3F 1 Cross Sectional Study of the Predictors of the Number of Attendees at a Sexual Health Service 2002 2012

Wednesday, June 11, 2014: 10:45 AM
Eric PF Chow, PhD, Melbourne Sexual Health Centre, The Alfred Hospital, Melbourne, Australia and Nimal Gamagedara, MBBS, MSc [Community Medicine], MD [Community Medicine], Epidemiology unit, Department of Health Services, Provincial Directorate of Health Services, Badulla, Sri Lanka, Provincial Directorate of Health Services, Uva province, Sri Lanka, Badulla, Sri Lanka

Background:  Open access to sexual health services may be inefficient if there are substantial unpredictable fluctuations in presentations. Our aim was to determine if the number of presentations over the last 11 years could be predicted.

Methods:  This cross sectional study involved all individuals presenting to Melbourne Sexual Health Centre (MSHC) from 2002 to 2012.  The outcome measure was the number of presentations during a clinical session (half day). 

Results:  There were 270,070 presentations to the clinic among 86,717 individuals. The factors associated with the largest difference in mean presentations per session were morning or afternoon (60 vs. 51 per session), days of the week (57-67 per session), months of the year (93-112 per day), year (77-131 per day), maximum temperatures of <15C vs. ≥ 30C (56-62 per morning session), and 5 working days after holiday periods (61 vs. 54).  A multiple linear regression model using these factors explained 64% of the variation in attendances per session.  Peak attendance rates (>90th percentile) were also strongly correlated with these same variables. Higher risk heterosexuals (≤ 25 years of age) attended more commonly in the afternoons (37% of heterosexuals) than mornings (30%). No factor other than year of attendance substantially influenced the proportion of higher risk men who have sex with men (MSM) (≥ 10 partners per year) who attended. 

Conclusions:  A considerable proportion of the variability in presentations was explained by known factors that could predict client presentations to sexual health services and therefore allow optimal allocation of resources to match demand.