Multilevel Determinants of Racial/Ethnic Disparities in Lung Cancer Screening Utilization
肺癌筛查利用中种族/民族差异的多层次决定因素
基本信息
- 批准号:10640224
- 负责人:
- 金额:$ 53.68万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-06-07 至 2026-04-30
- 项目状态:未结题
- 来源:
- 关键词:AddressAdultAffectAgeAttitudeAwarenessBehaviorBeliefBlack PopulationsBlack raceClinicalClinical ServicesContinuity of Patient CareCounselingDataData SourcesDiseaseDisparityDisparity populationDocumentationElectronic Health RecordEligibility DeterminationEnrollmentEnsureEquityEthnic OriginEthnic PopulationFosteringHealthHealth InsuranceHealth PersonnelHealth PrioritiesHealth ServicesHealth care facilityHealth systemHealthcareHouseholdIndividualInfluentialsIntegrated Health Care SystemsInterventionKnowledgeLanguageLinkMalignant neoplasm of lungMeasuresMedicalMedicareMinorityNeighborhoodsPatient Self-ReportPatientsPatternPharmacotherapyPopulationPopulation HeterogeneityProcessProviderQuestionnairesRaceRecommendationRecording of previous eventsRegistriesReportingResourcesScreening for cancerServicesSmokeSmokingSmoking HistorySocioeconomic StatusSolidSurveysTarget PopulationsTimeTrustUnited States Preventative Services Task ForceVisitWorkcancer caredistrustethnic disparityethnic minorityfollow-upformer smokerhigh risk populationimplementation barriersimprovedinsightinsurance claimsknowledge baselow dose computed tomographylung cancer screeningmortalitymultilevel analysisoutreachpublic health relevanceracial determinantracial disparityracial minorityracial populationresidencescreeningsexshared decision makingsmoking cessationsocial stigmasociodemographicsstemtrenduptakewillingness
项目摘要
ABSTRACT
Since December 2013, the U.S. Preventive Services Task Force has recommended lung cancer screening
(LCS) with low-dose computed tomography for high-risk individuals with a smoking history, affording a major
opportunity to reduce lung cancer mortality, especially in racial/ethnic and disadvantaged populations that are
disproportionately affected by the disease. Yet, there is concern that LCS is not being delivered effectively and
equitably, given its many unique implementation challenges. LCS utilization remains low. Emerging data also
suggest poorer uptake of LCS in Black versus white individuals. Even less is known about racial/ethnic
disparities in smoking cessation, although smoking cessation counseling is an integral component of the LCS
process. Identifying factors associated with LCS utilization, particularly those that contribute to racial/ethnic
disparities, is thus critical to deliver LCS optimally. Following well-established conceptual frameworks in which
multiple levels of influence affect cancer screening behaviors, we posit that LCS utilization is affected by
individual-, neighborhood-, provider-, and health facility-level factors. Studies to identify multilevel factors
associated with LCS utilization have been limited to date, due in part to known constraints in the data sources
available to evaluate LCS, especially at steps before screening initiation. Electronic health records (EHR) are a
recognized but largely untapped data source to address LCS. Compared to other data sources, integrated
health system EHRs capture comprehensive longitudinal data on clinical services from a defined population,
providing a robust and efficient means to investigate multilevel determinants of disparities in LCS utilization. In
our foundational work using EHR data to characterize early patterns of LCS utilization, we found evidence of
racial/ethnic disparities in the process after screening initiation. In this proposal, we aim to identify and
understand multilevel determinants of racial/ethnic disparities in LCS utilization, before and up through
screening initiation. Specifically, we will determine the influence of factors at the individual, neighborhood,
provider, and facility levels on disparities in LCS utilization, starting from the opportunity to be screened, as
measured by the completeness of EHR documentation on smoking history to assess LCS eligibility (Aim 1),
followed by LCS referral and initiation (Aim 2) and referral and use of smoking cessation services (Aim 3). We
will compile, link, and analyze available EHR, questionnaire, and geospatial data from a sociodemographically
diverse population of over 1.3 million adults in an integrated health system from 2014 to 2023. Overall, our
multilevel analysis will generate valuable insight into the major and modifiable drivers of racial/ethnic disparities
at key steps in LCS from eligibility assessment to screening initiation. These findings will provide an empirical
basis to guide health systems in developing multilevel interventions that improve LCS outreach and utilization,
both effectively and equitably.
