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Related Experiment Videos

Treatment on demand: an operational model.

E H Kaplan1, M Johri

  • 1Yale School of Management, New Haven, CT 06520-8200, USA. edward.kaplan@yale.edu

Health Care Management Science
|July 25, 2000
PubMed
Summary
This summary is machine-generated.

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Achieving "treatment on demand" for substance abuse requires understanding capacity. This study models treatment flows to estimate needed capacity, queue lengths, and waiting times for immediate program entry.

Area of Science:

  • Public Health
  • Health Services Research
  • Mathematical Modeling

Background:

  • Substance abuse treatment systems often face demand exceeding supply.
  • Limited understanding exists on factors influencing treatment access, such as queues and waiting times.
  • The capacity needed to achieve "treatment on demand" remains understudied.

Purpose of the Study:

  • To develop a mathematical model for drug treatment flows.
  • To estimate the treatment capacity required to eliminate queues and achieve "treatment on demand".
  • To analyze the costs and benefits associated with increasing treatment capacity.

Main Methods:

  • Development of a mathematical model simulating drug treatment system dynamics.
  • Estimation of queue lengths, waiting times, and admission probabilities based on treatment capacity.

Related Experiment Videos

  • Application of the model to a case study in San Francisco.

    • Main Results:

    • The model provides estimates for queue lengths and waiting times at various treatment capacities.
    • It identifies the specific capacity needed to enable immediate entry into substance abuse treatment.
    • The model allows for cost-benefit analyses of expanding treatment capacity.

    Conclusions:

    • Mathematical modeling is crucial for understanding and optimizing substance abuse treatment systems.
    • Significant increases in treatment capacity are likely necessary to meet the goal of "treatment on demand".
    • The developed model can inform policy decisions regarding resource allocation and system improvements.