Kimberly C Arthur1, Barbara A Lucenko2, Irina V Sharkova2, Jingping Xing2, Rita Mangione-Smith3,4. 1. Seattle Children's Research Institute, Seattle, Washington kimberly.arthur@seattlechildrens.org. 2. Washington State Department of Social and Health Services, Division of Research and Data Analysis, Olympia, Washington. 3. Seattle Children's Research Institute, Seattle, Washington. 4. University of Washington Department of Pediatrics, Seattle, Washington.
Abstract
PURPOSE: Screening for social determinants of health is challenging but critically important for optimizing child health outcomes. We aimed to test the feasibility of using an integrated state agency administrative database to identify social complexity risk factors and examined their relationship to emergency department (ED) use. METHODS: We conducted a retrospective cohort study among children younger than 18 years with Washington State Medicaid insurance coverage (N = 505,367). We linked child and parent administrative data for this cohort to identify a set of social complexity risk factors, such as poverty and parent mental illness, that have either a known or hypothesized association with suboptimal health care use. Using multivariate analyses, we examined associations of each risk factor and of number of risk factors with the rate of ED use. RESULTS: Nine of 11 identifiable social complexity risk factors were associated with a higher rate of ED use. Additionally, the rate increased as the number of risk factors increased from 0 to 5 or more, reaching approximately twice the rate when 5 or more risk factors were present in children aged younger than 5 years (incidence rate ratio = 1.92; 95% CI, 1.85-2.00) and in children aged 5 to 17 years (incidence rate ratio = 2.06; 95% CI, 1.99-2.14). CONCLUSIONS: State administrative data can be used to identify social complexity risk factors associated with higher rates of ED use among Medicaid-insured children. State agencies could give primary care medical homes a social risk flag or score to facilitate targeted screening and identification of needed resources, potentially preventing future unnecessary ED use in this vulnerable population of children.
PURPOSE: Screening for social determinants of health is challenging but critically important for optimizing child health outcomes. We aimed to test the feasibility of using an integrated state agency administrative database to identify social complexity risk factors and examined their relationship to emergency department (ED) use. METHODS: We conducted a retrospective cohort study among children younger than 18 years with Washington State Medicaid insurance coverage (N = 505,367). We linked child and parent administrative data for this cohort to identify a set of social complexity risk factors, such as poverty and parent mental illness, that have either a known or hypothesized association with suboptimal health care use. Using multivariate analyses, we examined associations of each risk factor and of number of risk factors with the rate of ED use. RESULTS: Nine of 11 identifiable social complexity risk factors were associated with a higher rate of ED use. Additionally, the rate increased as the number of risk factors increased from 0 to 5 or more, reaching approximately twice the rate when 5 or more risk factors were present in children aged younger than 5 years (incidence rate ratio = 1.92; 95% CI, 1.85-2.00) and in children aged 5 to 17 years (incidence rate ratio = 2.06; 95% CI, 1.99-2.14). CONCLUSIONS: State administrative data can be used to identify social complexity risk factors associated with higher rates of ED use among Medicaid-insured children. State agencies could give primary care medical homes a social risk flag or score to facilitate targeted screening and identification of needed resources, potentially preventing future unnecessary ED use in this vulnerable population of children.
Keywords:
access; adverse childhood experiences; and evaluation; health care quality; primary care; social determinants of health; vulnerable populations
Authors: Anna B Flynn; Kate E Fothergill; Holly C Wilcox; Elizabeth Coleclough; Russell Horwitz; Anne Ruble; Matthew D Burkey; Lawrence S Wissow Journal: Acad Pediatr Date: 2015 Sep-Oct Impact factor: 3.107
Authors: Jennifer E DeVoe; Andrew W Bazemore; Erika K Cottrell; Sonja Likumahuwa-Ackman; Jené Grandmont; Natalie Spach; Rachel Gold Journal: Ann Fam Med Date: 2016-03 Impact factor: 5.166
Authors: Tamara D Simon; Mary Lawrence Cawthon; Susan Stanford; Jean Popalisky; Dorothy Lyons; Peter Woodcox; Margaret Hood; Alex Y Chen; Rita Mangione-Smith Journal: Pediatrics Date: 2014-05-12 Impact factor: 7.124
Authors: Emalee G Flaherty; Richard Thompson; Howard Dubowitz; Elizabeth M Harvey; Diana J English; Laura J Proctor; Desmond K Runyan Journal: JAMA Pediatr Date: 2013-07 Impact factor: 16.193
Authors: Heather Angier; Sophia Giebultowicz; Jorge Kaufmann; John Heintzman; Jean O'Malley; Laura Moreno; Jennifer E DeVoe Journal: Medicine (Baltimore) Date: 2021-08-13 Impact factor: 1.817
Authors: Elizabeth Shenkman; Lindsay Thompson; Regina Bussing; Christopher B Forrest; Jennifer Woodard; Yijun Sun; Jasmine Mack; Kamila B Mistry; Matthew J Gurka Journal: Pediatrics Date: 2020-12-01 Impact factor: 7.124
Authors: Stanley Xu; Glenn K Goodrich; Kelly R Moore; Spero M Manson; Laura M Gottlieb; Danielle Hessler; Emily B Schroeder; John F Steiner Journal: Med Care Date: 2021-02-01 Impact factor: 3.178
Authors: Elham Hatef; Zachary Predmore; Elyse C Lasser; Hadi Kharrazi; Karin Nelson; Idamay Curtis; Stephan Fihn; Jonathan P Weiner Journal: AIMS Public Health Date: 2019-07-03