Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention最新文献

{"title":"Accuracy of ICD-10-CM coding for physical child abuse in a paediatric level I trauma centre.","authors":"Holly Hughes Garza,&nbsp;Karen E Piper,&nbsp;Amanda N Barczyk,&nbsp;Adriana Pérez,&nbsp;Karla A Lawson","doi":"10.1136/injuryprev-2019-043513","DOIUrl":"https://doi.org/10.1136/injuryprev-2019-043513","url":null,"abstract":"<p><p>This retrospective study examined the accuracy of the International Classification of Diseases, Clinical Modification (ICD-10-CM) coding for physical child abuse among patients less than 18 years of age who were evaluated due to concern for physical abuse by a multidisciplinary child protection team (MCPT) during 2016-2017 (N=312) in a paediatric level I trauma centre. Sensitivity, specificity, predictive values and diagnostic OR for ICD-10-CM coding were calculated and stratified by admission status, using as a reference standard the abuse determination of the MCPT recorded in a hospital registry. Among inpatients, child physical abuse coding sensitivity was 55.6% (95% CI 41.4% to 69.1%) and specificity was 78.6% (95% CI 59.0% to 91.7%), with diagnostic OR of 4.58 (95% CI 1.64 to 12.70). Among outpatients, sensitivity was 22.2% (95% CI 15.5% to 30.2%) and specificity was 86.3% (95% CI 77.7% to 92.5%), with diagnostic OR of 1.80 (95% CI 0.89 to 3.64). Use of ICD-10-CM coded data sets alone for surveillance may significantly underestimate the occurrence of physical child abuse.</p>","PeriodicalId":520647,"journal":{"name":"Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention","volume":" ","pages":"i71-i74"},"PeriodicalIF":3.7,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/injuryprev-2019-043513","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25440446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of ICD-10-CM coded hospitalisation and emergency department data for injury surveillance.","authors":"Renee L Johnson,&nbsp;Holly Hedegaard,&nbsp;Emilia S Pasalic,&nbsp;Pedro D Martinez","doi":"10.1136/injuryprev-2019-043515","DOIUrl":"https://doi.org/10.1136/injuryprev-2019-043515","url":null,"abstract":"Injury surveillance, the ongoing, systematic collection, analysis, interpretation and dissemination of injury data, provides critical information to support public health efforts to reduce injuryrelated morbidity, mortality and disability. 2 For the past several decades, state and local health departments and national agencies in the USA have relied on the use of hospital discharge and emergency department (ED) data coded using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9CM) to conduct injury surveillance. Surveillance case definitions and analyses have been based on ICD-9CM codes. However, a US mandate to code using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10CM) 5 has resulted in a need to update injury surveillance case definitions and analysis guidance based on ICD-10CM. Beginning in October 2015, the US Department of Health and Human Services required all hospitals and healthcare providers covered by the Health Insurance Portability and Accountability Act to use the ICD-10CM to report electronic healthcare transactions. 5 The coding structure of ICD-10CM is based on ICD-10 mortality coding and classification published by the WHO, however, the classification scheme has been greatly expanded to capture the diagnostic detail needed for medical diagnoses. ICD-10CM contains nearly five times the number of codes found in ICD-9CM (approximately 72 000 codes in ICD-10CM compared with 15 000 codes in ICD-9CM). Because ICD-10CM captures greater detail than either ICD-9CM or ICD-10, this classification system has the potential to provide enhanced understanding of the types and causes of nonfatal injury. Epidemiologists and researchers who are transitioning from the use of ICD-9CM coded data to ICD-10CM coded data should note the substantial differences in the injury diagnosis and external causeofinjury codes in the two coding systems. These differences, which have the potential to either introduce or alleviate bias in nonfatal injury measurement, have been described in detail elsewhere. Important differences that have implications for injury surveillance include: ► Changes in the codes that identify events involving poisoning or toxic effects. In ICD-9CM, two codes were required to describe each poisoning event—a diagnosis code (960–979 and 980–989) to describe the type of drug or toxic substance involved and an external cause code (E850–E858, E860–E869, E930–E949, E950– E952, E961–E962 and E980–E982) to describe the intent of the poisoning or adverse effect (eg, accidental (unintentional), intentional selfharm, homicide or undetermined). In ICD-10CM, the information about both the