{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T09:59:08Z","timestamp":1756461548670,"version":"3.41.0"},"reference-count":78,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T00:00:00Z","timestamp":1698278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Manage. Inf. Syst."],"published-print":{"date-parts":[[2023,12,31]]},"abstract":"<jats:p>Emergency room (ER) admissions are the front door for the utilization of a community's health resources and serve as a valuable proxy for a community health system's capacity. While recent research suggests that social determinants of health (SDOH) are important predictors of patient health outcomes, their impact on ER utilization during the COVID-19 pandemic is not well understood. Further, the role of hospital information integration in moderating the impact of SDOH on ER utilization has not received adequate attention. Utilizing longitudinal claims data from a regional health information exchange spanning 6 years including the COVID-19 period, we study how SDOH affects ER utilization and whether effective integration of patient health information across hospitals can moderate its impact. Our results suggest that a patient's economic well-being significantly reduces future ER utilization. The magnitude of this relationship is significant when patients are treated at hospitals with high information integration but is weaker when patients receive care at hospitals with lower levels of information integration. Instead, patients' family and social support can reduce ER utilization when they are treated at hospitals with low information integration. In other words, different dimensions of SDOH are important in low versus high information integration conditions. Furthermore, predictive modeling shows that patient visit type and prior visit history can significantly improve the predictive accuracy of ER utilization. Our research implications support efforts to develop national standards for the collection and sharing of SDOH data and their use and interpretation for clinical decision making by healthcare providers and policy makers.<\/jats:p>","DOI":"10.1145\/3583077","type":"journal-article","created":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T13:19:46Z","timestamp":1675775986000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Social Determinants of Health and ER Utilization: Role of Information Integration during COVID-19"],"prefix":"10.1145","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1111-3540","authenticated-orcid":false,"given":"Tianjian","family":"Guo","sequence":"first","affiliation":[{"name":"McCombs School of Business, UT Austin"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4265-5780","authenticated-orcid":false,"given":"Indranil","family":"Bardhan","sequence":"additional","affiliation":[{"name":"McCombs School of Business, UT Austin"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8946-0622","authenticated-orcid":false,"given":"Anjum","family":"Khurshid","sequence":"additional","affiliation":[{"name":"Department of Population Medicine, Harvard University"}]}],"member":"320","published-online":{"date-parts":[[2023,10,26]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"Centers for Medicare and Medicaid Services. 2022. 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