Use Action Plan Data Dashboard.

From 2000 to 2020, more than 28 000 North Carolina (NC) residents died of drug overdose. In response, NC Department of Health and Human Services worked with community partners to develop an Opioid and Substance Use Action Plan (OSUAP), now in its third iteration. The NC OSUAP data dashboard brings together data on 15 public health indicators and 16 local actions across 8 strategies. We share innovations in design, data structures, user tasks, and visual elements over 5 years of dashboard development and maintenance, with a special focus and supplemental material covering the technical details and techniques that dashboard design and implementation teams may benefit from.

Intimate Partner Violence Circumstances for Fatal Violence in the US.

This cross-sectional study investigates intimate partner violence circumstances associated with violent deaths in the US from 2015 to 2019.

Feasibility of linking violent death decedents to prior-month emergency department visits in North Carolina, 2019-2020.

OBJECTIVE: Linking data between violent death decedents and other sources can provide valuable insight, highlighting opportunities for prevention of violent injury. This study investigated the feasibility of linking North Carolina Violent Death Reporting System (NC-VDRS) records with North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) emergency department (ED) visit data to identify prior-month ED visits among this population. METHODS: NC-VDRS death records from 2019 through 2020 were linked to NC DETECT ED visit data from December 2018 through 2020 using a probabilistic linkage approach. Linkage variables included date of birth, age, sex, zip code and county of residence, date of event (death/ED visit) and mechanism of injury. Potential linkable ED visits were filtered to those occurring in the month prior to death and manually reviewed for validity. Linked records were compared with the NC-VDRS study population to assess linkage performance and generalisability. RESULTS: Among the 4768 violent deaths identified, we linked 1340 NC-VDRS records to at least one ED visit in the month prior to death. A higher proportion of decedents dying in medical facilities (ED/outpatient, hospital inpatient, hospice or nursing/long-term care facility) linked to a prior-month visit (80%) relative to those dying in other locations (12%). When stratified by place of death, linked decedents demographically resembled the overall NC-VDRS study population. CONCLUSIONS: Though resource intensive, an NC-VDRS-to-NC DETECT linkage was successful in identifying prior-month ED visits among violent death decedents. This linkage should be leveraged to further analyse ED utilisation prior to violent death, expanding the knowledge base surrounding prevention opportunities for violent injuries.

Detecting intimate partner violence circumstance for suicide: development and validation of a tool using natural language processing and supervised machine learning in the National Violent Death Reporting System.

BACKGROUND: Intimate partner violence (IPV) victims and perpetrators often report suicidal ideation, yet there is no comprehensive national dataset that allows for an assessment of the connection between IPV and suicide. The National Violent Death Reporting System (NVDRS) captures IPV circumstances for homicide-suicides (<2% of suicides), but not single suicides (suicide unconnected to other violent deaths; >98% of suicides). OBJECTIVE: To facilitate a more comprehensive understanding of the co-occurrence of IPV and suicide, we developed and validated a tool that detects mentions of IPV circumstances (yes/no) for single suicides in NVDRS death narratives. METHODS: We used 10 000 hand-labelled single suicide cases from NVDRS (2010-2018) to train (n=8500) and validate (n=1500) a classification model using supervised machine learning. We used natural language processing to extract relevant information from the death narratives within a concept normalisation framework. We tested numerous models and present performance metrics for the best approach. RESULTS: Our final model had robust sensitivity (0.70), specificity (0.98), precision (0.72) and kappa values (0.69). False positives mostly described other family violence. False negatives used vague and heterogeneous language to describe IPV, and often included abusive suicide threats. IMPLICATIONS: It is possible to detect IPV circumstances among singles suicides in NVDRS, although vague language in death narratives limited our tool's sensitivity. More attention to the role of IPV in suicide is merited both during the initial death investigation processes and subsequent NVDRS reporting. This tool can support future research to inform targeted prevention.

