External Cause Of Injury Codes Research Articles

Risk of Dementia Diagnosis After Injurious Falls in Older Adults

Emerging evidence suggests that mild cognitive impairment, which is a precursor to Alzheimer disease and related dementias (ADRD), places older adults at increased risk for falls. However, the risk that an older adult develops dementia after experiencing a fall is unknown. To determine the risk of new ADRD diagnosis after a fall in older adults. This retrospective cohort study examined Medicare Fee-for-Service data from 2014 to 2015, with follow-up data available for at least 1 year after the index encounter. Participants included adults aged 66 years and older who experienced a traumatic injury that resulted in an emergency department (ED) or inpatient encounter and did not have a preexisting diagnosis of dementia. Data analysis was performed from August 2023 to July 2024. Experiencing a fall compared with other mechanisms of injury, defined by International Classification of Diseases, Ninth Revision (ICD-9) and ICD-10 external cause of injury codes. The hazard of new ADRD diagnosis within 1 year of a fall, assessed by performing a Cox multivariable competing risk model that controlled for potential confounders while accounting for the competing risk of death. The study included 2 453 655 older adult patients who experienced a traumatic injury; 1 522 656 (62.1%) were female; 124 396 (5.1%) were Black and 2 232 102 (91.0%) were White; and the mean (SD) age was 78.1 (8.1) years. The mechanism of injury was a fall in 1 228 847 incidents (50.1%). ADRD was more frequently diagnosed within 1 year of a fall compared with other injury mechanisms (10.6% [129 910 of 1 228 847] vs 6.1% [74 799 of 1 224 808]; P < .001). The unadjusted hazard ratio (HR) of incident dementia diagnosis after a fall was 1.63 (95% CI, 1.61-1.64; P < .001). On multivariable Cox competing risk analysis, falling was independently associated with an increased risk of dementia diagnosis among older adults (HR, 1.21 [95% CI, 1.20-1.21]; P < .001) after controlling for patient demographics, medical comorbidities, and injury characteristics, while accounting for the competing risk of death. Among the subset of older adults without a recent skilled nursing facility admission, the HR was 1.27 (95% CI, 1.26-1.28; P < .001). In this cohort study, new ADRD diagnoses were more common after falls compared with other mechanisms of injury, with 10.6% of older adults being diagnosed with ADRD in the first year after a fall. To improve the early identification of ADRD, this study's findings suggest support for the implementation of cognitive screening in older adults who experience an injurious fall that results in an ED visit or hospital admission.

Friction Burns: Defining the Rub of Road Rash After Motorcycle Trauma.

There is a paucity of literature on friction burn epidemiology, injury characteristics, and management after trauma. This study aims to characterize friction burns resulting from motorcycle accidents, evaluate the role of specialized burn surgery teams, and assess the need for operative intervention. The trauma registry of a Level 1 Trauma Center was queried for all admissions after motorcycle accidents between January 2018 and December 2022. Patients were included if there was an external cause of injury code for an abrasion. Chart review was conducted to confirm a road rash injury, identify burn consultation, wound care recommendations, need for operating room (OR) procedure and skin grafting, and outcomes. Among the 810 patients meeting inclusion criteria, the cohort was 92% male, 46% Hispanic, with median age of 33 (IQR 26-44), and median ISS 8 (IQR 5-14). The extremities were most affected by friction burn followed by the abdomen, thorax, and face. Burn surgery was consulted in 7% (n=57) of cases which had a median TBSA of 4% (IQR 2-6%); 23% (n=13) of these patients underwent excision in the OR, 16% (n=9) required autografting, and 61% (n=35) were referred for burn follow-up on discharge. On multivariable regression, consults to burn were more likely in female patients (OR 3.40, p=0.002) and those with involvement of the upper extremity, abdomen, or thorax. Friction burns are common after motorcycle-related trauma. Local wound care is sufficient for a vast majority of these injuries and the need for specialized burn care and operative intervention is rare.

