Chapter title |
Health Technology Assessment and Appraisal of Therapies for Rare Diseases
|
---|---|
Chapter number | 13 |
Book title |
Rare Diseases Epidemiology: Update and Overview
|
Published in |
Advances in experimental medicine and biology, January 2017
|
DOI | 10.1007/978-3-319-67144-4_13 |
Pubmed ID | |
Book ISBNs |
978-3-31-967142-0, 978-3-31-967144-4
|
Authors |
Georgi Iskrov, Tsonka Miteva-Katrandzhieva, Rumen Stefanov |
Abstract |
Innovative rare disease therapies and health technology assessment (HTA) share a lot of similarities. Both represent cases of interaction of epidemiology and health economics. Both are relatively new topics in public health practice. And both pose a lot of challenges to rare disease stakeholders who are currently looking for tools to support the timely access to innovative treatments while putting budget spending in order. This is why optimisation of assessment and appraisal of new rare disease therapies is a fundamental issue in rare disease health policy. Rare disease patients and caregivers expect prolonged life expectancy and improved quality of life and they perceive innovative health technologies as a rightful way to achieve these objectives.Multi-criteria decision analysis (MCDA) provides a structured, transparent approach to identify preferred alternatives by means of combined calculation of relative importance of different criteria and performance of the alternatives on these criteria. The labyrinth of competing interests and numerous stakeholders involved is why innovative rare disease health technologies make an excellent case study of the integration between HTA and MCDA. This kind of formalisation of decision-making is perceived as fair and legitimate, leading to a balance and agreement. MCDA provides a stage for a debate of policy priorities, health system specifics and societal attitudes, while also addressing the impact of rarity on all criteria and considerations. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 89 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 15 | 17% |
Researcher | 11 | 12% |
Student > Bachelor | 5 | 6% |
Student > Ph. D. Student | 5 | 6% |
Student > Doctoral Student | 4 | 4% |
Other | 14 | 16% |
Unknown | 35 | 39% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 14 | 16% |
Nursing and Health Professions | 10 | 11% |
Economics, Econometrics and Finance | 6 | 7% |
Pharmacology, Toxicology and Pharmaceutical Science | 6 | 7% |
Social Sciences | 5 | 6% |
Other | 13 | 15% |
Unknown | 35 | 39% |