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How do socio-economic factors and distance predict access to prevention and rehabilitation services in a Danish municipality?

Aim The aim was to explore the extent to which a Danish prevention centre catered to marginalised groups within the catchment area. We determined whether the district's socio-economic vulnerability status and distance from the citizens' residential sector to the centre influenced referrals...

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Published in:Primary health care research & development 2016-11, Vol.17 (6), p.578-585
Main Authors: Hindhede, Anette L., Bonde, Ane, Schipperijn, Jasper, Scheuer, Stine H., Sørensen, Susanne M., Aagaard-Hansen, Jens
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description Aim The aim was to explore the extent to which a Danish prevention centre catered to marginalised groups within the catchment area. We determined whether the district's socio-economic vulnerability status and distance from the citizens' residential sector to the centre influenced referrals of citizens to the centre, their attendance at initial appointment, and completion of planned activities at the centre. Disparities in access to health care services is one among many aspects of inequality in health. There are multiple determinants within populations (socio-economic status, ethnicity, and education) as well as the health care systems (resource availability and cultural acceptability). A total of 347 participants referred to the centre during a 10-month period were included. For each of 44 districts within the catchment area, the degree of socio-economic vulnerability was estimated based on the citizens' educational level, ethnicity, income, and unemployment rate. A socio-economic vulnerability score (SE-score) was calculated. Logistic regression was used to calculate the probability that a person was referred to the centre, attended the initial appointment, and completed the planned activities, depending on sex, age, SE-score of district of residence, and distance to the centre. Findings Citizens from locations with a high socio-economic vulnerability had increased probability of being referred by general practitioners, hospitals, and job centres. Citizens living further away from the prevention centre had a reduced probability of being referred by their general practitioners. After referral, there was no difference in probability of attendance or completion as a function of SE-score or distance between the citizens' district and the centre. In conclusion, the centre is capable of attracting referrals from districts where the need is likely to be relatively high in terms of socio-economic vulnerability, whereas distance reduced the probability of referral. No differences were found in attendance or completion.
doi_str_mv 10.1017/S1463423616000268
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We determined whether the district's socio-economic vulnerability status and distance from the citizens' residential sector to the centre influenced referrals of citizens to the centre, their attendance at initial appointment, and completion of planned activities at the centre. Disparities in access to health care services is one among many aspects of inequality in health. There are multiple determinants within populations (socio-economic status, ethnicity, and education) as well as the health care systems (resource availability and cultural acceptability). A total of 347 participants referred to the centre during a 10-month period were included. For each of 44 districts within the catchment area, the degree of socio-economic vulnerability was estimated based on the citizens' educational level, ethnicity, income, and unemployment rate. A socio-economic vulnerability score (SE-score) was calculated. Logistic regression was used to calculate the probability that a person was referred to the centre, attended the initial appointment, and completed the planned activities, depending on sex, age, SE-score of district of residence, and distance to the centre. Findings Citizens from locations with a high socio-economic vulnerability had increased probability of being referred by general practitioners, hospitals, and job centres. Citizens living further away from the prevention centre had a reduced probability of being referred by their general practitioners. After referral, there was no difference in probability of attendance or completion as a function of SE-score or distance between the citizens' district and the centre. In conclusion, the centre is capable of attracting referrals from districts where the need is likely to be relatively high in terms of socio-economic vulnerability, whereas distance reduced the probability of referral. 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Logistic regression was used to calculate the probability that a person was referred to the centre, attended the initial appointment, and completed the planned activities, depending on sex, age, SE-score of district of residence, and distance to the centre. Findings Citizens from locations with a high socio-economic vulnerability had increased probability of being referred by general practitioners, hospitals, and job centres. Citizens living further away from the prevention centre had a reduced probability of being referred by their general practitioners. After referral, there was no difference in probability of attendance or completion as a function of SE-score or distance between the citizens' district and the centre. In conclusion, the centre is capable of attracting referrals from districts where the need is likely to be relatively high in terms of socio-economic vulnerability, whereas distance reduced the probability of referral. 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development</jtitle><addtitle>Prim Health Care Res Dev</addtitle><date>2016-11</date><risdate>2016</risdate><volume>17</volume><issue>6</issue><spage>578</spage><epage>585</epage><pages>578-585</pages><issn>1463-4236</issn><eissn>1477-1128</eissn><abstract>Aim The aim was to explore the extent to which a Danish prevention centre catered to marginalised groups within the catchment area. We determined whether the district's socio-economic vulnerability status and distance from the citizens' residential sector to the centre influenced referrals of citizens to the centre, their attendance at initial appointment, and completion of planned activities at the centre. Disparities in access to health care services is one among many aspects of inequality in health. There are multiple determinants within populations (socio-economic status, ethnicity, and education) as well as the health care systems (resource availability and cultural acceptability). A total of 347 participants referred to the centre during a 10-month period were included. For each of 44 districts within the catchment area, the degree of socio-economic vulnerability was estimated based on the citizens' educational level, ethnicity, income, and unemployment rate. A socio-economic vulnerability score (SE-score) was calculated. Logistic regression was used to calculate the probability that a person was referred to the centre, attended the initial appointment, and completed the planned activities, depending on sex, age, SE-score of district of residence, and distance to the centre. Findings Citizens from locations with a high socio-economic vulnerability had increased probability of being referred by general practitioners, hospitals, and job centres. Citizens living further away from the prevention centre had a reduced probability of being referred by their general practitioners. After referral, there was no difference in probability of attendance or completion as a function of SE-score or distance between the citizens' district and the centre. In conclusion, the centre is capable of attracting referrals from districts where the need is likely to be relatively high in terms of socio-economic vulnerability, whereas distance reduced the probability of referral. 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source Cambridge University Press
subjects Adult
Alcohol
Cancer
Chronic obstructive pulmonary disease
Collaboration
Denmark
Diabetes
Disease
Disease prevention
Ethnic Groups - statistics & numerical data
Family physicians
Female
Health care access
Health care policy
Health services
Health Services Accessibility - statistics & numerical data
Humans
Inequality
Male
Medical referrals
Middle Aged
Patients
Preventive Medicine - statistics & numerical data
Referral and Consultation - statistics & numerical data
Rehabilitation
Rehabilitation Centers - statistics & numerical data
Rehabilitation Centers - utilization
Risk factors
Rural Population - statistics & numerical data
Social sciences
Socioeconomic Factors
title How do socio-economic factors and distance predict access to prevention and rehabilitation services in a Danish municipality?
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