Evaluation of the Coding System for the Causes of Traffic Accidents at the Medical Records Unit of Hospital X in Merangin, Indonesia

The coding system is one of the important things in several activity units in medical records. Writing a complete, clear, and specific diagnosis by the doctor and coding officer is a support in determining the correct code. This study aimed to describe writing equipment and accuracy of the results coding external causes (external cause) traffic accident cases in Hospital X in Merangin Regency. This research is a descriptive observational study. The research location is the medical records installation section coding of Hospital X in Merangin Regency. This research was conducted in November 2021-June 2022. The inclusion criteria for research subjects were medical records of patients in traffic accident cases recorded from September to 2021. A total of 64 medical record documents were sampled in this study. In the external cause of injury code, the completeness of the victim's role item was 39.06%, the victim's type of transportation was 96.88%, the opposing party involved in the collision was 92.19%, and the victim's activities during the accident were 3.12%. In this study, only 2 medical records explained the victim's activities during the traffic accident because the hospital reporting did not use the 5th character, which describes the victim's activities. In conclusion, most of the external cause items recorded in traffic accident cases are written completely. Factors related to inaccuracy external cause code in the form of man, method, material, and machine.

COST OF US EMERGENCY DEPARTMENT AND INPATIENT VISITS FOR FALL INJURIES IN OLDER ADULTS: 2016–2018

Abstract Falls are a leading cause of injury among older adults. While numerous studies have estimated the economic burden of falls, how health care spending varies by sociodemographic and injury factors is not well understood. The purpose of this study was to describe the average annual frequency of emergency department and inpatient visits and associated costs for fall injuries among older adults in the United States and identify factors associated with higher cost using data from the 2016-2018 National Inpatient Sample and National Emergency Department Sample. The study cohort included encounters with an ICD-10 external cause of injury code for fall (W00-W19). Number of visits was computed using survey weights. Direct visit cost was estimated from charges, applying cost-to-charge and professional fee ratios. On average, an estimated 2.7 million (95%CI: 2.5-2.9) fall-related ED visits and 1.1 million (95%CI: 1.1-1.2) inpatient visits occurred annually. The annual average cost was $1,105 (95%CI: $1,083-$1,127) per ED visit and $18,047 (95%CI: $17,905-$18,189) per inpatient visit totaling $22.9 billion annually. Higher inpatient cost was associated with age (65-74: $20,258 vs 85+: $16,183), gender (men: $19,541 vs. women: $17,181), and race (White: $17,570 vs. Black/Hispanic: $19,602); higher ED cost was associated with age (65-74: $1,009 vs. 85+: $1,198) and dementia diagnosis ($1,369 vs. $1,073). Fifty five percent of inpatient and 25% of ED visits were for fracture which had higher cost compared to sprains, dislocations, and superficial injuries. Results indicate growing number of fall-related admissions and costs underscoring need for targeted prevention and intervention strategies.

Predictive Risk Model for Serious Falls Among Older Persons Living With HIV.

Older (older than 50 years) persons living with HIV (PWH) are at elevated risk for falls. We explored how well our algorithm for predicting falls in a general population of middle-aged Veterans (age 45-65 years) worked among older PWH who use antiretroviral therapy (ART) and whether model fit improved with inclusion of specific ART classes. This analysis included 304,951 six-month person-intervals over a 15-year period (2001-2015) contributed by 26,373 older PWH from the Veterans Aging Cohort Study who were taking ART. Serious falls (those falls warranting a visit to a health care provider) were identified by external cause of injury codes and a machine-learning algorithm applied to radiology reports. Potential predictors included a fall within the past 12 months, demographics, body mass index, Veterans Aging Cohort Study Index 2.0 score, substance use, and measures of multimorbidity and polypharmacy. We assessed discrimination and calibration from application of the original coefficients (model derived from middle-aged Veterans) to older PWH and then reassessed by refitting the model using multivariable logistic regression with generalized estimating equations. We also explored whether model performance improved with indicators of ART classes. With application of the original coefficients, discrimination was good (C-statistic 0.725; 95% CI: 0.719 to 0.730) but calibration was poor. After refitting the model, both discrimination (C-statistic 0.732; 95% CI: 0.727 to 0.734) and calibration were good. Including ART classes did not improve model performance. After refitting their coefficients, the same variables predicted risk of serious falls among older PWH nearly and they had among middle-aged Veterans.

A national assessment of legacy versus new generation Medicaid data.

