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However, each district has its own unique characteristics that influence waiting times.
We also expect that the urgency estimated at the telephone may influence waiting times.
Although home visits waiting times increase with increasing distance from the GP cooperative, it appears that traffic intensity, home visit intensity, and urgency also influence waiting times.
It is not known whether this assumption is correct or if there are other factors that influence waiting times as well.
Its results suggested that NPs might influence waiting times, but only for practices in this health plan during the time of the study.
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Multiple factors may influence wait time dynamics, including time-varying referral rates, number of nephrologists, pooled versus individual triage systems, and practice sizes.
The aims of our study were to: (1) document wait times in breast cancer care pathways, from disease detection to start of first adjuvant therapy; (2) examine the implications of using different care intervals to report wait times and identify delays in care; and (3) assesses how clinical, demographic and treatment factors influence wait times over the entire clinical path.
To identify the variables influencing waiting time for specialized care (waiting lists) through multiple regression analysis and to analyze the health districts with long waiting times according to these variables.
Further, we investigated if other factors (traffic intensity, home visit intensity, time of day, and degree of urgency) influenced waiting times.
Education and income levels were important factors influencing wait times within a period but not between periods.
A general linear model with a stepwise selection (P<0.05) was used to identify dominant cofactors influencing wait times at the three levels of care interval resolution.
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