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Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis

BACKGROUND: Multimorbidity (the presence of two or more non-communicable diseases) is a major growing challenge for many low-income and middle-income countries (LMICs). Yet, its effects on health care costs and financial burden for patients have not been adequately studied. This study investigates t...

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Autores principales: Anindya, Kanya, Ng, Nawi, Atun, Rifat, Marthias, Tiara, Zhao, Yang, McPake, Barbara, van Heusden, Alexander, Pan, Tianxin, Lee, John Tayu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097787/
https://www.ncbi.nlm.nih.gov/pubmed/33952273
http://dx.doi.org/10.1186/s12913-021-06446-9
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author Anindya, Kanya
Ng, Nawi
Atun, Rifat
Marthias, Tiara
Zhao, Yang
McPake, Barbara
van Heusden, Alexander
Pan, Tianxin
Lee, John Tayu
author_facet Anindya, Kanya
Ng, Nawi
Atun, Rifat
Marthias, Tiara
Zhao, Yang
McPake, Barbara
van Heusden, Alexander
Pan, Tianxin
Lee, John Tayu
author_sort Anindya, Kanya
collection PubMed
description BACKGROUND: Multimorbidity (the presence of two or more non-communicable diseases) is a major growing challenge for many low-income and middle-income countries (LMICs). Yet, its effects on health care costs and financial burden for patients have not been adequately studied. This study investigates the effect of multimorbidity across the different percentiles of healthcare utilisation and out-of-pocket expenditure (OOPE). METHODS: We conducted a secondary data analysis of the 2014/2015 Indonesian Family Life Survey (IFLS-5), which included 13,798 respondents aged ≥40 years. Poisson regression was used to assess the association between sociodemographic characteristics and the total number of non-communicable diseases (NCDs), while multivariate logistic regression and quantile regression analysis was used to estimate the associations between multimorbidity, health service use and OOPE. RESULTS: Overall, 20.8% of total participants had two or more NCDs in 2014/2015. The number of NCDs was associated with higher healthcare utilisation (coefficient 0.11, 95% CI 0.07–0.14 for outpatient care and coefficient 0.09 (95% CI 0.02–0.16 for inpatient care) and higher four-weekly OOPE (coefficient 27.0, 95% CI 11.4–42.7). The quantile regression results indicated that the marginal effect of having three or more NCDs on the absolute amount of four-weekly OOPE was smaller for the lower percentiles (at the 25th percentile, coefficient 1.0, 95% CI 0.5–1.5) but more pronounced for the higher percentile of out-of-pocket spending distribution (at the 90th percentile, coefficient 31.0, 95% CI 15.9–46.2). CONCLUSION: Multimorbidity is positively correlated with health service utilisation and OOPE and has a significant effect, especially among those in the upper tail of the utilisation/costs distribution. Health financing strategies are urgently required to meet the needs of patients with multimorbidity, particularly for vulnerable groups that have a higher level of health care utilisation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06446-9.
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spelling pubmed-80977872021-05-05 Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis Anindya, Kanya Ng, Nawi Atun, Rifat Marthias, Tiara Zhao, Yang McPake, Barbara van Heusden, Alexander Pan, Tianxin Lee, John Tayu BMC Health Serv Res Research Article BACKGROUND: Multimorbidity (the presence of two or more non-communicable diseases) is a major growing challenge for many low-income and middle-income countries (LMICs). Yet, its effects on health care costs and financial burden for patients have not been adequately studied. This study investigates the effect of multimorbidity across the different percentiles of healthcare utilisation and out-of-pocket expenditure (OOPE). METHODS: We conducted a secondary data analysis of the 2014/2015 Indonesian Family Life Survey (IFLS-5), which included 13,798 respondents aged ≥40 years. Poisson regression was used to assess the association between sociodemographic characteristics and the total number of non-communicable diseases (NCDs), while multivariate logistic regression and quantile regression analysis was used to estimate the associations between multimorbidity, health service use and OOPE. RESULTS: Overall, 20.8% of total participants had two or more NCDs in 2014/2015. The number of NCDs was associated with higher healthcare utilisation (coefficient 0.11, 95% CI 0.07–0.14 for outpatient care and coefficient 0.09 (95% CI 0.02–0.16 for inpatient care) and higher four-weekly OOPE (coefficient 27.0, 95% CI 11.4–42.7). The quantile regression results indicated that the marginal effect of having three or more NCDs on the absolute amount of four-weekly OOPE was smaller for the lower percentiles (at the 25th percentile, coefficient 1.0, 95% CI 0.5–1.5) but more pronounced for the higher percentile of out-of-pocket spending distribution (at the 90th percentile, coefficient 31.0, 95% CI 15.9–46.2). CONCLUSION: Multimorbidity is positively correlated with health service utilisation and OOPE and has a significant effect, especially among those in the upper tail of the utilisation/costs distribution. Health financing strategies are urgently required to meet the needs of patients with multimorbidity, particularly for vulnerable groups that have a higher level of health care utilisation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06446-9. BioMed Central 2021-05-05 /pmc/articles/PMC8097787/ /pubmed/33952273 http://dx.doi.org/10.1186/s12913-021-06446-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Anindya, Kanya
Ng, Nawi
Atun, Rifat
Marthias, Tiara
Zhao, Yang
McPake, Barbara
van Heusden, Alexander
Pan, Tianxin
Lee, John Tayu
Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis
title Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis
title_full Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis
title_fullStr Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis
title_full_unstemmed Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis
title_short Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis
title_sort effect of multimorbidity on utilisation and out-of-pocket expenditure in indonesia: quantile regression analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097787/
https://www.ncbi.nlm.nih.gov/pubmed/33952273
http://dx.doi.org/10.1186/s12913-021-06446-9
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