To compare the performance of Medicaid legacy, Medicaid new generation, and Medicare claims on data analytic tasks. Medicaid Analytic eXtract (MAX) claims (legacy) of 100% beneficiaries in 2011 (all states except Idaho), 2012 (all states), 2013 (28 states), and 2014 (17 states); 2016 Transformed Medicaid Statistical Information System Analytic Files (TAF) claims (new generation) of 100% beneficiaries from all states; Medicare claims of 20% beneficiaries in 2011-2014, 2016. We focused on the chain of events that starts with an out-of-hospital medical emergency and ends with hospital death or survival to discharge. We developed six data quality indicators to assess ambulance variables; linkage between claims; external cause of injury code reporting; and death reporting on hospital discharge status codes. For the latter, we estimated injury severity and modeled its association with death in the Medicare population. We used the model to compare reported versus expected deaths by injury severity in the Medicaid population. Datasets were compared by state and fee-for-service versus managed care. Medicare and Medicaid beneficiaries with emergency ambulance transports. Medicare claims had high performance across indicators and states; MAX claims substantially underperformed on multiple indicators in most states. For example, most states reported external cause codes for over 90% of Medicare but less than 15% of Medicaid injury cases. Medicaid fee-for-service did not consistently perform better than Medicaid managed care. Compared with MAX, TAF claims performed significantly better on some indicators but continued to have poor external cause code reporting. Finally, MAX and TAF managed care records reported deaths at discharge in the range of expected deaths; however, fee-for-service claims might have underreported high-severity injury deaths. New generation Medicaid claims performed better than legacy claims on some indicators, but much more improvement is needed to allow high-quality policy analysis.

A taxonomy of childhood pedal cyclist injuries from latent class analysis: associations with factors pertinent to prevention

BackgroundStudies of pedal cyclist injuries have largely focused on individual injury categories, but every region of the cyclist’s body is exposed to potential trauma. Real-world injury patterns can be complex, and isolated injuries to one body part are uncommon among casualties requiring hospitalization. Latent class analysis (LCA) may identify important patterns in heterogeneous samples of qualitative data.MethodsData were taken from the Trauma Quality Improvement Program of the American College of Surgeons for 2017. Inclusion criteria were age 18 years or less and an external cause of injury code for pedal cyclist. Injuries were characterized by Abbreviated Injury Scale codes. Injury categories and the total number of injuries served as covariates for LCA. A model was selected on the basis of the Akaike and Bayesian information criteria and the interpretability of the classes. Associations were analyzed between class membership and demographic factors, circumstantial factors, metrics of injury severity, and helmet wear. Within-class associations of helmet wear with injury severity were analyzed as well.ResultsThere were 6151 injured pediatric pedal cyclists in the study sample. The mortality rate was 0.5%. The rate of helmet wear was 18%. LCA yielded a model with 6 classes: ‘polytrauma’ (5.5%), ‘brain’ (9.0%), ‘abdomen’ (11.0%), ‘upper limb’ (20.9%), ‘lower limb’ (12.4%), and ‘head’ (41.2%). Class membership had highly significant univariate associations with all covariates except insurance payer. Helmet wear was most common in the ‘abdomen’ class and least common in the ‘polytrauma’ and ‘brain’ classes. Within classes, there was no association of helmet wear with severity of injury.ConclusionsLCA identified 6 clear and distinct patterns of injury with varying demographic and circumstantial associations that may be relevant for prevention. The rate of helmet wear was low, but it varied among classes in accordance with mechanistic expectations. LCA may be an underutilized tool in trauma epidemiology.

National Trends in Emergency Department Visits for Child Maltreatment, 2007-2014.

To understand the prevalence of child maltreatment-related emergency department (ED) visits in the United States, we examined data from the 2007 to 2014 Nationwide Emergency Department Sample. Based on existing literature, International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9 CM) ED discharge codes for children less than 10 years of age were characterized as specified child maltreatment, defined as visits with an explicit maltreatment ICD-9 CM or external causes of injury codes. The prevalence of child maltreatment visits per 100,000 children in the United States (based on Center for Disease Control Wide-ranging ONline Data for Epidemiologic Research estimates) overall and by sociodemographic factors was examined, and tests for trends over time were evaluated with Cochran-Armitage tests. Analyses were conducted in 2019. The prevalence of child maltreatment based in ICD-9 CM discharge codes ED visits dropped from 69.2 visits per 100,000 in 2007 to 65.9 visits per 100,000 in 2014; this trend was statistically significant. The prevalence was lowest in 2010 (60.1 visits per 100,000 children). There were increases observed for some demographic groups in this period. Throughout the 8-year period examined, the prevalence of child maltreatment visits was highest for physical abuse compared with other forms of maltreatment, higher for boys compared with girls; highest for children younger than 1 year, and higher for children living in neighborhoods with the lowest median income compared with children in higher-income neighborhoods. The Nationwide Emergency Department Sample data set is a valuable surveillance tool for examining trends in child maltreatment. Future studies should explore what factors may explain variations in child maltreatment over time to best develop prevention strategies.

Brief Report: Are Serious Falls Associated With Subsequent Fragility Fractures Among Veterans Living With HIV?

