Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-26T22:30:21.797Z Has data issue: false hasContentIssue false

VP182 Network Amongst The Health Technology Assessment Ecosystem

Published online by Cambridge University Press:  12 January 2018

Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
INTRODUCTION:

There has been a growing interest in international collaboration among Health Technology Assessment (HTA) organizations on macro, meso, and micro policy-making levels. Global member-driven professional HTA societies make contributions to scientific improvement and enhance interactions in the HTA ecosystem. However, little is known about collaboration between HTA organizations at the global level. This study intends to examine the main drivers of network relationships of HTA organizations.

METHODS:

Social network analysis was used to ascertain the relationships between HTA organizations and to visualize the main drivers of collaboration. The total number of memberships of the HTA organizations of the International Society For Pharmacoeconomics and Outcomes Research (ISPOR), Health Technology Assessment International (HTAi), International Netowork of Agencies for HTA (INAHTA), EuroScan, European Network for HTA (EUnetHTA), HTAsiaLink, Red de Evaluación de Tecnologías en Salud de las Américas (RedETSA) were considered to create the network. Ten different types of HTA organizations were considered in the analysis including the Ministry of Health (MoH), university, for-profit, and hospitals. The Fruchterman-Reingold algorithm was used to perform network analysis; average clustering coefficient and average path length were examined to measure collaborative performance.

RESULTS:

A network graph of the HTA ecosystem shows the highest collaborative frequency in terms of HTA organizations, occurred with members of the Ministry of Health, government agencies, universities, and non-profit organizations. The average path length was 2.21 and the average clustering coefficient was 36.576 which indicates an obvious clustering effect.

CONCLUSIONS:

These study results highlight that the network throughout the HTA ecosystem is driven by government organizations. Integrating the private sector into the system, creating common information and data sharing strategies, and improving the number of internationally experienced HTA professionals are essential strategies to foster collaboration in HTA organizations. As HTA is shaped by local dynamics and there is no gold standard for HTA implementation, encouragement of collaborative efforts is the only way to prevent duplication of effort and to make health technologies available for everyone.

Type
Vignette Presentations
Copyright
Copyright © Cambridge University Press 2018