AN AGENT-BASED APPROACH TO IMPROVING RESOURCE ALLOCATION IN THE DUTCH YOUTH HEALTH CARE SECTOR

1. AN AGENT-BASED APPROACH TO IMPROVING RESOURCE ALLOCATION IN THE DUTCH YOUTH HEALTH CARE SECTOR Erik Giesen1, Wolfgang Ketter2, Rob Zuidwijk2 1INITI8, 2Erasmus University Rotterdam, 09-06-2009

2. NEWSLINES • Extra money for removing youth care waiting lists (RTV Noord, 29 October 2008) • Additional money for waiting lists in youth care (Regering.nl, 9 January 2008) • More money to the big cities for youth care (ANP, 11 November 2008) • Millions extra for youth health care (ANP, 4 September 2008) An agent-based approach to improving resource allocation in the Dutch youth health care sector

3. CONTEXT Care provider A Care provider A Care provider A Care provider B Care provider B Care provider B Care provider C Care provider C Care provider C Care provider D Care provider D Care provider D Province Province Province Institution for youth health care Institution for youth health care Institution for youth health care € € € € € € Government € € € An agent-based approach to improving resource allocation in the Dutch youth health care sector

4. CONTEXT MOTIVATION: • Lack of scientific research for resource allocation in health care taking into account the rich level of complexity in waiting line behavior by incorporating multi-agent theory based on an extensive amount of real-world data. Resource allocation Care provider A Care provider B Care provider C Care provider D Institution for youth health care An agent-based approach to improving resource allocation in the Dutch youth health care sector

5. RESEARCH OBJECTIVE OBJECTIVE Improve the resource allocation process between: • the institution for youth health care • the associated care providers by: • designing an experimental platform based on: • multi agent simulation • real world data MAIN QUESTIONS • What are relevant characteristics of the resource allocation process? • How can a queue management in the youth care sector be organised? • What should a simulation model of the youth care sector look like? • Which factors influence the choice for an optimal queue management philosophy? An agent-based approach to improving resource allocation in the Dutch youth health care sector

6. METHODOLOGY BLOCK DIAGRAM SIMULATION Sources Input analyses Modeling Output analyses Reporting Key Performance Indicators Allocation behavior Expert Interviews Simulation model Experiments Results Case selection behavior Data analyses Real world data Validation An agent-based approach to improving resource allocation in the Dutch youth health care sector

7. RELEVANT CHARACTERISTICS OF THE RESOURCE ALLOCATION PROCESS • Many factors including: • a withdrawal and return mechanism • a non-stationary Poisson arrival process • single child and group based treatment • age based in/exclusion filters • geographical bounded allocation • but most importantly… • a preference algorithm to include a care provider’s case preference • Real world case selection at the care providers: Age related dependencies Queue of waiting cases Potential cases Case selection for treatment Political influence An agent-based approach to improving resource allocation in the Dutch youth health care sector

8. RELEVANT CHARACTERISTICS OF THE RESOURCE ALLOCATION PROCESS • Example of the political influenced decision process: An agent-based approach to improving resource allocation in the Dutch youth health care sector

9. QUEUE MANAGEMENT STRATEGIES IN THE YOUTH CARE SECTOR Push to decentralized queues Push from a centralized queue 1 2 Free Free Push Push 4 3 Pull to decentralized queues Pull from centralized queue Pull Pull An agent-based approach to improving resource allocation in the Dutch youth health care sector

10. FACTORS OF INFLUENCE FOR CHOSING THE OPTIMAL ALLOCATION STRATEGY THE 5 KEY PERFORMANCE INDICATORS USED FOR EVALUATION • Waiting line aspects • Cases on the waiting list • Aggregated waiting time • Service level aspects • Cases taken into care • Cases withdrawn • Utilization of resources MEASUREMENT • Average system performance (AVG) • Difficult case performance (DIF) Pull Decentral Pull Central Push Central Push Decentral An agent-based approach to improving resource allocation in the Dutch youth health care sector

11. CONCLUSIONS & CONTRIBUTION CONCLUSIONS • The current system evokes neglecting of difficult cases • Choosing an optimal allocation strategy depends on the relative importance of the difficult cases over the remaining cases • We, however, advise the push from a centralized queue strategy CONTRIBUTION • Successful implementation of an agent-based simulation model in a real world setting with real world data • A simulation platform including a high level of complexity for studying waiting line scenarios in youth health care • Advise for an improved allocation strategy based on experiments with varying scenarios An agent-based approach to improving resource allocation in the Dutch youth health care sector

12. FUTURE WORK FUTURE WORK: • In-depth analysis on the political influenced decision process at the care providers. • Implementation of a human preference model in the decision making process at the institution of youth health care. • Experiments with alternative strategies which include auctioning mechanisms. An agent-based approach to improving resource allocation in the Dutch youth health care sector

13. TIME FOR QUESTIONS An expert knows all the answers -- if you ask the right questions.

14. Erik Giesen Wolgang Ketter Rob ZuidwijkINITI8 Erasmus University Erasmus UniversityGiesen@initi8.nl WKetter@rsm.nl RZuidwijk@rsm.nl INITI8, Erasmus University Rotterdam, 09-06-2009