The extensive research on falls and fragility fractures among persons living with HIV (PWH) has not explored the association between serious falls and subsequent fragility fracture. We explored this association. Veterans Aging Cohort Study. This analysis included 304,951 6-month person- intervals over a 15-year period (2001-2015) contributed by 26,373 PWH who were 50+ years of age (mean age 55 years) and taking antiretroviral therapy (ART). Serious falls (those falls significant enough to result in a visit to a health care provider) were identified by the external cause of injury codes and a machine learning algorithm applied to radiology reports. Fragility fractures were identified using ICD9 codes and included hip fracture, vertebral fractures, and upper arm fracture and were modeled with multivariable logistic regression with generalized estimating equations. After adjustment, serious falls in the previous year were associated with increased risk of fragility fracture [odds ratio (OR) 2.10; 95% confidence interval (CI): 1.83 to 2.41]. The use of integrase inhibitors was the only ART risk factor (OR 1.17; 95% CI: 1.03 to 1.33). Other risk factors included the diagnosis of alcohol use disorder (OR 1.49; 95% CI: 1.31 to 1.70) and having a prescription for an opioid in the previous 6 months (OR 1.40; 95% CI: 1.27 to 1.53). Serious falls within the past year are strongly associated with fragility fractures among PWH on ART-largely a middle-aged population-much as they are among older adults in the general population.

Identification of Fall-Related Injuries in Nursing Home Residents Using Administrative Claims Data.

Fall-related injuries (FRIs) are a leading cause of morbidity, mortality, and costs among nursing home (NH) residents. Carefully defining FRIs in administrative data is essential for improving injury-reduction efforts. We developed a series of novel claims-based algorithms for identifying FRIs in long-stay NH residents. This is a retrospective cohort of residents of NH residing there for at least 100 days who were continuously enrolled in Medicare Parts A and B in 2016. FRIs were identified using 4 claims-based case-qualifying (CQ) definitions (Inpatient [CQ1], Outpatient and Provider with Procedure [CQ2], Outpatient and Provider with Fall [CQ3], or Inpatient or Outpatient and Provider with Fall [CQ4]). Correlation was calculated using phi correlation coefficients. Of 153 220 residents (mean [SD] age 81.2 [12.1], 68.0% female), we identified 10 104 with at least one FRI according to one or more CQ definition. Among 2 950 residents with hip fractures, 1 852 (62.8%) were identified by all algorithms. Algorithm CQ4 (n = 326-2 775) identified more FRIs across all injuries while CQ1 identified less (n = 21-2 320). CQ2 identified more intracranial bleeds (1 028 vs 448) than CQ1. For nonfracture categories, few FRIs were identified using CQ1 (n = 20-488). Of the 2 320 residents with hip fractures identified by CQ1, 2 145 (92.5%) had external cause of injury codes. All algorithms were strongly correlated, with phi coefficients ranging from 0.82 to 0.99. Claims-based algorithms applied to outpatient and provider claims identify more nonfracture FRIs. When identifying risk factors, stakeholders should select the algorithm(s) suitable for the FRI and study purpose.

Firearm injuries during legal interventions Nationwide analysis.

There is limited literature on firearm injuries during legal interventions. The purpose of this study was to examine the epidemiology, injury characteristics, and outcomes of both civilians and law enforcement officials (LEOs) who sustained firearm injuries over the course of legal action. Retrospective observational study using data from the National Trauma Data Bank (2015-2017) was performed. All patients who were injured by firearms during legal interventions were identified using the International Classification of Disease, Tenth Revision, external cause of injury codes. The study groups were injured civilian suspects and police officers. Demographics, injury characteristics, and outcomes were analyzed and compared between the groups. Primary outcomes were the clinical and injury characteristics among the victims. A total of 1,411 patients were included in the study, of which 1,091 (77.3%) were civilians, 289 officers (20.5%), and 31 bystanders (2.2%). Overall, 95.2% of patients were male. Compared with LEOs, civilians were younger (31 vs. 34 years, p = 0.007) and more severely injured (median Injury Severity Score, 13 vs. 10 [p = 0.005]; Injury Severity Score >15, 44.4% vs. 37.1% [p = 0.025]). Civilians were more likely to sustain severe (Abbreviated Injury Scale, ≥3) intra-abdominal injuries (26.8% vs. 16.1%, p < 0.001) and spinal fractures (13.0% vs. 6.9%, p = 0.004). In-hospital mortality and overall complication rate were similar between the groups (mortality: civilians, 24.7% vs. LEOs, 27.3% [p = 0.360]; overall complications: civilians, 10.3% vs. LEOs, 8.4% [p = 0.338]). Firearm injuries during legal interventions are associated with significant injury burden and a higher mortality than the reported mortality in gunshot wounds among civilians. The mortality and overall complication rate were similar between civilian suspects and law enforcement officials. Epidemiologic, level IV.

