Individual and area-level factors associated with ambulatory care sensitive conditions in Finland

Abstract Background Geographic variation is common in ambulatory care sensitive conditions (ACSCs) - used as a proxy indicator for primary care quality. Its use is debated as it is more strongly associated with individual socioeconomic position (SEP) and health status than factors related to primary...

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Veröffentlicht in:European journal of public health 2019-11, Vol.29 (Supplement_4)
Hauptverfasser: Satokangas, M, Arffman, M, Leyland, A, Keskimäki, I
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creator Satokangas, M
Arffman, M
Leyland, A
Keskimäki, I
description Abstract Background Geographic variation is common in ambulatory care sensitive conditions (ACSCs) - used as a proxy indicator for primary care quality. Its use is debated as it is more strongly associated with individual socioeconomic position (SEP) and health status than factors related to primary care. While most earlier studies have been cross-sectional, this study aims to observe if these associations change over time. Finland offers a good possibility for this due to its extensive registers and unexplained over time convergence of geographic variation in ACSC. Methods This observational study obtained ACSCs in 2011-2017 from the Finnish Hospital Discharge Register and divided them into subgroups of acute, chronic and vaccine-preventable causes. In these subgroups we analysed geographic variations with a three-level multilevel logistic regression model - individuals, health centre areas (HC) and hospital districts (HD) - and estimated the proportion of the variance at each level explained by individual SEP and comorbidities, as well as both primary care and hospital supply and spatial access at three time points. Results In the preliminary results of the baseline geographic variation in total ACSCs in 2011-2013 - the model with age and sex - the variance between HDs was nearly twice that between HCs. Individual SEP and comorbidities explained 46% of the variance between HDs and 29% between HCs; and area-level proportion of ACSC periods in primary care inpatient wards a further 12% and 5%. This evened out the unexplained variance between HDs and HCs. Conclusions Geographic variation in ACSCs was more pronounced in hospital districts than in the smaller health centre areas. The excess variance between HDs was explained by individual SEP and health status as well as by use of primary care inpatient wards. Our findings suggest that not only hospital bed supply, but also the national structure of hospital services affects ACSCs. This challenges international ACSC comparisons. Key messages Geographic variation in ACSCs concentrated in larger areas with differing population characteristics. The national structure of hospital services, such as use of primary care inpatient wards, affects ACSCs.
doi_str_mv 10.1093/eurpub/ckz185.663
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Its use is debated as it is more strongly associated with individual socioeconomic position (SEP) and health status than factors related to primary care. While most earlier studies have been cross-sectional, this study aims to observe if these associations change over time. Finland offers a good possibility for this due to its extensive registers and unexplained over time convergence of geographic variation in ACSC. Methods This observational study obtained ACSCs in 2011-2017 from the Finnish Hospital Discharge Register and divided them into subgroups of acute, chronic and vaccine-preventable causes. In these subgroups we analysed geographic variations with a three-level multilevel logistic regression model - individuals, health centre areas (HC) and hospital districts (HD) - and estimated the proportion of the variance at each level explained by individual SEP and comorbidities, as well as both primary care and hospital supply and spatial access at three time points. Results In the preliminary results of the baseline geographic variation in total ACSCs in 2011-2013 - the model with age and sex - the variance between HDs was nearly twice that between HCs. Individual SEP and comorbidities explained 46% of the variance between HDs and 29% between HCs; and area-level proportion of ACSC periods in primary care inpatient wards a further 12% and 5%. This evened out the unexplained variance between HDs and HCs. Conclusions Geographic variation in ACSCs was more pronounced in hospital districts than in the smaller health centre areas. The excess variance between HDs was explained by individual SEP and health status as well as by use of primary care inpatient wards. Our findings suggest that not only hospital bed supply, but also the national structure of hospital services affects ACSCs. This challenges international ACSC comparisons. Key messages Geographic variation in ACSCs concentrated in larger areas with differing population characteristics. The national structure of hospital services, such as use of primary care inpatient wards, affects ACSCs.