抽象的
自2013年12月以来,美国预防服务工作队建议肺癌筛查
(LCS)具有低剂量计算机断层扫描,可为具有吸烟史的高风险个体提供专业
降低肺癌死亡率的机会,尤其是在种族/种族和处境不利的人群中
受该疾病的影响不成比例。但是,人们担心LCS并未有效地交付
鉴于其许多独特的实施挑战。 LCS利用率保持较低。新兴数据也是如此
表明黑人与白人个体的LC摄取较差。关于种族/种族的知之甚少
尽管戒烟咨询是LCS的组成部分,但戒烟的差异是
过程。识别与LCS利用相关的因素,尤其是那些有助于种族/种族的因素
因此,差异对于最佳提供LC至关重要。遵循建立良好的概念框架
多种影响影响癌症筛查行为,我们认为LCS利用受到
个人,邻里,提供者和医疗机构级别的因素。研究以识别多层因素
与LCS利用相关联已限于迄今为止,部分归因于数据源中的已知约束
可用于评估LCS,尤其是在筛选启动之前的步骤中。电子健康记录(EHR)是
公认的,但在很大程度上未开发的数据源可以解决LCS。与其他数据源相比
卫生系统EHRS从定义人群中获取有关临床服务的全面纵向数据,
提供强大而有效的手段来研究LCS利用率中差异的多层次决定因素。在
我们使用EHR数据来表征LCS利用率的早期模式的基础工作,我们发现了证据
筛查开始后的种族/种族差异。在此提案中,我们旨在确定和
在LCS利用率中,了解种族/种族差异的多层次决定因素,
筛选开始。具体而言,我们将确定因素对个人,邻里的影响,
提供者以及LCS利用率差异的设施水平,从筛查的机会开始,
通过对吸烟史的EHR文档的完整性来衡量,以评估LCS资格(AIM 1),
其次是LCS推荐和启动(AIM 2)以及戒烟服务的推荐和使用(AIM 3)。我们
将从社会人口统计学上编译,链接和分析可用的EHR,问卷和地理空间数据
从2014年到2023年,在综合卫生系统中有超过130万成年人的多样化人口。总体而言,我们
多层分析将对种族/种族差异的主要且可修改的驱动因素产生宝贵的见解
从资格评估到筛选开始的LC中的关键步骤。这些发现将提供经验
指导卫生系统开发多层干预措施以改善LCS外展和利用的基础,
有效和公平。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Clinical Adjuncts to Lung Cancer Screening: A Narrative Review.
肺癌筛查的临床辅助:叙述性回顾。
- DOI:10.1016/j.thorsurg.2023.03.002
- 发表时间:2023
- 期刊:
- 影响因子:2.1
- 作者:Susai,CynthiaJ;Velotta,JeffreyB;Sakoda,LoriC
- 通讯作者:Sakoda,LoriC
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Lori Sakoda其他文献
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{{ truncateString('Lori Sakoda', 18)}}的其他基金
Multilevel Determinants of Racial/Ethnic Disparities in Lung Cancer Screening Utilization
肺癌筛查利用中种族/民族差异的多层次决定因素
- 批准号:
10443477 - 财政年份:2022
- 资助金额:
$ 53.68万 - 项目类别:
Evaluating a Risk Prediction Model for Lung Cancer
评估肺癌风险预测模型
- 批准号:
9271910 - 财政年份:2015
- 资助金额:
$ 53.68万 - 项目类别:
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