United States trends in healthcare charges for pediatric firearm injuries.

From 2009 to 2016, >21,000 children died and an estimated 118,000 suffered non-fatal injuries from firearms in the United States. Limited data is available on resource utilization by injury intent. We use hospital charges as a proxy for resource use and sought to: 1) estimate mean charges for initial ED and inpatient care for acute firearm injuries among children in the U.S.; 2) compare differences in charges by firearm injury intent among children; and 3) evaluate trends in charges for pediatric firearm injuries over time, including within intent subgroups. In this repeated cross-sectional analysis of the 2009-2016 Nationwide Emergency Department Sample, we identified firearm injury cases among children aged ≤19years using ICD-9-CM and ICD-10-CM external cause of injury codes (e-codes). Injury intent was categorized using e-codes as unintentional, assault-related, self-inflicted, or undetermined. Linear regressions utilizing survey weighting were used to examine associations between injury intent and healthcare charges, and to evaluate trends in mean charges over time. Among 21,951 unweighted cases representing 102,072 pediatric firearm-related injuries, mean age was 16.6years, and a majority were male (88.2%) and publicly insured (51.5%). Injuries were 53.9% assault-related, 37.7% unintentional, 1.8% self-inflicted, and 6.7% undetermined. Self-inflicted injuries had higher mean charges ($98,988) than assault-related ($52,496) and unintentional ($28,618) injuries (p<0.001). Self-inflicted injuries remained associated with higher mean charges relative to unintentional injuries, after adjusting for patient demographics, hospital characteristics, and injury severity (p=0.015). Mean charges for assault-related injuries also remained significantly higher than charges for unintentional injuries in multivariable models (p<0.001). After adjusting for inflation, mean charges for pediatric firearm-related injuries increased over time (p-trend=0.018) and were 23.1% higher in 2016 versus 2009. Mean charges increased over time among unintentional injuries (p-trend=0.002), but not among cases with assault-related or self-inflicted injuries. Self-inflicted and assault-related firearm injuries are associated with higher mean healthcare charges than unintentional firearm injuries among children. Mean charges for pediatric firearm injuries have also increased over time. These findings can help guide prevention interventions aimed at reducing the substantial burden of firearm injuries among children.

Using hospitalization data for injury surveillance in agriculture, forestry and fishing: a crosswalk between ICD10CM external cause of injury coding and The Occupational Injury and Illness Classification System

BackgroundWhile statistics related to occupational injuries exist at state and national levels, there are notable difficulties with using these to understand non-fatal injuries trends in agriculture, forestry, and commercial fishing. This paper describes the development and testing of a crosswalk between ICD-10-CM external cause of injury codes (E-codes) for agriculture, forestry, and fishing (AFF) and the Occupational Injury and Illness Classification System (OIICS). By using this crosswalk, researchers can efficiently process hospitalization data and quickly assemble relevant cases of AFF injuries useful for epidemiological tracking.MethodsAll 6810 ICD-10-CM E- codes were double-reviewed and tagged for AFF- relatedness. Those related to AFF were then coded into a crosswalk to OIICS. The crosswalk was tested on hospital data (inpatient, outpatient, and emergency department) from New York, Massachusetts, and Vermont using SAS9.3. Injury records were characterized by type of event, source of injury, and by general demographics using descriptive epidemiology.ResultsOf the 6810 E-codes available in the ICD-10-CM scheme, 263 different E-codes were ultimately classified as 1 = true case, 2 = traumatic/acute and suspected AFF, or 3 = AFF and suspected traumatic/acute. The crosswalk mapping identified 9969 patient records either confirmed to be or suspected to be an AFF injury out of a total of 38,412,241 records in the datasets, combined. Of these, 963 were true cases of agricultural injury. The remaining 9006 were suspected AFF cases, where the E-code was not specific enough to assign certainty to the record’s work-relatedness. For the true agricultural cases, the most frequent combinations presented were contact with agricultural/garden equipment (301), non-roadway incident involving off-road vehicle (222), and struck by cow or other bovine (150). For suspected agricultural cases, the majority (68.2%) represent animal-related injuries.ConclusionsThe crosswalk provides a reproducible, low-cost, rapid means to identify and code AFF injuries from hospital data. The use of this crosswalk is best suited to identifying true agricultural cases; however, capturing suspected cases of agriculture, forestry, and fishing injury also provides valuable data.

