Walk-in clinics working in a network. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Montecinos, Julio; Ouhimmou, Mustapha; Chauhan, Satyaveer
• Is Part Of: Logistique & management. Volume 25:Issue 1(2017)
• Page Start: 43
• Page End: 56
• Publication Date: 2017-01-02
• Subjects: Data analysis -- walk-in-clinics -- health supply chain -- workload and healthcare offer -- modelling and computer simulation; Analyse des données -- cliniques sans rendez-vous -- chaîne logistique des soins et santé -- équilibrage de charge -- modélisation mathématique -- simulation; Logistics -- Periodicals; Management -- Periodicals; Integrated logistic support -- Periodicals; Integrated logistic support; Logistics; Management; Periodicals; 658.505
• DOI: 10.1080/12507970.2017.1310002
• Languages: English
• ISSNs: 1250-7970

Abstract

ABSTRACT: This paper proposes a new approach to balance the loads in a network of walk-in clinics (WiCs) by dispersing patients based on patients' preferences, emergency and geographical locations. WiCs accept patients without an appointment and they are flexible in serving last-minute patients and non-severe emergencies. WiCs are usually geographically distributed to be close to patients. Having limited resources, WiCs manage the number and severity of patients they can handle. In some cases, the geographical dispersion of WiCs is not enough to allow natural load balance among clinics, leaving some WiCs with an excess of demand in some zones and with few patients in others. This implies that patients sometimes do not receive healthcare quickly, they leave the facilities disappointed and medical staff lose efficiency in their work. This paper proposes a centralised system that reduces both long waiting times and workload of several WiCs within a network, thus preserving patients' freedom to choose a clinic at the same time. This approach has been applied to a case study and the results showed an improvement, reducing the number of patients in overloaded clinics and saving 112.7 minutes on average. An extended simulation also shows that in 26 cases over 40 days, a rebalance is possible with few moves representing less than 12.4% of the total number of patients in all clinics, with some downsides that could be corrected during the journey.