Development of an Economic Model to Assess the Cost Effectiveness of Asthma Management Strategies

Price, Martin; Briggs, Andrew

doi:10.2165/00019053-200220030-00004

Cited by 83 publications

(54 citation statements)

References 12 publications

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“…A total of 15 226,[252][253][254][255][256][257][258][259][260][261][262][263][264][265] published full-text studies were judged as full economic evaluations and met our inclusion criteria and involved adults with asthma. All of the 15 studies were published after 1994.…”

Section: Summary Of the Included Cost-effectiveness Studiesmentioning

confidence: 99%

Systematic review and economic analysis of the comparative effectiveness of different inhaled corticosteroids and their usage with long-acting beta2 agonists for the treatment of chronic asthma in adults and children aged 12 years and over

Shepherd¹,

Rogers²,

Anderson³

et al. 2008

Health Technol Assess

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Section: Summary Of the Included Cost-effectiveness Studiesmentioning

confidence: 99%

Systematic review and economic analysis of the comparative effectiveness of different inhaled corticosteroids and their usage with long-acting beta2 agonists for the treatment of chronic asthma in adults and children aged 12 years and over

Shepherd¹,

Rogers²,

Anderson³

et al. 2008

Health Technol Assess

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“…CEACs can now be found in major medical journals such as BMJ [1][2][3][4][5], New England Journal of Medicine [6,7], Lancet [8], Circulation [9], Chest [10] as well as health economics and health technology assessment journals [11][12][13][14][15][16][17]. Given the widespread dissemination of this technique it is important to ensure that both analysts and potential users of the information understand the nature and interpretation of these curves.…”

Section: Introductionmentioning

confidence: 99%

Cost‐effectiveness acceptability curves – facts, fallacies and frequently asked questions

2004

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Cost‐effectiveness acceptability curves (CEACs) have been widely adopted as a method to quantify and graphically represent uncertainty in economic evaluation studies of health‐care technologies. However, there remain some common fallacies regarding the nature and shape of CEACs that largely result from the ‘textbook’ illustration of the CEAC. This ‘textbook’ CEAC shows a smooth curve starting at probability 0, with an asymptote to 1 for higher money values of the health outcome (λ). But this familiar ‘ogive’ shape which makes the ‘textbook’ CEAC look like a cumulative distribution function is just one special case of the CEAC. The reality is that the CEAC can take many shapes and turns because it is a graphic transformation from the cost‐effectiveness plane, where the joint density of incremental costs and effects may ‘straddle’ quadrants with attendant discontinuities and asymptotes. In fact CEACs: (i) do not have to cut the y‐axis at 0; (ii) do not have to asymptote to 1; (iii) are not always monotonically increasing in λ; and (iv) do not represent cumulative distribution functions (cdfs). Within this paper we present a ‘gallery’ of CEACs in order to identify the fallacies and illustrate the facts surrounding the CEAC. The aim of the paper is to serve as a reference tool to accompany the increased use of CEACs within major medical journals. Copyright © 2004 John Wiley & Sons, Ltd.

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“…A child is considered to be in a negative asthma state if he or she has had a health care encounter to treat an asthma exacerbation or has had excessive use of rescue medication; otherwise he or she is in a stable asthma state. This definition is based on the Global Initiative on Asthma (GINA) and is similar to indices used in other studies of asthma exacerbations (see Price andBriggs, 2002 andStempel et al, 2005). Since there are two possible states before and after participation, H i has four possible values, as illustrated in Figure III.…”

Section: Evaluation Resultsmentioning

confidence: 99%

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

Brandt

Gale

Tager³

2009

SSRN Journal

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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.Keywords: Asthma, treatment effect, health intervention, propensity scores JEL Classification: I1, D13, H51, C31, C80, C81, C83 _______________________ Estimation of Treatment Effect of Asthma Case Management Using Propensity Score MethodsObjective: 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 nonparticipants 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 dis...

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Development of an Economic Model to Assess the Cost Effectiveness of Asthma Management Strategies

Cited by 83 publications

References 12 publications

Systematic review and economic analysis of the comparative effectiveness of different inhaled corticosteroids and their usage with long-acting beta2 agonists for the treatment of chronic asthma in adults and children aged 12 years and over

Systematic review and economic analysis of the comparative effectiveness of different inhaled corticosteroids and their usage with long-acting beta2 agonists for the treatment of chronic asthma in adults and children aged 12 years and over

Cost‐effectiveness acceptability curves – facts, fallacies and frequently asked questions

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

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