Beyond Hip Fracture: Orthopaedic Trauma in an Aging America

Trauma related death and disability is common among working-age Americans, however the impact on older adults is consequential and increasing. Fractures are the most common traumatic injury diagnosis among Medicare beneficiaries, and though fragility fractures continue to be an important health problem, recent data indicate an increase in high-energy fractures. The purpose of this study was to produce national incidence estimates among US men and women ≥ 65 years using data from the 2003-2014 National Inpatient Sample (NIS). The study cohort included hospitalizations involving upper and/or lower extremity fractures which were further classified by mechanism as high or low energy using external cause of injury codes. Incidence was computed using survey weights provided by NIS, and population estimates from the Census Bureau. The incidence of high-energy fractures increased from 744.1/100,000 persons (95%CI: 681.1–807.1) in 2003 to 821.4/100,000 (95%CI: 795.0 – 874.8) in 2014 in women, and from 359.1/100,000 (95%CI: 331.4–386.8) to 408.2/100,000 (95%CI: 394.–809.2) in men. Over 80% were motor vehicle related. The greatest increase was among those ≥ 85 (1,856.4/100,000 to 2,126.3/100,000 in women; 1,069.1/100,000 to 1,215.1/100,000 in men). Simultaneously, the incidence of low-energy fractures declined: 748.4/100,000 (95%CI: 687.5–809.2) to 443.8/100,000 (95%CI: 423.5 -464.1) in women, and 310.6/100,000 (95%CI: 285 – 336.2) to 206.3/100,000 (95%CI: 196.5 - 216) in men. Results suggest that fractures commonly seen in younger adults will be seen more frequently in older age. It is therefore essential to establish treatment pathways to optimize outcomes for the growing number of injured older adults.

Epidemiologic Trends in Fatal and Nonfatal Firearm Injuries in the US, 2009-2017

Firearm injury research in the US has focused on fatal injuries. The incidence and epidemiologic factors associated with nonfatal firearm injuries are less understood. To evaluate estimates of incidence and trends over time of fatal and nonfatal firearm injuries. A cross-sectional, ecologic study was conducted using data throughout the US from 2009 to 2017. Data on fatal injuries from the Centers for Disease Control and Prevention were combined with national data on emergency department visits for nonfatal firearm injury from the Nationwide Emergency Department (ED) sample. Data analysis was conducted from August 2019 to September 2020. Firearm injuries identified with International Classification of Diseases external cause of injury codes and categorized by intent of injury, age group, and urban-rural location. Incidence, case fatality rate, and trends over time of firearm injury according to intent, age group, and urban-rural location. From 2009 to 2017, there was a mean of 85 694 ED visits for nonfatal firearm injury and 34 538 deaths each year. An annual mean of 26 445 deaths (76.6%) occurred outside of the hospital. Assault was the most common overall mechanism (38.9%), followed by unintentional injuries (36.9%) and intentional self-harm (19.6%). Self-harm, which accounted for 21 128 deaths (61.2%), had the highest case fatality rate (89.4%; 95% CI, 88.5%-90.4%), followed by assault (25.9%; 95% CI, 23.7%-28.6%) and legal intervention (23.4%; 95% CI, 21.6%-25.5%). Unintentional injuries were the most common nonfatal injuries (43 729 [51.0%]) and had the lowest case fatality rate (1.2%; 95% CI, 1.1%-1.3%). Self-harm deaths, 87.8% of which occurred outside the hospital, increased in all age groups in both rural and urban areas during the study period and were most common among people aged 55 years and older. The rate of fatal assault injuries was higher in urban than in rural areas (16.6 vs 9.0 per 100 000 per year) and highest among people aged 15 to 34 years (38.6 per 100 000 per year). Rates of unintentional injury were higher in rural than in urban areas (18.5 per 100 000 vs 12.4 per 100 000). In this cross-sectional study, suicide appears to be the most common cause of firearm injury death in the US, and most people who die from suicide never reach the hospital. These findings suggest that assaults and unintentional injuries account for most nonfatal and overall firearm injuries and for most of the injuries that are treated in hospitals.