drug or substance involved and the intent are captured in a single code (T36–T50 for drugs and biological substances, and T51–65 for toxic effects of nondrug substances). These T codes contain a character in the code to specify the intent of the poisoning (ie, accidental (unintention","PeriodicalId":520647,"journal":{"name":"Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention","volume":" ","pages":"i1-i2"},"PeriodicalIF":3.7,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/injuryprev-2019-043515","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25440055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interrupted time series analysis of cannabis coding in Colorado during the ICD-10-CM transition.","authors":"Katelyn E Hall,&nbsp;Hannah Yang,&nbsp;DeLayna Goulding,&nbsp;Elyse Contreras,&nbsp;Katherine A James","doi":"10.1136/injuryprev-2019-043511","DOIUrl":"https://doi.org/10.1136/injuryprev-2019-043511","url":null,"abstract":"<p><p>The International Classification of Diseases, 10^th Revision, Clinical Modification (ICD-10-CM), implemented in 2015, has more codes than ICD-9-CM for events involving cannabis. We examined cannabis indicator trends across the transition from ICD-9-CM to ICD-10-CM in Colorado, where state law regulates adult cannabis use. Using 2011 to 2018 data from hospital and emergency department (ED) discharges, we calculated monthly rates per 1000 discharges for two indicators: (1) cannabis use disorders and (2) poisoning and adverse effects of psychodysleptics. Immediate, point-of-transition (level) and gradual, post-transition (slope) changes across the ICD-9-CM to ICD-10-CM transition were tested using interrupted time series models adjusted for legalisation, seasonality and autocorrelation. We observed a level increase and slope increase in the rate of ED discharges with cannabis use disorders. Hospital discharges with cannabis use disorders had a negative slope change after the transition and no level change. ED discharges with poisoning and adverse effects of psychodysleptics showed an increase in slope after the transition. No effects of the transition were observed on hospital discharges with poisoning and adverse effects of psychodysleptics. Shifts in the level and slope of cannabis indicator rates after implementation of the new coding scheme suggest the use of caution when interpreting trends spanning the ICD-9-CM to ICD-10-CM transition.</p>","PeriodicalId":520647,"journal":{"name":"Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention","volume":" ","pages":"i66-i70"},"PeriodicalIF":3.7,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/injuryprev-2019-043511","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25440445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multisite medical record review of emergency department visits for unspecified injury of head following the ICD-10-CM coding transition.","authors":"Alexis Peterson,&nbsp;Barbara A Gabella,&nbsp;Jewell Johnson,&nbsp;Beth Hume,&nbsp;Ann Liu,&nbsp;Julia F Costich,&nbsp;Jeanne Hathaway,&nbsp;Svetla Slavova,&nbsp;Renee Johnson,&nbsp;Matt Breiding","doi":"10.1136/injuryprev-2019-043517","DOIUrl":"https://doi.org/10.1136/injuryprev-2019-043517","url":null,"abstract":"<p><strong>Introduction: </strong>In 2016, a proposed International Classification of Diseases, Tenth Edition, Clinical Modification surveillance definition for traumatic brain injury (TBI) morbidity was introduced that excluded the unspecified injury of head (S09.90) diagnosis code. This study assessed emergency department (ED) medical records containing S09.90 for evidence of TBI based on medical documentation.</p><p><strong>Methods: </strong>State health department representatives in Maryland, Kentucky, Colorado and Massachusetts reviewed a target of 385 randomly sampled ED records uniquely assigned the S09.90 diagnosis code (without proposed TBI codes), which were initial medical encounters among state residents discharged home during October 2015-December 2018. Using standardised abstraction procedures, reviewers recorded signs and symptoms of TBI, and head imaging results. A tiered case confirmation strategy was applied that assigned a level of certainty (high, medium, low, none) to each record based on the number and type of symptoms and imaging results present in the record. Positive predictive value (PPV) of S09.90 by level of TBI certainty was calculated by state.</p><p><strong>Results: </strong>Wide variation in PPV of sampled ED records assigned S09.90: 36%-52% had medium or high evidence of TBI, while 48%-64% contained low or no evidence of a TBI. Loss of consciousness was mentioned in 8%-24% of sampled medical records.