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 interpreta...
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| Format: | Article |
| Language: | English |
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BMC
2018-05-01
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| Series: | BMC Health Services Research |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12913-018-3128-4 |
| _version_ | 1811295000898568192 |
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| author | Eline F. de Vries Richard Heijink Jeroen N. Struijs Caroline A. Baan |
| author_facet | Eline F. de Vries Richard Heijink Jeroen N. Struijs Caroline A. Baan |
| author_sort | Eline F. de Vries |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T05:26:00Z |
| format | Article |
| id | doaj.art-a89d83aaf5a142fe889c07637c518245 |
| institution | Directory Open Access Journal |
| issn | 1472-6963 |
| language | English |
| last_indexed | 2024-04-13T05:26:00Z |
| publishDate | 2018-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Health Services Research |
| spelling | doaj.art-a89d83aaf5a142fe889c07637c5182452022-12-22T03:00:35ZengBMCBMC Health Services Research1472-69632018-05-011811910.1186/s12913-018-3128-4Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseasesEline F. de Vries0Richard Heijink1Jeroen N. Struijs2Caroline A. Baan3Tilburg University, Tranzo, Tilburg School of Social and Behavioral SciencesDutch Healthcare AuthorityDepartment of Quality of Care and Health Economics, National Institute of Public Health and the Environment (RIVM), Center for Nutrition, Prevention and Health ServicesTilburg University, Tranzo, Tilburg School of Social and Behavioral SciencesAbstract 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.http://link.springer.com/article/10.1186/s12913-018-3128-4Regional variationHealthcare spendingLmmDisease-approach |
| spellingShingle | Eline F. de Vries Richard Heijink Jeroen N. Struijs Caroline A. Baan Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases BMC Health Services Research Regional variation Healthcare spending Lmm Disease-approach |
| title | Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases |
| title_full | Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases |
| title_fullStr | Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases |
| title_full_unstemmed | Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases |
| title_short | Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases |
| title_sort | unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases |
| topic | Regional variation Healthcare spending Lmm Disease-approach |
| url | http://link.springer.com/article/10.1186/s12913-018-3128-4 |
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