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We thus hypothesize: Hypothesis 1 (H1): Population size has a direct positive effect on service utilization.
There is limited evidence regarding the effect of franchising on service utilization [ 6].
The primary family caregiver has a high impact on service utilization.
A major peak on service utilization for cluster 5, the Most Here cluster, is case management.
Thus we hypothesize: Hypothesis 3.1 (H3.1): Service accessibility has a direct negative effect on service utilization.
Quality improvement does not automatically compensate for negative effects of higher prices on service utilization [ 73].
Thus, we hypothesize: Hypothesis 4.1 (H4.1): Educational profile has a direct negative effect on service utilization.
Service accessibility decreases the effect of population size on service utilization (β=−0.606, p<0.01), and educational profile weakens the effects of population size and age profile on service utilization (β=−0.595, p<0.01; β=−0.286, p<0.01, respectively).
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Hierarchical analysis was applied to estimate the effects of patient and municipality-level variables on services utilization.
In these models, main effect of all independent variables listed in the table were included to compare their effects on services utilization after adjusting for other independent variables.
It is important to quantify the effect of this healthcare policy on services utilization so that policymakers can evaluate the impact of their decision on this population of youth at increased risk for receipt of suboptimal care.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com