This document analyzes the social network of collaborations within REBRATS, Brazil's national health technology assessment network. A social network analysis of 435 studies from 2009-2014 found 1094 researchers from 249 institutions collaborating within 101 communities. Central institutions with the most collaborators included FIOCRUZ, UFBA, USP, UFMG and UFRGS. The analysis provides insights into the structure and performance of research networks that can help inform their expansion and management to address increasing demands on health technology assessment.

1. Social Network Analysis of HTA Collaborations:
the case of REBRATS
Tazio Vanni
General Coordinator of Health Technology Assessment
Department of Science and Technology
Secretariat of Science, Technology and Strategic Inputs
Brazilian Ministry of Health

2. Research team
• Luciana Leão
• Rodrigo Costa
• Flávia Elias
• Juliana Girardi
• Lucas Felipe
• Oney Araújo
• Elenilda Martins

3. Introduction
• Health Technology Assessment (HTA) is becoming
increasingly multidisciplinary.
• Policy-makers and researchers are relying more on
multi-institutional networks to develop strong,
intellectually diverse teams that can answer complex
research questions.
• National governments have promoted HTA networks in
order:
– to develop useful HTA studies
– to support capacity building among health care workers
and policy-makers
– to foster sustainable health systems

4. Saúde e CT&I: Inovação para o acesso
Social and Economic
Development
Health System Science and
Technology
System

5.  Objective: To integrate health researchers and decision-
makers in the promotion, development and diffusion of
health technology assessment to support a sustainable
Brazilian National Health System.
 Working groups:
1. Research Prioritization and Promotion;
2. Methodological Development and Evaluation;
3. Professional Training and Continuous Education;
4. Information and Communication Management;
5. Technological Horizon Scanning;
6. Health Services Research.
 Members: Currently 81 institutions, including research
centres, hospitals, universities, federal, regional and
municipal health agencies.
 Coordination: Joint Committee lead by
the Department of Science and
Technology, Ministry of Health
 Investment: ~US$ 10 millions
 Studies: 435 studies

6. Introduction
• Social network analysis (SNA) can be used to
evaluate collaborations between institutions and
groups.
• SNA has the potential:
– to identify hubs and authorities
– to improve information diffusion and consensus
building
– to monitor and evaluate integration among
institutions
– to inform expansion and restructuring plans

7. Objective
• No peer-reviewed publications investigating
networks in HTA could be found in Medline
and Embase.
• The overall objective of this study was to
evaluate patterns of scientific collaboration in
HTA networks, using REBRATS as a case study.

8. Methods
• REBRATS relies on a virtual repository
(SISREBRATS), which is the largest repository
of HTA studies in Portuguese.
• From the 396 studies included in SISREBRATS
from 11/2009 to 09/2014, we extracted data
for authors’ names, institutional affiliation and
location (state in Brazil).

9. Methods
• We developed a programme in C++ to
structure the data extracted in mixing
matrices.
• Gephi open-source network analysis software
for visualization and exploration of networks
and complex systems.
• Network layout was defined using the
Fruchterman-Reingold and Force Atlas 2
algorithms.

10. SNA metrics
• Nodes metrics included centrality and
betweenness.
• Network statistics included density, connected
components, diameter, average distance
between nodes and clustering coefficient.

11. Methods
• Individuals were classified according to time
since graduation, gender and education.
• Institutions were classified according to
REBRATS membership, the region they were
based and type of institution.

12. 12
Number of Researchers: 1094
Number of communities: 101
Density: 0.008
Average centrality: 9.13

13. Top 10 authors Centrality Institution Top 10 authors Betweenness Institution
Francisco Acurcio 52 UFMG Flavia Elias 20.086 Fiocruz
Carisi Polanczky 50 IATS Denizar Vianna 71.312 UERJ
Edina Koga 41 UNIFESP Braulio Luna 16.848 UNIFESP
Jose Jardim 35 UNIFESP Carisi Polanczky 16.630 IATS
Tais Galvao 30 UFAM
Francisco
Acurcio 15.849 UFMG
Flavia Elias 29 FIOCRUZ Cid Manso 13.689 IMS UERJ
Braulio Luna 28 UNIFESP Claudia Coeli 12.056 UFRJ
Luis Rohde 28 UFRGS
Marcus
Tolentino 10.484 UFAM
Jorge Ribeiro 28 UFRGS Marisa Santos 10.399 INC RJ
Regis Andriolo 28 UEP Bernardo Tura 9.591 INC RJ

14. 0%
5%
10%
15%
20%
25%
30%
2 - 12 13 - 22 23- 32 33 - 42 43 - 52
Time since first graduation
0%
10%
20%
30%
40%
50%
60%
Male Female
Gender
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
MSc/MA PHD Experts* Graduates
Educational Level

15. 15
Number of institutions: 249
Number of REBRATS members: 78
Average nº collaborators (members): 16
Average nº collaborators (non-members): 7

16. Network statistics
Number of nodes
Average degree
Density
Average clustering coefficient
Number of connected components
249
9.373
0,037
0.767
1

17. Institution Centrality Institution Betweenness
FIOCRUZ 87 FIOCRUZ 0.2198
UFBA 63 USP 0.1427
USP 61 UFBA 0.1196
UFMG 52 UFRGS 0.1132
UFRGS 52 UFMG 0.1071
UERJ 49 UFSC 0.0900
HCPA 47 HCPA 0.0776
UFRJ 46 UERJ 0.0757
SVS_MS 42 UNICAMP 0.0556
UFSC 37 FM_USP 0.0433

19. Universities/Research Institutes
Government
Health Services

20. Discussion
• We have shown that SNA is instrumental to
monitor and evaluate, as well as to inform the
expansion and restructuring plans for HTA
networks, and possibily other research networks.
• There are different dimensions of collaborations
that should be further investigated.
• The creation, evolution and integration should be
further explored.

21. Discussion
• More comprehensive datasets with other
variables that can explain the structure and
performance of these networks.
• Combination of datasets and methods should be
employed to further our understanding of these
networks.
• Development of impact assessment tools for
research networks.
• Define guidelines for the creation and
management of research networks.

22. Discussion
• There are still many questions for which the
HTA community has not provided answers.
• The increase in life expectancy and the
epidemiological transition coupled with the
growth of the knowledge economy are
increasing the preassure on the HTA
community to develop new assessment tools.
• To met these challenges we have to consider
what are the optimal research ecosystems.

23. Thank you
tazio.vanni@saude.gov.br