Using Coronial Records to Provide Novel In-Depth Insights into Work-Related Fatal Injury

IntroductionNew Zealand’s (NZ) workplace fatality record is very poor compared to similar OECD countries. The reasons for NZ’s poor performance are highly debated yet inadequately informed due to a lack of high quality fatality data. Due to incomplete official data on work fatalities in NZ, it is not currently possible to use routine official data collections to reliably report: i) who is fatally injured due to work activities, and ii) what groups should be prioritised for action.&#x0D; Objectives and ApproachThis study uses coronial records to overcome the limitations of existing official data collections to provide the most complete and detailed evidence platform for occupational safety policy and action in NZ. A work-related fatal injury dataset spanning the period 2005-2014 was created by: 1) identifying possible cases aged 0-84 years from the Mortality Collection using selected external cause of injury codes, 2) linking these to Coronial records and 3) identifying and coding work-related cases.&#x0D; ResultsOf 7,730 injury fatalities with corresponding Coronial records retrieved and reviewed, 1,924 (24%) were work-related, of which 955 were workers. Fifty-nine per cent more worker deaths were identified compared to available official NZ Government estimates from notification and compensation data. Workers killed on public roads were the main additional group identified. Official data do not provide occupation-based fatality rates; our study found ‘Miners and drillers’, ‘deckhands and fishermen’ and ‘loggers’ had the highest rates of fatal injury.&#x0D; Conclusion / ImplicationsCoronial records offer a rich source of population data on work-related fatal injury deaths, providing better estimates of work-traffic fatalities and high risk occupations than are otherwise available as well as evidence for establishing prevention strategies in NZ.

Washington's liquor license system and alcohol-related adverse health outcomes.

In June 2012, Washington state (USA) implemented Initiative 1183, privatizing liquor sales. As a result, off-premises outlets increased from 330 to over 1400 and trading hours lengthened. Increased availability of liquor may lead to increased consumption. This study examines the impact of Initiative 1183 on alcohol-related adverse health outcomes, measured by inpatient hospitalizations for alcohol-related disorders and accidental injuries. It further assesses heterogeneity by urbanicity, because outlets increased most in metropolitan-urban areas. County-by-quarter difference-in-difference linear regression models, estimated statewide and within metropolitan/rural strata. Data are from AHRQ Healthcare Cost and Utilization State Inpatient Database 2010-2014 and HHS Area Health Resource File 2010-2014. Changes in the rates of hospitalizations in the 2.5years following Initiative 1183 in Washington (n=39 counties) are compared with changes in Oregon (n=36 counties). County rates of hospitalizations per 1000 residents, including all records with any-listed ICD-9 Clinical Classification Software code denoting an alcohol-related disorder, and all records with any-listed external cause of injury code denoting an accidental injury. The increase in the rate of accidental injury hospitalizations in Washington's metropolitan-urban counties was on average 0.289 hospitalizations per 1000 county residents per quarter greater than the simultaneous increase observed in Oregon (P=0.017). This result was robust to alternative specifications using a propensity score matched sample and synthetic control methods with data from other comparison states. The evidence did not suggest that Initiative 1183 was associated with differential changes in the rate of hospitalizations for alcohol-related disorders in metropolitan-urban (P=0.941), non-metropolitan-urban (P=0.162), or rural counties (P=0.876). Implementing Washington's Initiative 1183 (privatizing liquor sales) appears to have been associated with a significant increase in the rate of accidental injury hospitalizations in urban counties in that state but does not appear to be significantly associated with changes in the rate of hospitalizations specifically for alcohol-related disorders within 2.5years.

Serious Falls in Middle-Aged Veterans: Development and Validation of a Predictive Risk Model.

Due to high rates of multimorbidity, polypharmacy, and hazardous alcohol and opioid use, middle-aged Veterans are at risk for serious falls (those prompting a visit with a healthcare provider), posing significant risk to their forthcoming geriatric health and quality of life. We developed and validated a predictive model of the 6-month risk of serious falls among middle-aged Veterans. Cohort study. Veterans Health Administration (VA). Veterans, aged 45 to 65 years, who presented for care within the VA between 2012 and 2015 (N = 275,940). The exposures of primary interest were substance use (including alcohol and prescription opioid use), multimorbidity, and polypharmacy. Hazardous alcohol use was defined as an Alcohol Use Disorders Identification Test - Consumption (AUDIT-C) score of 3 or greater for women and 4 or greater for men. We used International Classification of Diseases, Ninth Revision (ICD-9), codes to identify alcohol and illicit substance use disorders and identified prescription opioid use from pharmacy fill-refill data. We included counts of chronic medications and of physical and mental health comorbidities. We identified serious falls using external cause of injury codes and a machine-learning algorithm that identified serious falls in radiology reports. We used multivariable logistic regression with general estimating equations to calculate risk. We used an integrated predictiveness curve to identify intervention thresholds. Most of our sample (54%) was aged 60 years or younger. Duration of follow-up was up to 4 years. Veterans who fell were more likely to be female (11% vs 7%) and White (72% vs 68%). They experienced 43,641 serious falls during follow-up. We identified 16 key predictors of serious falls and five interaction terms. Model performance was enhanced by addition of opioid use, as evidenced by overall category-free net reclassification improvement of 0.32 (P < .001). Discrimination (C-statistic = 0.76) and calibration were excellent for both development and validation data sets. We developed and internally validated a model to predict 6-month risk of serious falls among middle-aged Veterans with excellent discrimination and calibration.

