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Estimation of mean health care costs and incremental cost-effectiveness ratios with possibly censored data

Author

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  • Shuai Chen

    (University of Wisconsin–Madison)

  • Jennifer Rolfes

    (T-Mobile)

  • Hongwei Zhao

    (Texas A&M Health Science Center)

Abstract

In this article, we describe the hcost program for estimating mean health care costs and incremental cost-effectiveness ratios with possibly censored data. hcost estimates the mean survival time and the mean costs, as well as their variances and covariance, for a given time horizon. If the group variable is specified, hcost will report the differences between two groups, as well as the incremental cost-effectiveness ratio and its confidence interval (optional). hcost can estimate the mean costs using two methods corresponding to different types of data: the Bang and Tsiatis (2000, Biometrika 87: 329–343) estimator using only the total costs or the Zhao and Tian (2001, Biometrics 57: 1002–1008) estimator when cost-history data are available. The hcost program can also be used to specify the annual discounting rates for survival time and costs. Copyright 2015 by StataCorp LP.

Suggested Citation

  • Shuai Chen & Jennifer Rolfes & Hongwei Zhao, 2015. "Estimation of mean health care costs and incremental cost-effectiveness ratios with possibly censored data," Stata Journal, StataCorp LP, vol. 15(3), pages 698-711, September.
    • Handle: RePEc:tsj:stataj:v:15:y:2015:i:3:p:698-711
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    Cited by:

    1. Benedetta Pongiglione & Aleksandra Torbica, 2022. "How real can we get in generating real world evidence? Exploring the opportunities of routinely collected administrative data for evaluation of medical devices," Health Economics, John Wiley & Sons, Ltd., vol. 31(S1), pages 25-43, September.

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