Patient Characteristics Associated with Access to Minimally Invasive Gynecologic Surgery: Changes during the COVID-19 Pandemic.

STUDY OBJECTIVE: To evaluate patient characteristics that affect access to minimally invasive gynecologic surgery (MIGS) subspecialty care and identify changes during the coronavirus disease 2019 pandemic. DESIGN: Retrospective cohort study of patients referred to MIGS from 2014 to 2016 (historic cohort) compared with those referred to MIGS in 2020 (pandemic cohort). Primary outcome was the interval between referral and first appointment. SETTING: Single-institution academic MIGS division. PATIENTS: Historic cohort (n = 1082) and pandemic cohort (n = 770). INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: Demographics and socioeconomic variables (race, ethnicity, language, insurance, employment, and socioeconomic factors by census tract) and distance from hospital were compared between historic and pandemic cohorts with respect to referral interval using the chi-square, Fisher exact tests, and logistic regression. After adjusting for referral indication, being unemployed and living in an area with less population density, less education, and higher percentage of poverty were associated with a referral interval >30 days in the historic cohort. In the pandemic cohort, only unemployment persisted as a covariate associated with prolonged referral interval and new associated variables were primary language other than English (odds ratio, 3.20; 95% confidence interval [CI], 1.60-6.40) and "other" race (odds ratio, 2.22; 95% CI, 1.34-3.68). The odds of waiting >30 days increased by 6% with the addition of 1 demographic risk factor (95% CI, 1.01-1.10) and by 17% for 3 risk factors (95% CI, 1.03-1.34) in the historic cohort whereas no significant intersectionality was identified in the pandemic cohort. Average referral intervals were significantly shorter during the pandemic (31 vs 50 days, p <.01). Telemedicine appointments had a significantly shorter referral interval than in-person appointments (27 vs 47 days, p <.01). Of patients using telemedicine, a greater proportion were non-Hispanic, English speaking, employed, privately insured, and lived further from the hospital (p <.05). CONCLUSION: Time from referral to first appointment at a tertiary-care MIGS practice during the coronavirus disease 2019 pandemic was shorter than that before the pandemic, likely owing to the adoption of telemedicine. Differences in socioeconomic and demographic factors suggest that telemedicine improved access to care and decreased access disparities for many populations, but not for non-English-speaking patients.

Database selection matters: A case study in child restraint use and injury patterns using North Carolina motor vehicle traffic crash report and trauma registry data.

OBJECTIVE: While proper restraint use is protective against motor traffic vehicle crash (MVTC)-associated morbidity and mortality, it is inconsistently measured across health and MVTC data sources. This project addresses this gap by assessing differences in child restraint measures between two North Carolina (NC) datasets and comparing the utility of these sources to evaluate patterns of child restraint use and associated health outcomes. METHODS: We analyzed 2018 NC MVTC and NC Trauma Registry (NCTR) data for children ≤15 years old, both separately and as linked MVTC-NCTR records. We calculated mean and standard deviation for continuous variables and frequency and proportion for categorical variables. Among linked records, we compared reported restraint use and performed age-adjusted logistic regression to estimate associations between restraint use and severe injury. RESULTS: A lower proportion of pediatric MVTC victims were reported as unrestrained in the MVTC (14.7%) versus NCTR (25.8%) data. Among linked MVTC-NCTR records, only 41.3% featured perfect concordance of restraint information between datasets. Among linked records, child restraint was reported for 31.3% of children, while the NCTR data allowed more granular coding of child restraint (30.3% overall), including child booster seat (13.5%), child car seat (8.7%), infant car seat (4.8%), and unrestrained in child car seat (3.4%). Age-adjusted regression analyses of the linked data revealed that lap/shoulder seatbelt use was significantly associated with lower likelihood of severe injury compared to being unrestrained whether informed by MVTC (OR = 0.39; 95% CI: 0.16, 0.93) or NCTR (OR = 0.38; 95% CI: 0.15, 0.96) data. While the association between reported use of a child car seat and severe injury was not statistically significant in the MVTC data (OR = 0.50; 95% CI: 0.19, 1.32), child car seat use reported in the NCTR data revealed a significant association (OR = 0.16; 95% CI: 0.03, 0.93). CONCLUSIONS: Linked crash and trauma center data allow for identifying important patterns of restraint use among pediatric passengers in MVTCs. Dataset-dependent differences in measuring restraint use have critical public health implications and illustrate the importance of careful dataset selection prior to analysis, as the use of different data sources may impact overall study conclusions.