</p><p><strong>Discussion: </strong>Exclusion of the S09.90 code in surveillance estimates may result in many missed TBI cases; inclusion may result in counting many false positives. Further, missed TBI cases influenced by incidence estimates, based on the TBI surveillance definition, may lead to inadequate allocation of public health resources.</p>","PeriodicalId":520647,"journal":{"name":"Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention","volume":" ","pages":"i13-i18"},"PeriodicalIF":3.7,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/injuryprev-2019-043517","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25441516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of ICD-10-CM codes for injuries complicating pregnancy, childbirth and the puerperium: a medical record review.","authors":"Anna Hansen,&nbsp;Dana Quesinberry,&nbsp;Peter Akpunonu,&nbsp;Julia Martin,&nbsp;Svetla Slavova","doi":"10.1136/injuryprev-2019-043512","DOIUrl":"https://doi.org/10.1136/injuryprev-2019-043512","url":null,"abstract":"<p><strong>Introduction: </strong>The purpose of this study was to estimate the positive predictive value (PPV) of International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes for injury, poisoning, physical or sexual assault complicating pregnancy, childbirth and the puerperium (PCP) to capture injury encounters within both hospital and emergency department claims data.</p><p><strong>Methods: </strong>A medical record review was conducted on a sample (n=157) of inpatient and emergency department claims from one Kentucky healthcare system from 2015 to 2017, with any diagnosis in the ICD-10-CM range O9A.2-O9A.4. Study clinicians reviewed medical records for the sampled cases and used an abstraction form to collect information on documented presence of injury and PCP complications. The study estimated the PPVs and the 95% CIs of O9A.2-O9A.4 codes for (1) capturing injuries and (2) capturing injuries complicating PCP.</p><p><strong>Results: </strong>The estimated PPV for the codes O9A.2-O9A.4 to identify injury in the full sample was 79.6% (95% CI 73.3% to 85.9%) and the PPV for capturing injuries complicating PCP was 72.0% (95% CI 65.0% to 79.0%). The estimated PPV for an inpatient principal diagnosis O9A.2-O9A.4 to capture injuries was 90.7% (95% CI 82.0% to 99.4%) and the PPV for capturing injuries complicating PCP was 88.4% (95% CI 78.4% to 98.4%). The estimated PPV for any mention of O9A.2-O9A.4 in emergency department data to capture injuries was 95.2% (95% CI 90.6% to 99.9%) and the PPV for capturing injuries complicating PCP was 81.0% (95% CI 72.4% to 89.5%).</p><p><strong>Discussion: </strong>The O9A.2-O9A.4 codes captured high percentage true injury cases among pregnant and puerperal women.</p>","PeriodicalId":520647,"journal":{"name":"Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention","volume":" ","pages":"i9-i12"},"PeriodicalIF":3.7,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/injuryprev-2019-043512","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25440056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defining indicators for drug overdose emergency department visits and hospitalisations in ICD-10-CM coded discharge data.","authors":"Alana Vivolo-Kantor,&nbsp;Emilia Pasalic,&nbsp;Stephen Liu,&nbsp;Pedro D Martinez,&nbsp;Robert Matthew Gladden","doi":"10.1136/injuryprev-2019-043521","DOIUrl":"https://doi.org/10.1136/injuryprev-2019-043521","url":null,"abstract":"<p><strong>Introduction: </strong>The drug overdose epidemic has worsened over the past decade; however, efforts have been made to better understand and track nonfatal overdoses using various data sources including emergency department and hospital admission data from billing and discharge files.</p><p><strong>Methods and findings: </strong>The Centers for Disease Control and Prevention (CDC) has developed surveillance case definition guidance using standardised discharge diagnosis codes for public health practitioners and epidemiologists using lessons learnt from CDC's funded recipients and the Council for State and Territorial Epidemiologists (CSTE) International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) Drug Poisoning Indicators Workgroup and General Injury ICD-10-CM Workgroup. CDC's guidance was informed by health departments and CSTE's workgroups and included several key aspects for assessing drug overdose in emergency department and hospitalisation discharge data. These include: (1) searching all diagnosis fields to identify drug overdose cases; (2) estimating drug overdose incidence using visits for initial encounter but excluding subsequent encounters and sequelae; (3) excluding underdosing and adverse effects from drug overdose incidence indicators; and (4) using codes T36-T50 for overdose surveillance. CDC's guidance also suggests analysing intent separately for ICD-10-CM coding.