</description><identifier>ISSN: 1101-1262</identifier><identifier>EISSN: 1464-360X</identifier><identifier>DOI: 10.1093/eurpub/ckz185.663</identifier><language>eng</language><publisher>Oxford: Oxford University Press</publisher><subject>Ambulatory care ; Districts ; Emergency medical services ; Geographical variations ; Health care ; Health care facilities ; Observational studies ; Population characteristics ; Primary care ; Public health ; Quality of care ; Regression analysis ; Regression models ; Subgroups</subject><ispartof>European journal of public health, 2019-11, Vol.29 (Supplement_4)</ispartof><rights>The Author(s) 2019. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved. 2019</rights><rights>The Author(s) 2019. Published by Oxford University Press on behalf of the European Public Health Association. 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Its use is debated as it is more strongly associated with individual socioeconomic position (SEP) and health status than factors related to primary care. While most earlier studies have been cross-sectional, this study aims to observe if these associations change over time. Finland offers a good possibility for this due to its extensive registers and unexplained over time convergence of geographic variation in ACSC. Methods This observational study obtained ACSCs in 2011-2017 from the Finnish Hospital Discharge Register and divided them into subgroups of acute, chronic and vaccine-preventable causes. In these subgroups we analysed geographic variations with a three-level multilevel logistic regression model - individuals, health centre areas (HC) and hospital districts (HD) - and estimated the proportion of the variance at each level explained by individual SEP and comorbidities, as well as both primary care and hospital supply and spatial access at three time points. Results In the preliminary results of the baseline geographic variation in total ACSCs in 2011-2013 - the model with age and sex - the variance between HDs was nearly twice that between HCs. Individual SEP and comorbidities explained 46% of the variance between HDs and 29% between HCs; and area-level proportion of ACSC periods in primary care inpatient wards a further 12% and 5%. This evened out the unexplained variance between HDs and HCs. Conclusions Geographic variation in ACSCs was more pronounced in hospital districts than in the smaller health centre areas. The excess variance between HDs was explained by individual SEP and health status as well as by use of primary care inpatient wards. Our findings suggest that not only hospital bed supply, but also the national structure of hospital services affects ACSCs. This challenges international ACSC comparisons. Key messages Geographic variation in ACSCs concentrated in larger areas with differing population characteristics. 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Its use is debated as it is more strongly associated with individual socioeconomic position (SEP) and health status than factors related to primary care. While most earlier studies have been cross-sectional, this study aims to observe if these associations change over time. Finland offers a good possibility for this due to its extensive registers and unexplained over time convergence of geographic variation in ACSC. Methods This observational study obtained ACSCs in 2011-2017 from the Finnish Hospital Discharge Register and divided them into subgroups of acute, chronic and vaccine-preventable causes. In these subgroups we analysed geographic variations with a three-level multilevel logistic regression model - individuals, health centre areas (HC) and hospital districts (HD) - and estimated the proportion of the variance at each level explained by individual SEP and comorbidities, as well as both primary care and hospital supply and spatial access at three time points. Results In the preliminary results of the baseline geographic variation in total ACSCs in 2011-2013 - the model with age and sex - the variance between HDs was nearly twice that between HCs. Individual SEP and comorbidities explained 46% of the variance between HDs and 29% between HCs; and area-level proportion of ACSC periods in primary care inpatient wards a further 12% and 5%. This evened out the unexplained variance between HDs and HCs. Conclusions Geographic variation in ACSCs was more pronounced in hospital districts than in the smaller health centre areas. The excess variance between HDs was explained by individual SEP and health status as well as by use of primary care inpatient wards. Our findings suggest that not only hospital bed supply, but also the national structure of hospital services affects ACSCs. This challenges international ACSC comparisons. Key messages Geographic variation in ACSCs concentrated in larger areas with differing population characteristics. The national structure of hospital services, such as use of primary care inpatient wards, affects ACSCs.</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><doi>10.1093/eurpub/ckz185.663</doi><oa>free_for_read</oa></addata></record>
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subjects Ambulatory care
Districts
Emergency medical services
Geographical variations
Health care
Health care facilities
Observational studies
Population characteristics
Primary care
Public health
Quality of care
Regression analysis
Regression models
Subgroups
title Individual and area-level factors associated with ambulatory care sensitive conditions in Finland
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