Mental health emergency department visits: An exploration of case definitions in North Carolina.

BACKGROUND: Mental health (MH) disorders comprise a high disease burden and have long-lasting impacts. To improve MH, it is important to define public health MH surveillance. METHODS: We compared MH related definitions using ICD-10-CM codes: The Council of State and Territorial Epidemiologists' (CSTE) surveillance indicators for all MH, mood or depressive, schizophrenic, and drug/alcohol-induced disorders; and North Carolina's (NC) syndromic surveillance system's definition for anxiety/mood/psychotic disorders, and suicide/self-harm. We compared code definitions and frequent codes in 2019 emergency department (ED) data for those age ≥ 10 years. RESULTS: CSTE's definition resulted in over one million MH-related visits (23% of all ED visits) and NC's definitions in 451,807 MH-related visits (9% of all ED visits). Using CSTE's broadest definition, nicotine use was the most common visit type; using NC's definitions, it was major depressive disorder. CONCLUSIONS: Standardizing population-level MH indicators benefits surveillance efforts. Given its prevalence, efforts should focus on documenting MH to improve treatment and prevention.

Exposure to industrial hog operations and gastrointestinal illness in North Carolina, USA.

With 9 million hogs, North Carolina (NC) is the second leading hog producer in the United States. Most hogs are housed at concentrated animal feeding operations (CAFOs), where millions of tons of hog waste can pollute air and water with fecal pathogens that can cause diarrhea, vomiting, and/or nausea (known as acute gastrointestinal illness (AGI)). We used NC's ZIP code-level emergency department (ED) data to calculate rates of AGI ED visits (2016-2019) and swine permit data to estimate hog exposure. Case exposure was estimated as the inverse distances from each hog CAFO to census block centroids, weighting with Gaussian decay and by manure amount per CAFO, then aggregated to ZIP code using population weights. We compared ZIP codes in the upper quartile of hog exposure ("high hog exposed") to those without hog exposure. Using inverse probability of treatment weighting, we created a control with similar demographics to the high hog exposed population and calculated rate ratios using quasi-Poisson models. We examined effect measure modification of rurality and race using adjusted models. In high hog exposed areas compared to areas without hog exposure, we observed a 11% increase (95% CI: 1.06, 1.17) in AGI rate and 21% increase specifically in rural areas (95% CI: 0.98, 1.43). When restricted to rural areas, we found an increased AGI rate among American Indian (RR = 4.29, 95% CI: 3.69, 4.88) and Black (RR = 1.45, 95% CI: 0.98, 1.91) residents. The association was stronger during the week after heavy rain (RR = 1.41, 95% CI: 1.19, 1.62) and in areas with both poultry and swine CAFOs (RR = 1.52, 95% CI: 1.48, 1.57). Residing near CAFOs may increase rates of AGI ED visits. Hog CAFOs are disproportionally built near rural Black and American Indian communities in NC and are associated with increased AGI most strongly in these populations.

Hurricane flooding and acute gastrointestinal illness in North Carolina.

