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Estimation of Treatment Effect of Asthma Case Management Using Propensity Score Methods

Author

Listed:
  • Sylvia Brandt

    () (Department of Resource Economics, University of Massachusetts Amherst)

  • Sara Gale

    () (Department of Epidemiology, University of California Berkeley)

  • Ira Tager

    () (Department of Epidemiology, University of California Berkeley)

Abstract

Objective: To estimate the treatment effect from participating in an asthma intervention that was part of the National Asthma Control Program. Study Setting: Data on children who participated in asthma case management (N=270) and eligible children who did not participate in case management (N=2,742) were extracted from a claims database. Study Design: We created 81 measures of health care utilization and 40 measures of neighborhood characteristics that could be related to participation in the program. The participation model was selected using the cross-validation-based Deletion Substitution and Addition (DSA) algorithm. We used optimal full matching for the vector of Mahalanobis’ distances and propensity scores to estimate the difference between participants and non-participants in the probability of a range of asthma outcomes. Principal Findings: Compared to non-participants, participants were more likely to have vaccinations for pulmonary illness, use controller medications, and have a refill for rescue medication. There was no statistically significant difference in the number of nebulizer treatments or ED visits between the two groups. We find that the asthma program had no significant effect on overall asthma control. Conclusion: We are not able to discern whether the lack of an effect in overall control is due to the effectiveness of the program, heterogeneity of effects or barriers outside the program’s control. We discuss how current programs could be modified to better inform future research and program design

Suggested Citation

  • Sylvia Brandt & Sara Gale & Ira Tager, 2009. "Estimation of Treatment Effect of Asthma Case Management Using Propensity Score Methods," Working Papers 2009-3, University of Massachusetts Amherst, Department of Resource Economics.
  • Handle: RePEc:dre:wpaper:2009-3
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    File URL: http://courses.umass.edu/resec/workingpapers/documents/ResEcWorkingPaper2009-3.pdf
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    1. repec:aph:ajpbhl:10.2105/ajph.2004.042994_0 is not listed on IDEAS
    2. Perry, Cynthia D., 2008. "Does treating maternal depression improve child health management The case of pediatric asthma," Journal of Health Economics, Elsevier, vol. 27(1), pages 157-173, January.
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    Keywords

    Asthma; treatment effect; health intervention; propensity scores;

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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