Designing Referral Network Structures and Decision Rules to Streamline Provision of Urgent Health and Human Services
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Authors
Gibbons, Deborah E.
Samaddar, Subhashish
Subjects
Agent-Based Models
Computational Models
Emergency Services
Health Care
Humanitarian Logistics
Interorganizational Networks
Network Structures
Public Health Systems
Referral Networks
Referral Partners
Simulation
Social Networks
Vaccine Delivery
Computational Models
Emergency Services
Health Care
Humanitarian Logistics
Interorganizational Networks
Network Structures
Public Health Systems
Referral Networks
Referral Partners
Simulation
Social Networks
Vaccine Delivery
Advisors
Date of Issue
2009-05
Date
Publisher
Decision Sciences Institute
Language
Abstract
This study uses fully factorial computer simulation to identify referral network attributes and referral decision rules that streamline the routing of people to urgent, limited services. As an example of a scenario, the model represents vaccine delivery in a city of 100,000 people during the first 30 days of a pandemic. By modeling patterns of communication among health care providers and daily routing of overflow clients to affiliated organizations, the simulations determine cumulative effects of referral network designs and decision rules on citywide delivery of available vaccines. Referral networks generally improve delivery rates when compared with random local search by clients. Increasing the health care organizations’ tendencies to form referral partnerships from zero to about four partners per organization sharply increases vaccine delivery under most conditions, but further increases in partnering yield little or no gain in system performance. When making referrals, probabilistic selection among partner organizations that have any capacity to deliver vaccines is more effective than selection of the highest-capacity partner, except when tendencies to form partnerships are very low. Implications for designing health and human service referral networks and helping practitioners optimize their use of the networks are discussed. Suggestions for using simulations to model comparable systems are provided.
Type
Article
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Citation
Decision Sciences, Volume 40, Number 2, May 2009.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.