Flory L Nkoy1, Bryan L Stone2, Andrew J Knighton3, Bernhard A Fassl2, Joseph M Johnson4, Christopher G Maloney2, Lucy A Savitz3. 1. Division of Pediatric Inpatient Medicine, University of Utah, Salt Lake City, Utah; flory.nkoy@hsc.utah.edu. 2. Division of Pediatric Inpatient Medicine, University of Utah, Salt Lake City, Utah. 3. Institute for Healthcare Delivery Research; and. 4. Utah Valley Hospital, Intermountain Healthcare, Salt Lake City, Utah.
Abstract
OBJECTIVES: Collecting social determinants data is challenging. We assigned patients a neighborhood-level social determinant measure, the area of deprivation index (ADI), by using census data. We then assessed the association between neighborhood deprivation and asthma hospitalization outcomes and tested the influence of insurance coverage. METHODS: A retrospective cohort study of children 2 to 17 years old admitted for asthma at 8 hospitals. An administrative database was used to collect patient data, including hospitalization outcomes and neighborhood deprivation status (ADI scores), which were grouped into quintiles (ADI 1, the least deprived neighborhoods; ADI 5, the most deprived neighborhoods). We used multivariable models, adjusting for covariates, to assess the associations and added a neighborhood deprivation status and insurance coverage interaction term. RESULTS: A total of 2270 children (median age 5 years; 40.6% girls) were admitted for asthma. We noted that higher ADI quintiles were associated with greater length of stay, higher cost, and more asthma readmissions (P < .05 for most quintiles). Having public insurance was independently associated with greater length of stay (β: 1.171; 95% confidence interval [CI]: 1.117-1.228; P < .001), higher cost (β: 1.147; 95% CI: 1.093-1.203; P < .001), and higher readmission odds (odds ratio: 1.81; 95% CI: 1.46-2.24; P < .001). There was a significant deprivation-insurance effect modification, with public insurance associated with worse outcomes and private insurance with better outcomes across ADI quintiles (P < .05 for most combinations). CONCLUSIONS: Neighborhood-level ADI measure is associated with asthma hospitalization outcomes. However, insurance coverage modifies this relationship and needs to be considered when using the ADI to identify and address health care disparities.
OBJECTIVES: Collecting social determinants data is challenging. We assigned patients a neighborhood-level social determinant measure, the area of deprivation index (ADI), by using census data. We then assessed the association between neighborhood deprivation and asthma hospitalization outcomes and tested the influence of insurance coverage. METHODS: A retrospective cohort study of children 2 to 17 years old admitted for asthma at 8 hospitals. An administrative database was used to collect patient data, including hospitalization outcomes and neighborhood deprivation status (ADI scores), which were grouped into quintiles (ADI 1, the least deprived neighborhoods; ADI 5, the most deprived neighborhoods). We used multivariable models, adjusting for covariates, to assess the associations and added a neighborhood deprivation status and insurance coverage interaction term. RESULTS: A total of 2270 children (median age 5 years; 40.6% girls) were admitted for asthma. We noted that higher ADI quintiles were associated with greater length of stay, higher cost, and more asthma readmissions (P < .05 for most quintiles). Having public insurance was independently associated with greater length of stay (β: 1.171; 95% confidence interval [CI]: 1.117-1.228; P < .001), higher cost (β: 1.147; 95% CI: 1.093-1.203; P < .001), and higher readmission odds (odds ratio: 1.81; 95% CI: 1.46-2.24; P < .001). There was a significant deprivation-insurance effect modification, with public insurance associated with worse outcomes and private insurance with better outcomes across ADI quintiles (P < .05 for most combinations). CONCLUSIONS: Neighborhood-level ADI measure is associated with asthma hospitalization outcomes. However, insurance coverage modifies this relationship and needs to be considered when using the ADI to identify and address health care disparities.
Authors: Emma Banwell; Joseph M Collaco; Gabriela R Oates; Jessica L Rice; Lucia D Juarez; Lisa R Young; Sharon A McGrath-Morrow Journal: Pediatr Pulmonol Date: 2022-05-21
Authors: Celestine H Yeung Gregerson; Amanda V Bakian; Jacob Wilkes; Andrew J Knighton; Flory Nkoy; Matthew Sweney; Francis M Filloux; Joshua L Bonkowsky Journal: J Child Neurol Date: 2019-09-10 Impact factor: 1.987
Authors: Sharad I Wadhwani; Andrew F Beck; John Bucuvalas; Laura Gottlieb; Uma Kotagal; Jennifer C Lai Journal: Am J Transplant Date: 2020-02-06 Impact factor: 8.086
Authors: Annie Gjelsvik; Michelle L Rogers; Aris Garro; Adam Sullivan; Daphne Koinis-Mitchell; Elizabeth L McQuaid; Raul Smego; Patrick M Vivier Journal: Prev Chronic Dis Date: 2019-05-30 Impact factor: 2.830
Authors: Jennifer A Lucas; Miguel Marino; Sophia Giebultowicz; Katie Fankhauser; Shakira F Suglia; Steffani R Bailey; Andrew Bazemore; John Heintzman Journal: Fam Med Community Health Date: 2021-07