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Impact of social determinants of health on improving the LACE index for 30-day unplanned readmission prediction
OBJECTIVE: Early and accurate prediction of patients at risk of readmission is key to reducing costs and improving outcomes. LACE is a widely used score to predict 30-day readmissions. We examine whether adding social determinants of health (SDOH) to LACE can improve its predictive performance. METH...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185729/ https://www.ncbi.nlm.nih.gov/pubmed/35702627 http://dx.doi.org/10.1093/jamiaopen/ooac046 |
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author | Belouali, Anas Bai, Haibin Raja, Kanimozhi Liu, Star Ding, Xiyu Kharrazi, Hadi |
author_facet | Belouali, Anas Bai, Haibin Raja, Kanimozhi Liu, Star Ding, Xiyu Kharrazi, Hadi |
author_sort | Belouali, Anas |
collection | PubMed |
description | OBJECTIVE: Early and accurate prediction of patients at risk of readmission is key to reducing costs and improving outcomes. LACE is a widely used score to predict 30-day readmissions. We examine whether adding social determinants of health (SDOH) to LACE can improve its predictive performance. METHODS: This is a retrospective study that included all inpatient encounters in the state of Maryland in 2019. We constructed predictive models by fitting Logistic Regression (LR) on LACE and different sets of SDOH predictors. We used the area under the curve (AUC) to evaluate discrimination and SHapley Additive exPlanations values to assess feature importance. RESULTS: Our study population included 316 558 patients of whom 35 431 (11.19%) patients were readmitted after 30 days. Readmitted patients had more challenges with individual-level SDOH and were more likely to reside in communities with poor SDOH conditions. Adding a combination of individual and community-level SDOH improved LACE performance from AUC = 0.698 (95% CI [0.695–0.7]; ref) to AUC = 0.708 (95% CI [0.705–0.71]; P < .001). The increase in AUC was highest in black patients (+1.6), patients aged 65 years or older (+1.4), and male patients (+1.4). DISCUSSION: We demonstrated the value of SDOH in improving the LACE index. Further, the additional predictive value of SDOH on readmission risk varies by subpopulations. Vulnerable populations like black patients and the elderly are likely to benefit more from the inclusion of SDOH in readmission prediction. CONCLUSION: These findings provide potential SDOH factors that health systems and policymakers can target to reduce overall readmissions. |
format | Online Article Text |
id | pubmed-9185729 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-91857292022-06-13 Impact of social determinants of health on improving the LACE index for 30-day unplanned readmission prediction Belouali, Anas Bai, Haibin Raja, Kanimozhi Liu, Star Ding, Xiyu Kharrazi, Hadi JAMIA Open Research and Applications OBJECTIVE: Early and accurate prediction of patients at risk of readmission is key to reducing costs and improving outcomes. LACE is a widely used score to predict 30-day readmissions. We examine whether adding social determinants of health (SDOH) to LACE can improve its predictive performance. METHODS: This is a retrospective study that included all inpatient encounters in the state of Maryland in 2019. We constructed predictive models by fitting Logistic Regression (LR) on LACE and different sets of SDOH predictors. We used the area under the curve (AUC) to evaluate discrimination and SHapley Additive exPlanations values to assess feature importance. RESULTS: Our study population included 316 558 patients of whom 35 431 (11.19%) patients were readmitted after 30 days. Readmitted patients had more challenges with individual-level SDOH and were more likely to reside in communities with poor SDOH conditions. Adding a combination of individual and community-level SDOH improved LACE performance from AUC = 0.698 (95% CI [0.695–0.7]; ref) to AUC = 0.708 (95% CI [0.705–0.71]; P < .001). The increase in AUC was highest in black patients (+1.6), patients aged 65 years or older (+1.4), and male patients (+1.4). DISCUSSION: We demonstrated the value of SDOH in improving the LACE index. Further, the additional predictive value of SDOH on readmission risk varies by subpopulations. Vulnerable populations like black patients and the elderly are likely to benefit more from the inclusion of SDOH in readmission prediction. CONCLUSION: These findings provide potential SDOH factors that health systems and policymakers can target to reduce overall readmissions. Oxford University Press 2022-06-10 /pmc/articles/PMC9185729/ /pubmed/35702627 http://dx.doi.org/10.1093/jamiaopen/ooac046 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research and Applications Belouali, Anas Bai, Haibin Raja, Kanimozhi Liu, Star Ding, Xiyu Kharrazi, Hadi Impact of social determinants of health on improving the LACE index for 30-day unplanned readmission prediction |
title | Impact of social determinants of health on improving the LACE index for 30-day unplanned readmission prediction |
title_full | Impact of social determinants of health on improving the LACE index for 30-day unplanned readmission prediction |
title_fullStr | Impact of social determinants of health on improving the LACE index for 30-day unplanned readmission prediction |
title_full_unstemmed | Impact of social determinants of health on improving the LACE index for 30-day unplanned readmission prediction |
title_short | Impact of social determinants of health on improving the LACE index for 30-day unplanned readmission prediction |
title_sort | impact of social determinants of health on improving the lace index for 30-day unplanned readmission prediction |
topic | Research and Applications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185729/ https://www.ncbi.nlm.nih.gov/pubmed/35702627 http://dx.doi.org/10.1093/jamiaopen/ooac046 |
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