Antiviral treatment for outpatient use during an influenza pandemic: a decision tree model of outcomes averted and cost-effectiveness.
J Public Health (Oxf)
; 41(2): 379-390, 2019 06 01.
Article
en En
| MEDLINE
| ID: mdl-29955851
ABSTRACT
BACKGROUND:
Many countries have acquired antiviral stockpiles for pandemic influenza mitigation and a significant part of the stockpile may be focussed towards community-based treatment.METHODS:
We developed a spreadsheet-based, decision tree model to assess outcomes averted and cost-effectiveness of antiviral treatment for outpatient use from the perspective of the healthcare payer in the UK. We defined five pandemic scenarios-one based on the 2009 A(H1N1) pandemic and four hypothetical scenarios varying in measures of transmissibility and severity.RESULTS:
Community-based antiviral treatment was estimated to avert 14-23% of hospitalizations in an overall population of 62.28 million. Higher proportions of averted outcomes were seen in patients with high-risk conditions, when compared to non-high-risk patients. We found that antiviral treatment was cost-saving across pandemic scenarios for high-risk population groups, and cost-saving for the overall population in higher severity influenza pandemics. Antiviral effectiveness had the greatest influence on both the number of hospitalizations averted and on cost-effectiveness.CONCLUSIONS:
This analysis shows that across pandemic scenarios, antiviral treatment can be cost-saving for population groups at high risk of influenza-related complications.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Contexto en salud:
1_ASSA2030
/
2_ODS3
Problema de salud:
1_financiamento_saude
/
2_enfermedades_transmissibles
Asunto principal:
Antivirales
/
Árboles de Decisión
/
Gripe Humana
/
Pandemias
Tipo de estudio:
Health_economic_evaluation
/
Prognostic_studies
Límite:
Humans
País/Región como asunto:
Europa
Idioma:
En
Revista:
J Public Health (Oxf)
Año:
2019
Tipo del documento:
Article
País de afiliación:
Reino Unido