Hurricanes often flood homes and industries, spreading pathogens. Contact with pathogen-contaminated water can result in diarrhea, vomiting, and/or nausea, known collectively as acute gastrointestinal illness (AGI). Hurricanes Matthew and Florence caused record-breaking flooding in North Carolina (NC) in October 2016 and September 2018, respectively. To examine the relationship between hurricane flooding and AGI in NC, we first calculated the percent of each ZIP code flooded after Hurricanes Matthew and Florence. Rates of all-cause AGI emergency department (ED) visits were calculated from NC's ED surveillance system data. Using controlled interrupted time series, we compared AGI ED visit rates during the three weeks after each hurricane in ZIP codes with a third or more of their area flooded to the predicted rates had these hurricanes not occurred, based on AGI 2016-2019 ED trends, and controlling for AGI ED visit rates in unflooded areas. We examined alternative case definitions (bacterial AGI) and effect measure modification by race and age. We observed an 11% increase (rate ratio (RR): 1.11, 95% CI: 1.00, 1.23) in AGI ED visit rates after Hurricanes Matthew and Florence. This effect was particularly strong among American Indian patients and patients aged 65 years and older after Florence and elevated among Black patients for both hurricanes. Florence's effect was more consistent than Matthew's effect, possibly because little rain preceded Florence and heavy rain preceded Matthew. When restricted to bacterial AGI, we found an 85% (RR: 1.85, 95% CI: 1.37, 2.34) increase in AGI ED visit rate after Florence, but no increase after Matthew. Hurricane flooding is associated with an increase in AGI ED visit rate, although the strength of effect may depend on total storm rainfall or antecedent rainfall. American Indians and Black people-historically pushed to less desirable, flood-prone land-may be at higher risk for AGI after storms.

The impact of the COVID-19 pandemic on the utilization of emergency department services for the treatment of injuries.

CONTEXT: The global COVID-19 pandemic has had a major impact on the utilization of healthcare services; however, the impact on population-level emergency department (ED) utilization patterns for the treatment of acute injuries has not been fully characterized. OBJECTIVE: This study examined the frequency of North Carolina (NC) EDs visits for selected injury mechanisms during the first eleven months of the COVID-19 pandemic. METHODS: Data were obtained from the NC Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT), NC's legislatively mandated statewide syndromic surveillance system for the years 2019 and 2020. Frequencies of January - November 2020 NC ED visits were compared to frequencies of 2019 visits for selected injury mechanisms, classified according to International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) injury diagnosis and mechanism codes. RESULTS: In 2020, the total number of injury-related visits declined by 19.5% (N = 651,158) as compared to 2019 (N = 809,095). Visits related to motor vehicle traffic crashes declined by a greater percentage (29%) and falls (19%) declined by a comparable percentage to total injury-related visits. Visits related to assault (15%) and self-harm (10%) declined by smaller percentages. Medication/drug overdose visits increased (10%), the only injury mechanism studied to increase during this period. CONCLUSION: Both ED avoidance and decreased exposures may have contributed to these declines, creating implications for injury morbidity and mortality. Injury outcomes exacerbated by the pandemic should be addressed by timely public health responses.

Re-prioritizing traffic stops to reduce motor vehicle crash outcomes and racial disparities.