</p><p><strong>Conclusions: </strong>CDC's guidance provides health departments a key tool to better monitor drug overdoses in their community. The implementation and validation of this standardised guidance across all CDC-funded health departments will be key to ensuring consistent and accurate reporting across all entities.</p>","PeriodicalId":520647,"journal":{"name":"Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention","volume":" ","pages":"i56-i61"},"PeriodicalIF":3.7,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/injuryprev-2019-043521","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25441522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multisite medical record review of emergency department visits for traumatic brain injury.","authors":"Barbara A Gabella,&nbsp;Jeanne E Hathaway,&nbsp;Beth Hume,&nbsp;Jewell Johnson,&nbsp;Julia F Costich,&nbsp;Svetla Slavova,&nbsp;Ann Y Liu","doi":"10.1136/injuryprev-2019-043510","DOIUrl":"https://doi.org/10.1136/injuryprev-2019-043510","url":null,"abstract":"<p><strong>Background: </strong>In 2016, the CDC in the USA proposed codes from the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) for identifying traumatic brain injury (TBI). This study estimated positive predictive value (PPV) of TBI for some of these codes.</p><p><strong>Methods: </strong>Four study sites used emergency department or trauma records from 2015 to 2018 to identify two random samples within each site selected by ICD-10-CM TBI codes for (1) intracranial injury (S06) or (2) skull fracture only (S02.0, S02.1-, S02.8-, S02.91) with no other TBI codes. Using common protocols, reviewers abstracted TBI signs and symptoms and head imaging results that were then used to assign certainty of TBI (none, low, medium, high) to each sampled record. PPVs were estimated as a percentage of records with medium-certainty or high-certainty for TBI and reported with 95% confidence interval (CI).</p><p><strong>Results: </strong>PPVs for intracranial injury codes ranged from 82% to 92% across the four samples. PPVs for skull fracture codes were 57% and 61% in the two university/trauma hospitals in each of two states with clinical reviewers, and 82% and 85% in the two states with professional coders reviewing statewide or nearly statewide samples. Margins of error for the 95% CI for all PPVs were under 5%.</p><p><strong>Discussion: </strong>ICD-10-CM codes for traumatic intracranial injury demonstrated high PPVs for capturing true TBI in different healthcare settings. The algorithm for TBI certainty may need refinement, because it yielded moderate-to-high PPVs for records with skull fracture codes that lacked intracranial injury codes.</p>","PeriodicalId":520647,"journal":{"name":"Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention","volume":" ","pages":"i42-i48"},"PeriodicalIF":3.7,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/injuryprev-2019-043510","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25441520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National rates of non-fatal emergency department visits and hospitalisations due to fall-related injuries in older adults 2010-2014 and 2016: transitioning from ICD-9-CM to ICD-10-CM.","authors":"Briana L Moreland, Elizabeth R Burns, Yara K Haddad","doi":"10.1136/injuryprev-2019-043516","DOIUrl":"10.1136/injuryprev-2019-043516","url":null,"abstract":"<p><strong>Background: </strong>This study describes rates of non-fatal fall-injury emergency department (ED) visits and hospitalisations before and after the US 2015 transition from the 9th to 10th revision of the International Classification of Diseases, Clinical Modification (ICD-9-CM to ICD-10-CM).</p><p><strong>Methods: </strong>ED visit and hospitalisation data for adults aged 65+ years were obtained from the 2010-2016 Healthcare Cost and Utilisation Project. Differences in fall injury rates between 2010 and 2014 (before transition), and 2014 and 2016 (before and after transition) were analysed using t-tests.</p><p><strong>Results: </strong>For ED visits, rates did not differ significantly between 2014 and 2016 (4288 vs 4318 per 100 000, respectively). Hospitalisation rates were lower in 2014 (1232 per 100 000) compared with 2016 (1281 per 100 000).</p><p><strong>Conclusion: </strong>Increased rates of fall-related hospitalisations could be an artefact of the transition or may reflect an increase in the rate of fall-related hospitalisations. Analyses of fall-related hospitalisations across the transition should be interpreted cautiously.