Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases

E.F. de Vries, R. Heijink, J.N. Struijs, C.A. Baan

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Abstract

BACKGROUND: To indicate inefficiencies in health systems, previous studies examined regional variation in healthcare spending by analyzing the entire population. As a result, population heterogeneity is taken into account to a limited extent only. Furthermore, it clouds a detailed interpretation which could be used to inform regional budget allocation decisions to improve quality of care of one chronic disease over another. Therefore, we aimed to gain insight into the drivers of regional variation in healthcare spending by studying prevalent chronic diseases.

METHODS: We used 2012 secondary health survey data linked with claims data, healthcare supply data and demographics at the individual level for 18 Dutch regions. We studied patients with diabetes (n = 10,767) and depression (n = 3,735), in addition to the general population (n = 44,694). For all samples, we estimated the cross-sectional relationship between spending, supply and demand variables and region effects using linear mixed models.

RESULTS: Regions with above (below) average spending for the general population mostly showed above (below) average spending for diabetes and depression as well. Less than 1% of the a-priori total variation in spending was attributed to the regions. For all samples, we found that individual-level demand variables explained 62-63% of the total variance. Self-reported health status was the most prominent predictor (28%) of healthcare spending. Supply variables also explained, although a small part, of regional variation in spending in the general population and depression. Demand variables explained nearly 100% of regional variation in spending for depression and 88% for diabetes, leaving 12% of the regional variation left unexplained indicating differences between regions due to inefficiencies.

CONCLUSIONS: The extent to which regional variation in healthcare spending can be considered as inefficiency may differ between regions and disease-groups. Therefore, analyzing chronic diseases, in addition to the traditional approach where the general population is studied, provides more insight into the causes of regional variation in healthcare spending, and identifies potential areas for efficiency improvement and budget allocation decisions.

Original languageEnglish
Article number323
Number of pages9
JournalBMC Health Services Research
Volume18
DOIs
Publication statusPublished - 2018

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Delivery of Health Care
Health Surveys
Linear Models

Keywords

  • Aged
  • Chronic Disease/economics
  • Cross-Sectional Studies
  • Delivery of Health Care/economics
  • Female
  • Health Expenditures/statistics & numerical data
  • Health Status
  • Humans
  • Netherlands/epidemiology
  • Prevalence

Cite this

@article{e09e5c82ef474f48b0293af4c75628a0,
title = "Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases",
abstract = "BACKGROUND: To indicate inefficiencies in health systems, previous studies examined regional variation in healthcare spending by analyzing the entire population. As a result, population heterogeneity is taken into account to a limited extent only. Furthermore, it clouds a detailed interpretation which could be used to inform regional budget allocation decisions to improve quality of care of one chronic disease over another. Therefore, we aimed to gain insight into the drivers of regional variation in healthcare spending by studying prevalent chronic diseases.METHODS: We used 2012 secondary health survey data linked with claims data, healthcare supply data and demographics at the individual level for 18 Dutch regions. We studied patients with diabetes (n = 10,767) and depression (n = 3,735), in addition to the general population (n = 44,694). For all samples, we estimated the cross-sectional relationship between spending, supply and demand variables and region effects using linear mixed models.RESULTS: Regions with above (below) average spending for the general population mostly showed above (below) average spending for diabetes and depression as well. Less than 1{\%} of the a-priori total variation in spending was attributed to the regions. For all samples, we found that individual-level demand variables explained 62-63{\%} of the total variance. Self-reported health status was the most prominent predictor (28{\%}) of healthcare spending. Supply variables also explained, although a small part, of regional variation in spending in the general population and depression. Demand variables explained nearly 100{\%} of regional variation in spending for depression and 88{\%} for diabetes, leaving 12{\%} of the regional variation left unexplained indicating differences between regions due to inefficiencies.CONCLUSIONS: The extent to which regional variation in healthcare spending can be considered as inefficiency may differ between regions and disease-groups. Therefore, analyzing chronic diseases, in addition to the traditional approach where the general population is studied, provides more insight into the causes of regional variation in healthcare spending, and identifies potential areas for efficiency improvement and budget allocation decisions.",
keywords = "Aged, Chronic Disease/economics, Cross-Sectional Studies, Delivery of Health Care/economics, Female, Health Expenditures/statistics & numerical data, Health Status, Humans, Netherlands/epidemiology, Prevalence",
author = "{de Vries}, E.F. and R. Heijink and J.N. Struijs and C.A. Baan",
year = "2018",
doi = "10.1186/s12913-018-3128-4",
language = "English",
volume = "18",
journal = "BMC Health Services Research",
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publisher = "BMC",

}

Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases. / de Vries, E.F.; Heijink, R.; Struijs, J.N.; Baan, C.A.

