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Joe Dinius ECE508 15 Oct 2009.  Introduction  Review of the Literature  Hypotheses  Model Description  Parameters  Results  Sensitivity Analysis.

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Presentation on theme: "Joe Dinius ECE508 15 Oct 2009.  Introduction  Review of the Literature  Hypotheses  Model Description  Parameters  Results  Sensitivity Analysis."— Presentation transcript:

1 Joe Dinius ECE508 15 Oct 2009

2  Introduction  Review of the Literature  Hypotheses  Model Description  Parameters  Results  Sensitivity Analysis  Conclusions

3  Healthcare is a pressing issue in American society ◦ Economic Recovery ◦ Public Welfare  Current public health data is insufficient to evaluate impact to public health impact due to uninsured  Agent-based simulation provides flexible framework for evaluating impact of uninsured to overall public health

4  Parameters of interest will be means and standard deviations of ◦ Cost ◦ Resource Utilization (Hospitalization) ◦ Time for epidemic to end  Agents are simple ◦ Interaction rule is nearest-neighbor disease propagation ◦ Hypothetical disease presented requiring hospitalization (resource utilization)

5  HUS08 publishes average data ◦ Percentage of Americans who are uninsured ◦ Cost of private vs. public insurance  Average results are misleading as not every condition requires treatment  Need data from catastrophic life events requiring hospitalization  Provides comparison between privately insured and uninsured  Other studies completed comparing FFS vs. managed care case studies for pregnant women in California

6  Lower percentage of uninsured agents should lead to lower epidemic time  Should be difference in cost structure as number of uninsured agents increases  Non-profit insurance should ensure better care at less net cost

7  One agent is infected at initialization  Random draw for susceptibility of nearest- neighbors is performed and agents are infected accordingly  Agents are hospitalized one day after being infected and social network is broken  Agents are hospitalized until treatment time ends ◦ If released before fully treated, time to be cured of the disease increases by a scale factor

8  After infection occurs, agents’ susceptibility goes to 0  Simulation runs until number of infected agents is 0

9  Insurance status ◦ Cost ◦ Treatment time  Susceptibility  Cure time  Scale factor for cure time

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11  Refer to paper for statistical tables of output

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13  Less statistically significant differences than expected ◦ Cost ◦ Resource Utilization ◦ Epidemic Duration  Metrics focused on were averaging ◦ Less impact on results from transients  Hypothetical disease model suggests macroscopic view of contemporary healthcare problem is incomplete

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