BACKGROUND: Law enforcement traffic stops are one of the most common entryways to the US justice system. Conventional frameworks suggest traffic stops promote public safety by reducing dangerous driving practices and non-vehicular crime. Law enforcement agencies have wide latitude in enforcement, including prioritization of stop types: (1) safety (e.g. moving violation) stops, (2) investigatory stops, or (3) economic (regulatory and equipment) stops. In order to prevent traffic crash fatalities and reduce racial disparities, the police department of Fayetteville, North Carolina significantly re-prioritized safety stops. METHODS: Annual traffic stop, motor vehicle crash, and crime data from 2002 to 2016 were combined to examine intervention (2013-2016) effects. Fayetteville was compared against synthetic control agencies built from 8 similar North Carolina agencies by weighted matching on pre-intervention period trends and comparison against post-intervention trends. RESULTS: On average over the intervention period as compared to synthetic controls, Fayetteville increased both the number of safety stops + 121% (95% confidence interval + 17%, + 318%) and the relative proportion of safety stops (+ 47%). Traffic crash and injury outcomes were reduced, including traffic fatalities - 28% (- 64%, + 43%), injurious crashes - 23% (- 49%, + 16%), and total crashes - 13% (- 48%, + 21%). Disparity measures were reduced, including Black percent of traffic stops - 7% (- 9%, - 5%) and Black vs. White traffic stop rate ratio - 21% (- 29%, - 13%). In contrast to the Ferguson Effect hypothesis, the relative de-prioritization of investigatory stops was not associated with an increase in non-traffic crime outcomes, which were reduced or unchanged, including index crimes - 10% (- 25%, + 8%) and violent crimes - 2% (- 33%, + 43%). Confidence intervals were estimated using a different technique and, given small samples, may be asymmetrical. CONCLUSIONS: The re-prioritization of traffic stop types by law enforcement agencies may have positive public health consequences both for motor vehicle injury and racial disparity outcomes while having little impact on non-traffic crime.

How do we assess a racial disparity in health? Distribution, interaction, and interpretation in epidemiological studies.

Identifying the exposures or interventions that exacerbate or ameliorate racial health disparities is one of the fundamental goals of social epidemiology. Introducing an interaction term between race and an exposure into a statistical model is commonly used in the epidemiologic literature to assess racial health disparities and the potential viability of a targeted health intervention. However, researchers may attribute too much authority to the interaction term and inadvertently ignore other salient information regarding the health disparity. In this article, we highlight empirical examples from the literature demonstrating limitations of overreliance on interaction terms in health disparities research; we further suggest approaches for moving beyond interaction terms when assessing these disparities. We promote a comprehensive framework of three guiding questions for disparity investigation, suggesting examination of the group-specific differences in (1) outcome prevalence, (2) exposure prevalence, and (3) effect size. Our framework allows for better assessment of meaningful differences in population health and the resulting implications for interventions, demonstrating that interaction terms alone do not provide sufficient means for determining how disparities arise. The widespread adoption of this more comprehensive approach has the potential to dramatically enhance understanding of the patterning of health and disease and the drivers of health disparities.

Child Maltreatment Surveillance Improvement Opportunities: A Wake County, North Carolina Pilot Project.

BACKGROUND As child maltreatment often occurs in private, child welfare numbers underestimate its true prevalence. Child maltreatment surveillance systems have been used to ascertain more accurate counts of children who experience maltreatment. This manuscript describes the results from a pilot child maltreatment surveillance system in Wake County, North Carolina.METHODS We linked 2010 and 2011 data from 3 sources (Child Protective Services, Raleigh Police Department, and Office of the Chief Medical Examiner) to obtain rates of definite and possible child maltreatment. We separately analyzed emergency department visits from 2010 and 2011 to obtain counts of definite and possible child maltreatment. We then compared the results from the surveillance systems to those obtained from Child Protective Services (CPS) data alone.RESULTS In 2010 and 2011, rates of definite child maltreatment were 11.7 and 11.3 per 1,000 children, respectively, when using the linked data, compared to 10.0 and 9.5 per 1,000 children using CPS data alone. The rates of possible maltreatment were 25.3 and 23.8 per 1,000, respectively. In the 2010 and 2011 emergency department data, there were 68 visits and 84 visits, respectively, that met the case definition for maltreatment.LIMITATIONS While 4 data sources were analyzed, only 3 were linked in the current surveillance system. It is likely that we would have identified more cases of maltreatment had more sources been included.CONCLUSION While the surveillance system identified more children who met the case definition of maltreatment than CPS data alone, the rates of definite child maltreatment were not considerably higher than official reports. Rates of possible child maltreatment were much higher than both the definite case definition and child welfare records. Tracking both definite and possible case definitions and using a variety of data sources provides a more complete picture of child maltreatment in North Carolina.