Modeling the potential impact of a prescription drug copayment increase on the adult asthmatic medicaid population

Modeling Healthcare Costs Attributable to Secondhand Smoke Exposure at Home among South Korean Children

Children exposed to secondhand smoke (SHS) are at increased risk for disease. We sought to estimate the medical costs among Korean children who were exposed to SHS at home. A Markov model was developed, including five diseases (asthma, acute otitis media, acute bronchitis, pneumonia and sudden infant death syndrome) that were significantly associated with SHS in children based on a systematic review. The time horizon of the analysis was 20 years (from birth to adulthood), and the cycle length was 1 week. The direct healthcare costs were discounted annually at 5%. Univariate and probabilistic sensitivity analyses were conducted. The Markov model estimated the healthcare costs for 20 years as 659.61 USD per exposed child, an increase of approximately 30% compared to the cost per unexposed child (507.32 USD). Sensitivity analysis suggested that the younger the age of the exposure, the greater the incremental healthcare costs incurred, implying that infants and young children were especially vulnerable to the SHS exposure. Findings of this study could provide key baseline data for future economic evaluations on SHS control policies in South Korea.

A Systematic Review of Decision-Analytic Models for Evaluating Cost-Effectiveness of Asthma Interventions

OBJECTIVE

To demonstrate the landscape of model-based economic studies in asthma and highlight where there is room for improvement in the design and reporting of studies.

DESIGN

A systematic review of the methodologies of model-based, cost-effectiveness analyses of asthma-related interventions was conducted. Models were evaluated for adherence to best-practice modeling and reporting guidelines and assumptions about the natural history of asthma.

METHODS

A systematic search of English articles was performed in MEDLINE, EMBASE, and citations within reviewed articles. Studies were summarized and evaluated based on their adherence to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS). We also studied the underlying assumptions about disease progression, heterogeneity in disease course, comorbidity, and treatment effects.

RESULTS

Forty-five models of asthma were included (33 Markov models, 10 decision trees, 2 closed-form equations). Novel biological treatments were evaluated in 12 studies. Some of the CHEERS' reporting recommendations were not satisfied, especially for models published in clinical journals. This was particularly the case for the choice of the modeling framework and reporting on heterogeneity. Only 13 studies considered any subgroups, and 2 explicitly considered the impact of comorbidities. Adherence to CHEERS requirements and the quality of models generally improved over time.

CONCLUSION

It would be difficult to replicate the findings of contemporary model-based evaluations of asthma-related interventions given that only a minority of studies reported the essential parameters of their studies. Current asthma models generally lack consideration of disease heterogeneity and do not seem to be ready for evaluation of precision medicine technologies.