Modelling improved efficiency in healthcare referral systems for the urban poor using a geo-referenced health facility data: the case of Sylhet City Corporation, Bangladesh

Author:

Adams Alayne M.ORCID,Ahmed Rushdia,Ahmed Shakil,Yusuf Sifat Shahana,Islam Rubana,Zakaria Salam Ruman M.,Panciera Rocco

Abstract

Abstract Background An effective referral system is critical to ensuring access to appropriate and timely healthcare services. In pluralistic healthcare systems such as Bangladesh, referral inefficiencies due to distance, diversion to inappropriate facilities and unsuitable hours of service are common, particularly for the urban poor. This study explores the reported referral networks of urban facilities and models alternative scenarios that increase referral efficiency in terms of distance and service hours. Methods Road network and geo-referenced facility census data from Sylhet City Corporation were used to examine referral linkages between public, private and NGO facilities for maternal and emergency/critical care services, respectively. Geographic distances were calculated using ArcGIS Network Analyst extension through a “distance matrix” which was imported into a relational database. For each reported referral linkage, an alternative referral destination was identified that provided the same service at a closer distance as indicated by facility geo-location and distance analysis. Independent sample t-tests with unequal variances were performed to analyze differences in distance for each alternate scenario modelled. Results The large majority of reported referrals were received by public facilities. Taking into account distance, cost and hours of service, alternative scenarios for emergency services can augment referral efficiencies by 1.5–1.9 km (p < 0.05) compared to 2.5–2.7 km in the current scenario. For maternal health services, modeled alternate referrals enabled greater referral efficiency if directed to private and NGO-managed facilities, while still ensuring availability after working-hours. These referral alternatives also decreased the burden on Sylhet City’s major public tertiary hospital, where most referrals were directed. Nevertheless, associated costs may be disadvantageous for the urban poor. Conclusions For both maternal and emergency/critical care services, significant distance reductions can be achieved for public, NGO and private facilities that avert burden on Sylhet City’s largest public tertiary hospital. GIS-informed analyses can help strengthen coordination between service providers and contribute to more effective and equitable referral systems in Bangladesh and similar countries.

Funder

Deutsche Gesellschaft für Internationale Zusammenarbeit

Publisher

Springer Science and Business Media LLC

Subject

Public Health, Environmental and Occupational Health

Reference51 articles.

1. United Nations. Department of economic and social affairs, population division. World urbanization prospects: the 2018 revision (ST/ESA/SER.A/420). New York: United Nations; 2019. https://population.un.org/wup/Publications/Files/WUP2018-Report.pdf. Accessed 9 Jan 2020.

2. Rydin Y, Bleahu A, Davies M, Dávila JD, Friel S, De Grandis G, et al. Shaping cities for health: complexity and the planning of urban environments in the 21st century. Lancet. 2012;379(9831):2079–108.

3. UN-Habitat. World cities report 2016: Urbanization and development- emerging futures. Nairobi: United Nations Human Settlements Programme (UN-Habitat); 2016. https://unhabitat.org/sites/default/files/download-manager-files/WCR-2016-WEB.pdf. Accessed 8 Jan 2020.

4. Hanson K, Berman P. Private health care provision in developing countries: a preliminary analysis of levels and composition. Health Policy Plan. 1998;13(3):195–211.

5. Harding A, Preker A, editors. Private participation in health services. Washington, DC: The World Bank; 2003.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3