Amanda M Lam, Mariana C Singletary, Theresa Cullen
{"title":"一种基于地理信息系统软件的方法，用于识别属于地址定义社区的公共卫生数据。","authors":"Amanda M Lam, Mariana C Singletary, Theresa Cullen","doi":"10.1093/jamia/ocae235","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This communication presents the results of defining a tribal health jurisdiction by a combination of tribal affiliation and case address.</p><p><strong>Methods: </strong>Through a county-tribal partnership, GIS software and custom code were used to extract tribal data from county data by identifying reservation addresses in county extracts of COVID-19 case records from December 30, 2019, to December 31, 2022 (n = 374,653) and COVID-19 vaccination records from December 1, 2020, to April 18, 2023 (n = 2,355,058).</p><p><strong>Results: </strong>The tool identified 1.91 times as many case records and 3.76 times as many vaccination records as filtering by tribal affiliation alone.</p><p><strong>Discussion and conclusion: </strong>This method of identifying communities by patient address, in combination with tribal affiliation and enrollment, can help tribal health jurisdictions attain equitable access to public health data, when done in partnership with a data sharing agreement. This methodology has potential applications for other populations underrepresented in public health and clinical research.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":null,"pages":null},"PeriodicalIF":4.7000,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A GIS software-based method to identify public health data belonging to address-defined communities.\",\"authors\":\"Amanda M Lam, Mariana C Singletary, Theresa Cullen\",\"doi\":\"10.1093/jamia/ocae235\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>This communication presents the results of defining a tribal health jurisdiction by a combination of tribal affiliation and case address.</p><p><strong>Methods: </strong>Through a county-tribal partnership, GIS software and custom code were used to extract tribal data from county data by identifying reservation addresses in county extracts of COVID-19 case records from December 30, 2019, to December 31, 2022 (n = 374,653) and COVID-19 vaccination records from December 1, 2020, to April 18, 2023 (n = 2,355,058).</p><p><strong>Results: </strong>The tool identified 1.91 times as many case records and 3.76 times as many vaccination records as filtering by tribal affiliation alone.</p><p><strong>Discussion and conclusion: </strong>This method of identifying communities by patient address, in combination with tribal affiliation and enrollment, can help tribal health jurisdictions attain equitable access to public health data, when done in partnership with a data sharing agreement. This methodology has potential applications for other populations underrepresented in public health and clinical research.</p>\",\"PeriodicalId\":50016,\"journal\":{\"name\":\"Journal of the American Medical Informatics Association\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American Medical Informatics Association\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1093/jamia/ocae235\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Medical Informatics Association","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1093/jamia/ocae235","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
A GIS software-based method to identify public health data belonging to address-defined communities.
Objective: This communication presents the results of defining a tribal health jurisdiction by a combination of tribal affiliation and case address.
Methods: Through a county-tribal partnership, GIS software and custom code were used to extract tribal data from county data by identifying reservation addresses in county extracts of COVID-19 case records from December 30, 2019, to December 31, 2022 (n = 374,653) and COVID-19 vaccination records from December 1, 2020, to April 18, 2023 (n = 2,355,058).
Results: The tool identified 1.91 times as many case records and 3.76 times as many vaccination records as filtering by tribal affiliation alone.
Discussion and conclusion: This method of identifying communities by patient address, in combination with tribal affiliation and enrollment, can help tribal health jurisdictions attain equitable access to public health data, when done in partnership with a data sharing agreement. This methodology has potential applications for other populations underrepresented in public health and clinical research.
期刊介绍：
JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.
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