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Looking beyond Administrative Health Care Data: The Role of Socioeconomic Status in Predicting Future High-cost Patients with Mental Health and Addiction

INTRODUCTION: Previous research has shown that the socioeconomic status (SES)–health gradient also extends to high-cost patients; however, little work has examined high-cost patients with mental illness and/or addiction. The objective of this study was to examine associations between individual-, ho...

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Autores principales: de Oliveira, Claire, Mondor, Luke, Wodchis, Walter P., Rosella, Laura C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892069/
https://www.ncbi.nlm.nih.gov/pubmed/33792407
http://dx.doi.org/10.1177/07067437211004882
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author de Oliveira, Claire
Mondor, Luke
Wodchis, Walter P.
Rosella, Laura C.
author_facet de Oliveira, Claire
Mondor, Luke
Wodchis, Walter P.
Rosella, Laura C.
author_sort de Oliveira, Claire
collection PubMed
description INTRODUCTION: Previous research has shown that the socioeconomic status (SES)–health gradient also extends to high-cost patients; however, little work has examined high-cost patients with mental illness and/or addiction. The objective of this study was to examine associations between individual-, household- and area-level SES factors and future high-cost use among these patients. METHODS: We linked survey data from adult participants (ages 18 and older) of 3 cycles of the Canadian Community Health Survey to administrative health care data from Ontario, Canada. Respondents with mental illness and/or addiction were identified based on prior mental health and addiction health care use and followed for 5 years for which we ascertained health care costs covered under the public health care system. We quantified associations between SES factors and becoming a high-cost patient (i.e., transitioning into the top 5%) using logistic regression models. For ordinal SES factors, such as income, education and marginalization variables, we measured absolute and relative inequalities using the slope and relative index of inequality. RESULTS: Among our sample, lower personal income (odds ratio [OR] = 2.11, 95% confidence interval [CI], 1.54 to 2.88, for CAD$0 to CAD$14,999), lower household income (OR = 2.11, 95% CI, 1.49 to 2.99, for lowest income quintile), food insecurity (OR = 1.87, 95% CI, 1.38 to 2.55) and non-homeownership (OR = 1.34, 95% CI, 1.08 to 1.66), at the individual and household levels, respectively, and higher residential instability (OR = 1.72, 95% CI, 1.23 to 2.42, for most marginalized), at the area level, were associated with higher odds of becoming a high-cost patient within a 5-year period. Moreover, the inequality analysis suggested pro-high-SES gradients in high-cost transitions. CONCLUSIONS: Policies aimed at high-cost patients with mental illness and/or addiction, or those concerned with preventing individuals with these conditions from becoming high-cost patients in the health care system, should also consider non-clinical factors such as income as well as related dimensions including food security and homeownership.
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spelling pubmed-88920692022-03-04 Looking beyond Administrative Health Care Data: The Role of Socioeconomic Status in Predicting Future High-cost Patients with Mental Health and Addiction de Oliveira, Claire Mondor, Luke Wodchis, Walter P. Rosella, Laura C. Can J Psychiatry Regular Articles INTRODUCTION: Previous research has shown that the socioeconomic status (SES)–health gradient also extends to high-cost patients; however, little work has examined high-cost patients with mental illness and/or addiction. The objective of this study was to examine associations between individual-, household- and area-level SES factors and future high-cost use among these patients. METHODS: We linked survey data from adult participants (ages 18 and older) of 3 cycles of the Canadian Community Health Survey to administrative health care data from Ontario, Canada. Respondents with mental illness and/or addiction were identified based on prior mental health and addiction health care use and followed for 5 years for which we ascertained health care costs covered under the public health care system. We quantified associations between SES factors and becoming a high-cost patient (i.e., transitioning into the top 5%) using logistic regression models. For ordinal SES factors, such as income, education and marginalization variables, we measured absolute and relative inequalities using the slope and relative index of inequality. RESULTS: Among our sample, lower personal income (odds ratio [OR] = 2.11, 95% confidence interval [CI], 1.54 to 2.88, for CAD$0 to CAD$14,999), lower household income (OR = 2.11, 95% CI, 1.49 to 2.99, for lowest income quintile), food insecurity (OR = 1.87, 95% CI, 1.38 to 2.55) and non-homeownership (OR = 1.34, 95% CI, 1.08 to 1.66), at the individual and household levels, respectively, and higher residential instability (OR = 1.72, 95% CI, 1.23 to 2.42, for most marginalized), at the area level, were associated with higher odds of becoming a high-cost patient within a 5-year period. Moreover, the inequality analysis suggested pro-high-SES gradients in high-cost transitions. CONCLUSIONS: Policies aimed at high-cost patients with mental illness and/or addiction, or those concerned with preventing individuals with these conditions from becoming high-cost patients in the health care system, should also consider non-clinical factors such as income as well as related dimensions including food security and homeownership. SAGE Publications 2021-04-01 2022-02 /pmc/articles/PMC8892069/ /pubmed/33792407 http://dx.doi.org/10.1177/07067437211004882 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Regular Articles
de Oliveira, Claire
Mondor, Luke
Wodchis, Walter P.
Rosella, Laura C.
Looking beyond Administrative Health Care Data: The Role of Socioeconomic Status in Predicting Future High-cost Patients with Mental Health and Addiction
title Looking beyond Administrative Health Care Data: The Role of Socioeconomic Status in Predicting Future High-cost Patients with Mental Health and Addiction
title_full Looking beyond Administrative Health Care Data: The Role of Socioeconomic Status in Predicting Future High-cost Patients with Mental Health and Addiction
title_fullStr Looking beyond Administrative Health Care Data: The Role of Socioeconomic Status in Predicting Future High-cost Patients with Mental Health and Addiction
title_full_unstemmed Looking beyond Administrative Health Care Data: The Role of Socioeconomic Status in Predicting Future High-cost Patients with Mental Health and Addiction
title_short Looking beyond Administrative Health Care Data: The Role of Socioeconomic Status in Predicting Future High-cost Patients with Mental Health and Addiction
title_sort looking beyond administrative health care data: the role of socioeconomic status in predicting future high-cost patients with mental health and addiction
topic Regular Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892069/
https://www.ncbi.nlm.nih.gov/pubmed/33792407
http://dx.doi.org/10.1177/07067437211004882
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