Incidence, Distribution, and Lethality of Firearm Injuries in California From 2005 to 2015

Little is known about nonfatal firearm injuries in the United States, and national estimates based on emergency department samples may not be accurate. To describe the incidence and distribution of nonfatal firearm injuries and estimate case fatality ratios (CFRs) for firearm injuries by external cause of injury code within California overall and by race/ethnicity, including an assessment of trends over time and geographic variation within the state. This serial cross-sectional study used complete statewide data for firearm-related mortality, emergency department visits, and hospitalizations among California residents from January 1, 2005, through December 31, 2015, to analyze incidence, distribution, and CFRs of firearm injury. Data were analyzed from 2018 to 2019. All individuals in California with a firearm injury based on International Classification of Diseases, Ninth Revision or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes were included. Counts and rates of nonfatal firearm injuries overall and stratified by external cause, sex, and race/ethnicity; total and clinical CFRs. Clinical CFR was calculated based on individuals treated in emergency departments or hospitals. Over the study period, there were 81 085 firearm-related emergency department visits and hospitalizations among individuals with a mean (SD) age of 27.5 (11.9) years, 72 567 (89.6%) of whom were men. Nonfatal firearm injuries in California decreased by 38.1% between 2005 and 2015, driven by a 46.4% decrease in assaultive injuries. Self-inflicted injuries and unintentional injuries remained relatively stable. The overall CFR for firearm injuries increased from 27.6% in 2005 to 32.2% in 2015 for a relative increase of 20.7%, while the clinical CFR remained stable between 7.0% and 9.0%. These findings suggest that although the number of firearm injuries has decreased in California, the lethality of these injuries has not. Similar studies from other states could provide more information about these trends nationwide.

Bike helmets prevent pediatric head injury in serious bicycle crashes with motor vehicles

BackgroundApproximately 75% of all bicycle-related mortality is secondary to head injuries, 85% of which could have been prevented by wearing a bicycle helmet. Younger children appear to be at greater risk than adults, yet helmet use is low despite this risk and legislation and ordinances requiring helmet use among younger riders. We sought to determine whether bicycle helmets are associated with the incidence and severity of head injury among pediatric bicyclists involved in a bicycle crash involving a motor vehicle.MethodsWe performed a retrospective review of patients age ≤ 18 years hospitalized at a level I pediatric trauma center between January 1, 2008, and December 31, 2018. Data were abstracted from the institutional trauma registry and electronic medical record. International Classification of Diseases 9th and 10th editions and external causes of injury codes were used to identify MV related bicycle crashes and determine the abbreviated injury severity (AIS) for head injury severity. Injury narratives were reviewed to determine helmet use. We calculated the incidence of head injury from bicycle vs. MV crashes utilizing descriptive statistics. We analyzed the risk and severity of injury utilizing univariate and multivariate logistic regression.ResultsOverall, 226 bicyclists were treated for injuries from being struck by a MV. The median age was 11 (interquartile range (IQR): 8 to 13) years. Helmeted bicyclists (n = 26, 27%) were younger (9.4 years versus 10.8 years, p = 0.04), and were less likely (OR 0.21, 95% CI 0.09 to 0.49) to be diagnosed with a head injury compared to unhelmeted bicyclists (n = 199). Of those with a head injury, helmeted bicyclists were less likely (OR 0.57, 95% CI 0.11–2.82) to sustain severe or higher injury using AIS. When adjusting for demographics (age, sex, race) and injury severity, helmet use predicted a reduction in head injury (OR 6.02, 95% CI 2.4–15.2).ConclusionsBicycle helmet use was associated with reduced odds of head injury and severity of injury.. These results support the use of strategies to increase the uptake of bicycle helmets wearing as part of a comprehensive youth bicycling injury prevention program.