Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population
Abstract Background 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 be...
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doaj-4e9b93f44a2d43398a1501ba6bc9cdf92021-07-18T11:06:09ZengBMCBMC Cardiovascular Disorders1471-22612021-07-0121111010.1186/s12872-021-02149-5Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient populationConnor Drake0Tyler Lian1Justin G. Trogdon2David Edelman3Howard Eisenson4Morris Weinberger5Kristin Reiter6Christopher M. Shea7Department of Population Health Sciences, Duke University School of MedicineDepartment of Population Health Sciences, Duke University School of MedicineDepartment of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel HillDepartment of Medicine, Duke University School of MedicineLincoln Community Health CenterDepartment of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel HillDepartment of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel HillDepartment of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel HillAbstract Background 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. Methods 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. Results 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). Conclusions 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.https://doi.org/10.1186/s12872-021-02149-5Social determinants of healthSocial needsPrimary carePredictive analyticsElectronic health record |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Connor Drake Tyler Lian Justin G. Trogdon David Edelman Howard Eisenson Morris Weinberger Kristin Reiter Christopher M. Shea |
spellingShingle |
Connor Drake Tyler Lian Justin G. Trogdon David Edelman Howard Eisenson Morris Weinberger Kristin Reiter Christopher M. Shea Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population BMC Cardiovascular Disorders Social determinants of health Social needs Primary care Predictive analytics Electronic health record |
author_facet |
Connor Drake Tyler Lian Justin G. Trogdon David Edelman Howard Eisenson Morris Weinberger Kristin Reiter Christopher M. Shea |
author_sort |
Connor Drake |
title |
Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population |
title_short |
Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population |
title_full |
Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population |
title_fullStr |
Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population |
title_full_unstemmed |
Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population |
title_sort |
evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population |
publisher |
BMC |
series |
BMC Cardiovascular Disorders |
issn |
1471-2261 |
publishDate |
2021-07-01 |
description |
Abstract Background 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. Methods 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. Results 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). Conclusions 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. |
topic |
Social determinants of health Social needs Primary care Predictive analytics Electronic health record |
url |
https://doi.org/10.1186/s12872-021-02149-5 |
work_keys_str_mv |
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