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. 2022 Mar 16;12:4554. doi: 10.1038/s41598-022-08344-4

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Data sources and linkage for modeling. Flow chart showing the data sources combined to create the dataset displayed. The data sources are displayed as three cylinders displaying the data linking between sources. The measures from each source are displayed as a rectangle linking to other cylinders. Patient-level HRSNs were collected in the AHC screening survey. Using survey demographic data, patients were mapped using a Master Patient Index database (MPI) to patient ID, demographics, diagnosis, and procedures in the EHR. Patients addresses provided in the survey and the EHR were geocoded to each patient’s address and corresponding Census tract. The geocoding is displayed as a diamond connected to the HRSN survey data measures.