In: BMC Health Services Research, Vol. 18, 323, 2018.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases

AU - de Vries, E.F.

AU - Heijink, R.

AU - Struijs, J.N.

AU - Baan, C.A.

PY - 2018

Y1 - 2018

N2 - BACKGROUND: To indicate inefficiencies in health systems, previous studies examined regional variation in healthcare spending by analyzing the entire population. As a result, population heterogeneity is taken into account to a limited extent only. Furthermore, it clouds a detailed interpretation which could be used to inform regional budget allocation decisions to improve quality of care of one chronic disease over another. Therefore, we aimed to gain insight into the drivers of regional variation in healthcare spending by studying prevalent chronic diseases.METHODS: We used 2012 secondary health survey data linked with claims data, healthcare supply data and demographics at the individual level for 18 Dutch regions. We studied patients with diabetes (n = 10,767) and depression (n = 3,735), in addition to the general population (n = 44,694). For all samples, we estimated the cross-sectional relationship between spending, supply and demand variables and region effects using linear mixed models.RESULTS: Regions with above (below) average spending for the general population mostly showed above (below) average spending for diabetes and depression as well. Less than 1% of the a-priori total variation in spending was attributed to the regions. For all samples, we found that individual-level demand variables explained 62-63% of the total variance. Self-reported health status was the most prominent predictor (28%) of healthcare spending. Supply variables also explained, although a small part, of regional variation in spending in the general population and depression. Demand variables explained nearly 100% of regional variation in spending for depression and 88% for diabetes, leaving 12% of the regional variation left unexplained indicating differences between regions due to inefficiencies.CONCLUSIONS: The extent to which regional variation in healthcare spending can be considered as inefficiency may differ between regions and disease-groups. Therefore, analyzing chronic diseases, in addition to the traditional approach where the general population is studied, provides more insight into the causes of regional variation in healthcare spending, and identifies potential areas for efficiency improvement and budget allocation decisions.

AB - BACKGROUND: To indicate inefficiencies in health systems, previous studies examined regional variation in healthcare spending by analyzing the entire population. As a result, population heterogeneity is taken into account to a limited extent only. Furthermore, it clouds a detailed interpretation which could be used to inform regional budget allocation decisions to improve quality of care of one chronic disease over another. Therefore, we aimed to gain insight into the drivers of regional variation in healthcare spending by studying prevalent chronic diseases.METHODS: We used 2012 secondary health survey data linked with claims data, healthcare supply data and demographics at the individual level for 18 Dutch regions. We studied patients with diabetes (n = 10,767) and depression (n = 3,735), in addition to the general population (n = 44,694). For all samples, we estimated the cross-sectional relationship between spending, supply and demand variables and region effects using linear mixed models.RESULTS: Regions with above (below) average spending for the general population mostly showed above (below) average spending for diabetes and depression as well. Less than 1% of the a-priori total variation in spending was attributed to the regions. For all samples, we found that individual-level demand variables explained 62-63% of the total variance. Self-reported health status was the most prominent predictor (28%) of healthcare spending. Supply variables also explained, although a small part, of regional variation in spending in the general population and depression. Demand variables explained nearly 100% of regional variation in spending for depression and 88% for diabetes, leaving 12% of the regional variation left unexplained indicating differences between regions due to inefficiencies.CONCLUSIONS: The extent to which regional variation in healthcare spending can be considered as inefficiency may differ between regions and disease-groups. Therefore, analyzing chronic diseases, in addition to the traditional approach where the general population is studied, provides more insight into the causes of regional variation in healthcare spending, and identifies potential areas for efficiency improvement and budget allocation decisions.

KW - Aged

KW - Chronic Disease/economics

KW - Cross-Sectional Studies

KW - Delivery of Health Care/economics

KW - Female

KW - Health Expenditures/statistics & numerical data

KW - Health Status

KW - Humans

KW - Netherlands/epidemiology

KW - Prevalence

U2 - 10.1186/s12913-018-3128-4

DO - 10.1186/s12913-018-3128-4

M3 - Article

VL - 18

JO - BMC Health Services Research

JF - BMC Health Services Research

SN - 1472-6963

M1 - 323

ER -