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首页> 外文期刊>BMC Cardiovascular Disorders >Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population
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Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population

机译：在联邦合格的社区保健中心患者人口中评估社会需求评估数据的社会需求评估数据协会

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Health systems are increasingly using standardized social needs screening and response protocols including the Protocol for Responding to and Assessing Patients’ Risks, Assets, and Experiences (PRAPARE) to improve population health and equity; despite established relationships between the social determinants of health and health outcomes, little is known about the associations between standardized social needs assessment information and patients’ clinical condition. In this cross-sectional study, we examined the relationship between social needs screening assessment data and measures of cardiometabolic clinical health from electronic health records data using two modelling approaches: a backward stepwise logistic regression and a least absolute selection and shrinkage operation (LASSO) logistic regression. Primary outcomes were dichotomized cardiometabolic measures related to obesity, hypertension, and atherosclerotic cardiovascular disease (ASCVD) 10-year risk. Nested models were built to evaluate the utility of social needs assessment data from PRAPARE for risk prediction, stratification, and population health management. Social needs related to lack of housing, unemployment, stress, access to medicine or health care, and inability to afford phone service were consistently associated with cardiometabolic risk across models. Model fit, as measured by the c-statistic, was poor for predicting obesity (logistic?=?0.586; LASSO?=?0.587), moderate for stage 1 hypertension (logistic?=?0.703; LASSO?=?0.688), and high for borderline ASCVD risk (logistic?=?0.954; LASSO?=?0.950). Associations between social needs assessment data and clinical outcomes vary by cardiometabolic condition. Social needs assessment data may be useful for prospectively identifying patients at heightened cardiometabolic risk; however, there are limits to the utility of social needs data for improving predictive performance.
机译：卫生系统越来越多地使用标准化的社会需求筛选和响应协议，包括响应和评估患者风险，资产和经验（PRAPARE）的议定书，以改善人口健康和股权;尽管建立了健康和健康结果的社会决定因素之间的关系，但对于标准化社会需求评估信息和患者的临床状况之间的协会知之甚少。在这种横断面研究中，我们研究了使用两个建模方法的电子健康记录数据的社会需求筛选数据和心细素临床健康的措施之间的关系：向后逐步逻辑回归和绝对的选择和收缩操作（套索）物流回归。主要结果是与肥胖，高血压和动脉粥样硬化疾病（ASCVD）10年风险相关的二分型心肌措施。建立嵌套模型，以评估社会需求评估数据的效用，从普拉帕雷进行风险预测，分层和人口健康管理。与住房，失业率，压力，医学或医疗保健有关的社会需求，以及无法接受电话服务，始终如一地与模型的心脏浮动风险相关联。由C统计量测量的模型适合用于预测肥胖症（物流？= 0.586;套索？= 0.587），适度为第1阶段的高血压（物流？=？0.703;套索？= 0.688），和边界内ASCVD风险高（Logistic？= 0.954;套索？=？0.950）。社会需求评估数据与临床结果之间的关联因心脏异常条件而异。社会需求评估数据可能对前瞻性识别患者的心脏素质风险预期鉴定;但是，社会需求数据的效用限制了提高预测性能的限制。

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