Molly P Jarman1, Elliott R Haut, Frank C Curriero, Renan C Castillo. 1. From the Department of Health Policy and Management (M.P.J.), Johns Hopkins Bloomberg School of Public Health Center for Surgery and Public Health, Brigham and Women's Hospital; Department of Surgery (E.R.H.), Johns Hopkins School of Medicine; Department of Epidemiology (F.C.C.), and Department of Health Policy and Management (R.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Abstract
BACKGROUND: Many rural, low-income, and historically underrepresented minority communities lack access to trauma center services, including surgical care and injury prevention efforts. Along with features of the built and social environment at injury incident locations, geographic barriers to trauma center services may contribute to injury disparities. This study sought to classify injury event locations based on features of the built and social environment at the injury scene, and to examine patterns in individual patient demographics, injury characteristics, and mortality by location class. METHODS: Data from the 2015 Maryland Adult Trauma Registry and associated prehospital records (n = 16,082) were used in a latent class analysis of characteristics of injury event locations, including trauma center distance, trauma center characteristics, land use, community-level per capita income, and community-level median age. Mortality effects of location class were estimated with logistic regression, with and without adjustment for individual patient demographics and injury characteristics. RESULTS: Eight classes were identified: rural, exurban, young suburban, aging suburban, inner suburban, urban fringe, high-income urban core, and low-income urban core. Patient characteristics and odds of death varied across classes. Compared with inner suburban locations, adjusted odds of death were highest at rural (odds ratio [OR], 1.98; 95% confidence interval [CI], 1.36-2.88), young suburb (OR, 1.57; 95% CI, 1.14-2.17), aging suburb (OR, 1.36; 95% CI, 1.04-1.78), and low-income urban core (OR, 1.38; 95% CI, 1.04-1.83) locations. CONCLUSION: Injury incident locations can be categorized into distinguishable classes with varying mortality risk. Identification of location classes may be useful for targeted primary prevention and treatment interventions, both by identifying geographic areas with the highest risk of injury mortality and by identifying patterns of individual risk within location classes. LEVEL OF EVIDENCE: Prognostic and epidemiological, level III.
BACKGROUND: Many rural, low-income, and historically underrepresented minority communities lack access to trauma center services, including surgical care and injury prevention efforts. Along with features of the built and social environment at injury incident locations, geographic barriers to trauma center services may contribute to injury disparities. This study sought to classify injury event locations based on features of the built and social environment at the injury scene, and to examine patterns in individual patient demographics, injury characteristics, and mortality by location class. METHODS: Data from the 2015 Maryland Adult Trauma Registry and associated prehospital records (n = 16,082) were used in a latent class analysis of characteristics of injury event locations, including trauma center distance, trauma center characteristics, land use, community-level per capita income, and community-level median age. Mortality effects of location class were estimated with logistic regression, with and without adjustment for individual patient demographics and injury characteristics. RESULTS: Eight classes were identified: rural, exurban, young suburban, aging suburban, inner suburban, urban fringe, high-income urban core, and low-income urban core. Patient characteristics and odds of death varied across classes. Compared with inner suburban locations, adjusted odds of death were highest at rural (odds ratio [OR], 1.98; 95% confidence interval [CI], 1.36-2.88), young suburb (OR, 1.57; 95% CI, 1.14-2.17), aging suburb (OR, 1.36; 95% CI, 1.04-1.78), and low-income urban core (OR, 1.38; 95% CI, 1.04-1.83) locations. CONCLUSION: Injury incident locations can be categorized into distinguishable classes with varying mortality risk. Identification of location classes may be useful for targeted primary prevention and treatment interventions, both by identifying geographic areas with the highest risk of injury mortality and by identifying patterns of individual risk within location classes. LEVEL OF EVIDENCE: Prognostic and epidemiological, level III.
Authors: Stephen K Epstein; Jonathan L Burstein; Randall B Case; Angela F Gardner; Sanford H Herman; Jon Mark Hirshon; John W Jermyn; Mary Pat McKay; James C Mitchiner; William P Sullivan; Mary Jo Wagner; Susan Beer; Laura Tiberi; Craig Price; Ron Cunningham; Dean Wilkerson; Marilyn Bromley; Marjorie Geist; Laura Gore; Cynthia A Singh; Gordon Wheeler; Stacy F Gleason; Jennifer Decker; Valerie M Gwinner; Renee H Schwalberg Journal: Ann Emerg Med Date: 2009-01 Impact factor: 5.721
Authors: Jeffrey A Butts; Caterina Gouvis Roman; Lindsay Bostwick; Jeremy R Porter Journal: Annu Rev Public Health Date: 2015-01-07 Impact factor: 21.981
Authors: Howard K Mell; Shannon N Mumma; Brian Hiestand; Brendan G Carr; Tara Holland; Jason Stopyra Journal: JAMA Surg Date: 2017-10-01 Impact factor: 14.766
Authors: Charles C Branas; Ellen J MacKenzie; Justin C Williams; C William Schwab; Harry M Teter; Marie C Flanigan; Alan J Blatt; Charles S ReVelle Journal: JAMA Date: 2005-06-01 Impact factor: 56.272
Authors: Brendan G Carr; Charles C Branas; Joshua P Metlay; Ashley F Sullivan; Carlos A Camargo Journal: Ann Emerg Med Date: 2009-02-07 Impact factor: 5.721
Authors: Emily Grenn; Matthew Kutcher; William B Hillegass; Chinenye Iwuchukwu; Amber Kyle; Stephen Bruehl; Burel Goodin; Hector Myers; Uma Rao; Subodh Nag; Kerry Kinney; Harrison Dickens; Matthew C Morris Journal: J Trauma Acute Care Surg Date: 2021-12-20 Impact factor: 3.697
Authors: Cheryl K Zogg; Robert D Becher; Michael K Dalton; Sameer A Hirji; Kimberly A Davis; Ali Salim; Zara Cooper; Molly P Jarman Journal: J Surg Res Date: 2022-03-07 Impact factor: 2.417
Authors: Anelia A Y Kassi; Anil K Mahavadi; Angelica Clavijo; Daniela Caliz; Stephanie W Lee; Aminul I Ahmed; Shoji Yokobori; Zhen Hu; Markus S Spurlock; Joseph M Wasserman; Karla N Rivera; Samuel Nodal; Henry R Powell; Long Di; Rolando Torres; Lai Yee Leung; Andres Mariano Rubiano; Ross M Bullock; Shyam Gajavelli Journal: Front Neurol Date: 2019-01-17 Impact factor: 4.086
Authors: Zar Popal; Eva Berkeveld; Kees Jan Ponsen; Harold Goei; Frank W Bloemers; Wietse P Zuidema; Georgios F Giannakopoulos Journal: Eur J Trauma Emerg Surg Date: 2019-09-04 Impact factor: 3.693
Authors: David Watson; Blair Benton; Elizabeth Ablah; Kelly Lightwine; Ronda Lusk; Hayrettin Okut; Thuy Bui; James M Haan Journal: Kans J Med Date: 2021-01-21