PUBLICATION MANUAL OF BUDGET IMPACT ANALYSIS (BIA) BY THE DEPARTMENT OF SCIENCE AND TECHNOLOGY OF THE MINISTRY OF HEALTH (DECIT)
Author(s)
Koury Cd1, Elias FT2
1FIPE -Fundação de Ensino e Pesquisas Econômicas, Brasilia, Brazil, 2Ministry of Health of Brazil, Brasilia, Brazil
The epidemiological and economic methods applied to health technologies evaluations had a significant development in the last two decades. The need to balance the incorporation of new technologies in health care and limited financial resources promoted the construction and application of instruments supporting the decision making of health technology. The requirement Budget Impact Analysis formally stated in Law 12.401/2011 establishing the incorporation process technologies in SUS. In this context, in 2010/2011, the National Agency of Sanitary Surveillance (ANVISA) and DECIT, in partnership Institute for Health Technology Assessment (IATS) for drawing up of this guideline. In the first stage of development were used international recommendations of Canada, Australia, the UK and Poland, the recommendations of the International Society for PharmacoEconomics and Outcomes Research (ISPOR) and the methods used in studies of budgetary impact that had already been published. Afterwards, drafted a preliminary version of the Guideline and a standard tool - Excel worksheets - to estimate the uptake of monetary resources required for adoption of new technologies. Revisions were carried out by technicians DECIT and health agencies, and the proposal was submitted to the Working Group on Development of Methodology REBRATS, composed of experts and academic researchers from several Brazilian states. Were also carried out workshops for the application of spreadsheets. In 2012, the first edition of the Guidelines was published two thousand copies in Portuguese in order to provide best practice recommendations for studies of budget impact.
Conference/Value in Health Info
2014-11, ISPOR Europe 2014, Amsterdam, The Netherlands
Value in Health, Vol. 17, No. 7 (November 2014)
Code
PRM256
Topic
Methodological & Statistical Research
Topic Subcategory
Confounding, Selection Bias Correction, Causal Inference
Disease
Multiple Diseases