A heuristic approach to solve the preventive health care problem with budget and congestion constraints

Abstract

This document is the Accepted Manuscript version of the following article: Soheil Davari, Kemal Kilic, and Siamak Naderi, ???A heuristic approach to solve the preventive health care problem with budget and congestion constraints???, Applied Mathematics and Computation, Vol. 276, pp. 442-453, March 2016. ?? 2016. Under embargo. Embargo end date: 14 January 2018. The Version of Record is available online at doi: https://doi.org/10.1016/j.amc.2015.11.073.Preventive health care is of utmost importance to governments since they can make massive savings on health care expenditure and promote the well-being of the society. Preventive care includes many services such as cancer screenings, vaccinations, hepatitis screenings, and smoking cessation programs. Despite the benefits of these services, their uptake is not satisfactory in many countries in the world. This can be attributed to financial barriers, social issues., and other factors. One of the most important barriers for preventive care is accessibility to proper services, which is a function of various qualitative and quantitative factors such as the distance to travel, waiting time, vicinity of facilities to other attractive facilities (such as shopping malls), and even the cleanliness of the facilities. Statistics show that even a small improvement in people???s participation can save massive amounts of money for any government and improve the well-being of the people in a society. This paper addresses the problem of designing a preventive health care network considering impatient clients, and budget constraints. The objective is to maximize the accessibility of services to people. We model the problem as a mixed-integer programming problem with budget constraints, and congestion considerations. An efficient variable neighborhood search procedure is proposed and computational experiments are performed on a large set of instances

Capacitated Preventive Health Infrastructure Planning with Accessibility-Based Service Equity

“…In fact, there are two sources of inaccessible demand: one is demand lost due to insufficient coverage and the other is demand lost due to congested facility (Abouee-Mehrizi et al, 2011;. For the first source, demand is elastic with respect to cost and customers are usually assigned to the closest facilities to maximize system total demand (Berman and Drezner, 2006;Davari et al, 2016;Marianov, 2003;Zhang et al, 2010). For the second source, customers could be denied to access the service (i.e., occurrence of balking) upon their arrival, due to capable space.…”

“…Zhang et al (2009) further incorporated congestion effect at a facility where the users are assumed to visit the facility with minimum total cost including travel time and queueing time. The queueing time can also be incorporated as a constraint (Davari et al, 2016). Multi-objective location problems are also proposed recently where multiple performances are evaluated (Dogan et al, 2020;Erdoğan et al, 2019).…”

Optimal Capacity Allocation when Patients encounter Congestion in Primary Healthcare Network

“…Zhang et al (2009) proposed a healthcare facility location model incorporating congestion. Davari et al (2016) suggested a mixed-integer programming model to design a health care network under budget and congestion considerations and also proposed a heuristic approach for solving the proposed model. A congested facility is unable to provide health care services to every patient and the patients are compelled to go elsewhere to get the services.…”

Design of Preventive Healthcare Services: A Brief Review

“…In another work, Davari et al (2016) presented a mixed-integer programming model for designing preventive healthcare networks subject to budget constraints and equity considerations. They developed a skewed variable neighborhood search algorithm to solve their proposed model.…”

“…Preventive services and programs are proven to be contributing to better life quality of patients by reducing the likelihood of receiving radical treatments such as surgery or chemotherapy, as well as saving their lives (Zhang et al 2020). Previous studies showed that even a small amount of improvement in the participation of these services can save massive amounts of money for healthcare organizations and governments (Davari et al 2016). Preventive healthcare is considered the most effective and efficient way of preventing disease and increasing public health in both developed and developing countries.…”