Noel C Barragan, Gabrielle Green, Matt Moyer, Gerardo Cruz, Sarine Pogosyan, Tony Kuo
{"title":"社区医疗中心目前使用算法逻辑识别未确诊高血压患者的做法和态度。","authors":"Noel C Barragan, Gabrielle Green, Matt Moyer, Gerardo Cruz, Sarine Pogosyan, Tony Kuo","doi":"10.1097/PHH.0000000000001927","DOIUrl":null,"url":null,"abstract":"<p><p>Treating patients with uncontrolled hypertension is a powerful intervention for reducing the risk of heart attack and stroke. Leveraging health information technology to identify patients with undiagnosed hypertension using algorithmic logic can be an effective approach for reaching hypertensive patients who may otherwise be overlooked. Despite evidence that this strategy can support favorable cardiovascular health outcomes in the safety-net healthcare setting, little is known about its implementation outside of targeted practice and research environments. In 2021-2022, Community Clinic Association of Los Angeles County and the Los Angeles County Department of Public Health collaborated on a mixed methods, organizational assessment of community health centers to better understand their practices and attitudes toward the use of algorithmic logic to identify patients with undiagnosed hypertension. Results from the assessment suggest that awareness and use of this approach are limited; numerous challenges are associated with its adoption and implementation.</p>","PeriodicalId":47855,"journal":{"name":"Journal of Public Health Management and Practice","volume":"30 ","pages":"S119-S123"},"PeriodicalIF":2.2000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Current Practices and Attitudes of Community Health Centers Toward the Use of Algorithmic Logic to Identify Patients with Undiagnosed Hypertension.\",\"authors\":\"Noel C Barragan, Gabrielle Green, Matt Moyer, Gerardo Cruz, Sarine Pogosyan, Tony Kuo\",\"doi\":\"10.1097/PHH.0000000000001927\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Treating patients with uncontrolled hypertension is a powerful intervention for reducing the risk of heart attack and stroke. Leveraging health information technology to identify patients with undiagnosed hypertension using algorithmic logic can be an effective approach for reaching hypertensive patients who may otherwise be overlooked. Despite evidence that this strategy can support favorable cardiovascular health outcomes in the safety-net healthcare setting, little is known about its implementation outside of targeted practice and research environments. In 2021-2022, Community Clinic Association of Los Angeles County and the Los Angeles County Department of Public Health collaborated on a mixed methods, organizational assessment of community health centers to better understand their practices and attitudes toward the use of algorithmic logic to identify patients with undiagnosed hypertension. Results from the assessment suggest that awareness and use of this approach are limited; numerous challenges are associated with its adoption and implementation.</p>\",\"PeriodicalId\":47855,\"journal\":{\"name\":\"Journal of Public Health Management and Practice\",\"volume\":\"30 \",\"pages\":\"S119-S123\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Public Health Management and Practice\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/PHH.0000000000001927\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/22 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Public Health Management and Practice","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/PHH.0000000000001927","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/22 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Current Practices and Attitudes of Community Health Centers Toward the Use of Algorithmic Logic to Identify Patients with Undiagnosed Hypertension.
Treating patients with uncontrolled hypertension is a powerful intervention for reducing the risk of heart attack and stroke. Leveraging health information technology to identify patients with undiagnosed hypertension using algorithmic logic can be an effective approach for reaching hypertensive patients who may otherwise be overlooked. Despite evidence that this strategy can support favorable cardiovascular health outcomes in the safety-net healthcare setting, little is known about its implementation outside of targeted practice and research environments. In 2021-2022, Community Clinic Association of Los Angeles County and the Los Angeles County Department of Public Health collaborated on a mixed methods, organizational assessment of community health centers to better understand their practices and attitudes toward the use of algorithmic logic to identify patients with undiagnosed hypertension. Results from the assessment suggest that awareness and use of this approach are limited; numerous challenges are associated with its adoption and implementation.
期刊介绍:
Journal of Public Health Management and Practice publishes articles which focus on evidence based public health practice and research. The journal is a bi-monthly peer-reviewed publication guided by a multidisciplinary editorial board of administrators, practitioners and scientists. Journal of Public Health Management and Practice publishes in a wide range of population health topics including research to practice; emergency preparedness; bioterrorism; infectious disease surveillance; environmental health; community health assessment, chronic disease prevention and health promotion, and academic-practice linkages.