</p>","PeriodicalId":520647,"journal":{"name":"Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention","volume":" ","pages":"i75-i78"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7948188/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25440447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of designated open water swim area regulations and open water drowning rates.","authors":"Linda Quan,&nbsp;Brianna Mills,&nbsp;Suet Sen Chau,&nbsp;Elizabeth Bennett,&nbsp;Kaylin Bolt,&nbsp;Anthony Gomez","doi":"10.1136/injuryprev-2019-043464","DOIUrl":"https://doi.org/10.1136/injuryprev-2019-043464","url":null,"abstract":"<p><strong>Background: </strong>Although most persons over 5 years of age drown in open water, few laws have sought to regulate open water swim sites. We examined the association between regulations for designated open water swim sites and open water drowning death rates by state.</p><p><strong>Methods: </strong>Using International Classification of Disease (ICD)-10 codes in the CDC Web-based Injury Statistics Query and Reporting System (WISQARS), we identified and calculated open water drowning deaths involving all ages from 2012 to 2017 for 50 states and calculated open water drowning death rates. We then identified and categorised types of state regulations (lifeguards, water quality, rescue equipment, tracking/planning/reporting and signage) for open water swim sites in place in 2017 for a sample of 30 states (20 high-drowning, 10 low-drowning). Analyses evaluated associations between open water drowning rates in three groups (overall, youth and non-white) and the total number and types of state regulations.</p><p><strong>Results: </strong>Swim site regulations and open water drowning death rates for 10 839 victims were associated in all regression models. States with more types of regulations had lower open water drowning death rates in a dose-response relationship. States lacking regulations compared with states with all five types of regulations had open water drowning death rates 3.02 times higher among youth (95% CI 1.82 to 4.99) and 4.16 times higher among non-white residents (95% CI 2.46 to 7.05). Lifeguard and tracking/planning/reporting regulations were associated with a 33% and 45% reduction in open water drowning rates overall and among those aged 0-17 years.</p><p><strong>Conclusion: </strong>States' open water swim area regulations, especially addressing tracking/planning/reporting and lifeguards, were associated with lower open water drowning death rates.</p>","PeriodicalId":520647,"journal":{"name":"Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention","volume":" ","pages":"10-16"},"PeriodicalIF":3.7,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/injuryprev-2019-043464","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37520551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying a systems thinking lens to injury causation in the outdoors: Evidence collected during 3 years of the Understanding and Preventing Led Outdoor Accidents Data System.","authors":"Scott McLean,&nbsp;Caroline F Finch,&nbsp;Natassia Goode,&nbsp;Amanda Clacy,&nbsp;Lauren J Coventon,&nbsp;Paul M Salmon","doi":"10.1136/injuryprev-2019-043424","DOIUrl":"https://doi.org/10.1136/injuryprev-2019-043424","url":null,"abstract":"<p><strong>Introduction: </strong>This article presents a detailed systems analysis of injury incidents from 35 Australian led outdoor activity organisations between 2014 to 2017.</p><p><strong>Method: </strong>Injury incident reports were collected using a specific led outdoor activity incident reporting system known as UPLOADS (Understanding and Preventing Led Outdoor Accidents Data System).</p><p><strong>Results: </strong>In total, 1367 people sustained injuries from across 20 different activities, with an injury rate of 1.9 injured people per 1000 participants over the three-year period. A total of 2234 contributory factors from multiple levels of the led outdoor activity system were identified from the incident reports, and 361 relationships were identified between contributory factors.</p><p><strong>Discussion: </strong>This systems analysis of injury incidents demonstrates that it is not only factors within the immediate context of the incident (<i>Participants, Environment, Equipment</i>) but factors from across multiple systemic levels that contributes to injury incidents (<i>Schools, Parents, Activity centre management</i>). Prevention efforts should focus on addressing the whole network of contributing factors and not only the prominent factors at the lower system levels within the immediate context of the injury incident occurrences.</p>","PeriodicalId":520647,"journal":{"name":"Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention","volume":" ","pages":"48-54"},"PeriodicalIF":3.7,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/injuryprev-2019-043424","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37523560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}