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There is a critical need to develop methods to identify children at high-risk for future exacerbation to allow targeted prevention measures. We sought to evaluate the utility of models using spatiotemporally resolved climatic data and individual electronic health records (EHR) in predicting pediatric asthma exacerbations.\n<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>We extracted retrospective EHR data for 5982 children with asthma who had an encounter within the Duke University Health System between January 1, 2014 and December 31, 2019. EHR data were linked to spatially resolved environmental data, and temporally resolved climate, pollution, allergen, and influenza case data. We used xgBoost to build predictive models of asthma exacerbation over 30\u2013180\u00a0day time horizons, and evaluated the contributions of different data types to model performance.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Models using readily available EHR data performed moderately well, as measured by the area under the receiver operating characteristic curve (AUC 0.730\u20130.742) over all three time horizons. Inclusion of spatial and temporal data did not significantly improve model performance. Generating a decision rule with a sensitivity of 70% produced a positive predictive value of 13.8% for 180\u00a0day outcomes but only 2.9% for 30\u00a0day outcomes.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>EHR data-based models perform moderately wellover a 30\u2013180\u00a0day time horizon to identify children who would benefit from asthma exacerbation prevention measures. Due to the low rate of exacerbations, longer-term models are likely to be most clinically useful.<\/jats:p>\n                <jats:p><jats:italic>Trial Registration<\/jats:italic>: Not applicable.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12911-022-01847-0","type":"journal-article","created":{"date-parts":[[2022,4,22]],"date-time":"2022-04-22T14:16:00Z","timestamp":1650636960000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models"],"prefix":"10.1186","volume":"22","author":[{"given":"Jillian H.","family":"Hurst","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Congwen","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haley P.","family":"Hostetler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohsen","family":"Ghiasi Gorveh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jason E.","family":"Lang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin A.","family":"Goldstein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,4,22]]},"reference":[{"key":"1847_CR1","unstructured":"Centers for Disease Control and Prevention. 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All experimental protocols were performed in accordance with relevant guidelines and regulations and approved by the Duke University Health System Internal Review Board.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"JEL received consulting fees serving on the Regeneron Pediatric Asthma Field Advisory Board. JHH, CZ, HPH, MGG, and BAG do not have any competing interests to declare.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"108"}}