Fares Qeadan, Erin F Madden, Kevin English, Kamilla L Venner, Benjamin Tingey, Jamie Egbert, Feli Anne S Hipol
{"title":"利用 Cerner Real-World Data™ 数据库量化美国印第安人和阿拉斯加原住民阿片类药物使用障碍和非致命性阿片类药物过量的负担。","authors":"Fares Qeadan, Erin F Madden, Kevin English, Kamilla L Venner, Benjamin Tingey, Jamie Egbert, Feli Anne S Hipol","doi":"10.1007/s40615-024-02084-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study evaluated the prevalence and incidence of opioid use disorder (OUD), rates of opioid overdose (OD), and rates of non-fatal (NF) OD in American Indian/Alaskan Native (AI/AN) populations.</p><p><strong>Methods: </strong>We used de-identified patient data from Oracle Cerner Real-World Data™. Rates were estimated over time, and stratified by sex, age, marital status, insurance, and region. Mann-Kendall trend tests and Theil-Sen slopes assessed changes over time for each group while autoregressive modeling assessed differences between groups.</p><p><strong>Results: </strong>The study identified trends in OUD and OD among 700,225 AI/AN patients aged 12 and above. Between 2012 and 2022, there was a significant upward trend in both OUD and OD rates (p < 0.05) , with OUD diagnosed in 1.75% and OD in 0.38% of the population. The Western region of the US exhibited the highest rates of OUD and OD. The 35-49 age group showed the highest rates of OUD, while the 12-34 age group had the highest rates of OD. Marital status analysis revealed higher rates of OUD and OD among separated, widowed, or single patients. Additionally, individuals with Medicare or Medicaid insurance demonstrated the highest rates of OUD and OD.</p><p><strong>Conclusion: </strong>Results show that rates of OUD, OD, and NF OD continue to rise among AI/AN individuals, with some regional and demographic variation. Our study provides foundational estimates of key AI/AN populations bearing greater burdens of opioid-related morbidity that federal, state, and tribal organizations can use to direct and develop targeted resources that can improve the health and well-being of AI/AN communities.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantifying the Burden of Opioid Use Disorder and Non-fatal Opioid Overdose in American Indian and Alaskan Native Populations Using the Cerner Real-World Data™ Database.\",\"authors\":\"Fares Qeadan, Erin F Madden, Kevin English, Kamilla L Venner, Benjamin Tingey, Jamie Egbert, Feli Anne S Hipol\",\"doi\":\"10.1007/s40615-024-02084-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>This study evaluated the prevalence and incidence of opioid use disorder (OUD), rates of opioid overdose (OD), and rates of non-fatal (NF) OD in American Indian/Alaskan Native (AI/AN) populations.</p><p><strong>Methods: </strong>We used de-identified patient data from Oracle Cerner Real-World Data™. Rates were estimated over time, and stratified by sex, age, marital status, insurance, and region. Mann-Kendall trend tests and Theil-Sen slopes assessed changes over time for each group while autoregressive modeling assessed differences between groups.</p><p><strong>Results: </strong>The study identified trends in OUD and OD among 700,225 AI/AN patients aged 12 and above. Between 2012 and 2022, there was a significant upward trend in both OUD and OD rates (p < 0.05) , with OUD diagnosed in 1.75% and OD in 0.38% of the population. The Western region of the US exhibited the highest rates of OUD and OD. The 35-49 age group showed the highest rates of OUD, while the 12-34 age group had the highest rates of OD. Marital status analysis revealed higher rates of OUD and OD among separated, widowed, or single patients. 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引用次数: 0
摘要
研究目的本研究评估了美国印第安人/阿拉斯加原住民(AI/AN)人群中阿片类药物使用障碍(OUD)的流行率和发病率、阿片类药物过量(OD)率以及非致命性(NF)OD 率:我们使用了来自 Oracle Cerner Real-World Data™ 的去身份化患者数据。我们估算了一段时间内的发病率,并按性别、年龄、婚姻状况、保险和地区进行了分层。Mann-Kendall 趋势检验和 Theil-Sen 斜率评估了各组随时间的变化,而自回归模型则评估了组间的差异:研究发现,在 700,225 名 12 岁及以上的美国原住民/印第安人患者中,OUD 和 OD 呈上升趋势。2012 年至 2022 年间,OUD 和 OD 的发病率均呈显著上升趋势(p < 0.05),其中 1.75% 的人口确诊为 OUD,0.38% 的人口确诊为 OD。美国西部地区的 OUD 和 OD 患病率最高。35-49 岁年龄组的 OUD 患病率最高,而 12-34 岁年龄组的 OD 患病率最高。婚姻状况分析显示,分居、丧偶或单身患者的 OUD 和 OD 感染率较高。此外,有医疗保险或医疗补助保险的人的 OUD 和 OD 率最高:研究结果表明,亚裔美国人/印第安人的 OUD、OD 和 NF OD 患病率持续上升,但存在一定的地区和人口统计学差异。我们的研究提供了对阿片类相关发病率负担较重的主要亚裔美国人/印第安人群体的基本估计,联邦、州和部落组织可利用这些估计来指导和开发有针对性的资源,从而改善亚裔美国人/印第安人社区的健康和福祉。
Quantifying the Burden of Opioid Use Disorder and Non-fatal Opioid Overdose in American Indian and Alaskan Native Populations Using the Cerner Real-World Data™ Database.
Objective: This study evaluated the prevalence and incidence of opioid use disorder (OUD), rates of opioid overdose (OD), and rates of non-fatal (NF) OD in American Indian/Alaskan Native (AI/AN) populations.
Methods: We used de-identified patient data from Oracle Cerner Real-World Data™. Rates were estimated over time, and stratified by sex, age, marital status, insurance, and region. Mann-Kendall trend tests and Theil-Sen slopes assessed changes over time for each group while autoregressive modeling assessed differences between groups.
Results: The study identified trends in OUD and OD among 700,225 AI/AN patients aged 12 and above. Between 2012 and 2022, there was a significant upward trend in both OUD and OD rates (p < 0.05) , with OUD diagnosed in 1.75% and OD in 0.38% of the population. The Western region of the US exhibited the highest rates of OUD and OD. The 35-49 age group showed the highest rates of OUD, while the 12-34 age group had the highest rates of OD. Marital status analysis revealed higher rates of OUD and OD among separated, widowed, or single patients. Additionally, individuals with Medicare or Medicaid insurance demonstrated the highest rates of OUD and OD.
Conclusion: Results show that rates of OUD, OD, and NF OD continue to rise among AI/AN individuals, with some regional and demographic variation. Our study provides foundational estimates of key AI/AN populations bearing greater burdens of opioid-related morbidity that federal, state, and tribal organizations can use to direct and develop targeted resources that can improve the health and well-being of AI/AN communities.