A facility location model for analysis of current and future demand for sexual health services

• Published in: PloS one Vol. 12; no. 8; p. e0183942
• Main Authors: Meskarian, Rudabeh, Penn, Marion L, Williams, Sarah, Monks, Thomas
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 29-08-2017; Public Library of Science (PLoS)
• Subjects: Algorithms; Annealing; Biology and Life Sciences; Birth control; Costs; Demand analysis; Earth Sciences; Genetic algorithms; Geography; Health care; Health promotion; Health sciences; Health services; Health Services Accessibility; Health Services Needs and Demand; Heuristic; Humans; Information systems; Medical diagnosis; Medicine and health sciences; Models, Theoretical; Operations research; People and places; Physical Sciences; Population; Problem solving; Problems; Public transportation; Reproduction; Reproductive Health; Reproductive Health Services; Reproductive systems; Research and Analysis Methods; Sexual assault; Sexual health; Social Sciences; Travel; Travel time; Traveltime; United Kingdom; United Kingdom > UK; England
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0183942

In this paper we address the clinic location selection problem for a fully integrated Sexual Health Service across Hampshire. The service provides outpatient services for Genito-Urinary Medicine, contraceptive and reproductive health, sexual health promotion and a sexual assault referral centre. We aim to assist the planning of sexual health service provision in Hampshire by conducting a location analysis using both current and predicted patient need. We identify the number of clinic locations required and their optimal geographic location that minimise patient travel time. To maximise the chances of uptake of results we validate the developed simple algorithm with an exact method as well as three well-known, but complex meta-heuristics. The analysis was conducted using car travel and public transport times. Two scenarios were considered: current clinic locations only; and anywhere within Hampshire. The results show that the clinic locations could be reduced from 28 to 20 and still keep 90% of all patient journeys by public transport (e.g. by bus or train) to a clinic within 30 minutes. The number of clinics could be further reduced to 8 if the travel time is based on car travel times within 15 minutes. Results from our simple solution method compared favourably to the exact solution as well as the complex meta-heuristics.