Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-23T02:31:52.012Z Has data issue: false hasContentIssue false
  • English
  • Français

INTEGRATE-HTA: A LOW- AND MIDDLE-INCOME COUNTRY PERSPECTIVE

Published online by Cambridge University Press:  06 November 2017

Leon Bijlmakers Open the ORCID record for Leon Bijlmakers [Opens in a new window] ,
Debjani Mueller ,
Rabia Kahveci ,
Yingyao Chen  and
Gert Jan van der Wilt
Leon Bijlmakers
Affiliation:
Radboud University Medical Centre, [email protected]
Debjani Mueller
Affiliation:
Charlotte Maxeke Research Cluster (CMeRC)
Rabia Kahveci
Affiliation:
Ankara Numune, Health Technology Assessment Unit (ANHTA)
Yingyao Chen
Affiliation:
Key Lab of Health Technology Assessment, School of Public Health, Fudan University
Gert Jan van der Wilt
Affiliation:
Radboud University Medical Centre
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives: The INTEGRATE-HTA project recommends that complexity be taken into account when conducting health technology assessments (HTAs) and suggests a five-step process for doing that. This study examines whether the approach suggested by INTEGRATE-HTA could be useful, appropriate, and feasible in the context of low- and middle-income countries (LMIC) given some of the typical challenges that healthcare systems face in those countries.

Methods: A nonexhaustive literature review was performed on the implementation in low and middle income countries of the five aspects recommended by the INTEGRATE-HTA project, using the following search terms: national health planning, health sector strategy, health sector performance, assessment criteria, health (management) information, complexity, context, stakeholder consultation.

Results: HTA is being practiced in LMIC in various ways and through different mechanisms, for example in health sector reviews, even though it is usually not referred to as HTA. It does not necessarily follow the five steps distinguished in the INTEGRATE-HTA model (scoping; defining the initial logic model; providing concepts and methods to identify, collect, and synthesize evidence in relation to various dimensions; extracting and presenting evidence in respect of agreed assessment criteria; providing guidance to draw conclusions and formulate recommendations).

Conclusions: The conditions for functional HTA are not always fulfilled in LMICs. At least four aspects would require special attention: (a) the scope and quality of routine health information that can support and be fed into health technology assessments and strategic planning; (b) consensus on health system performance assessment frameworks and their main criteria, in particular the inclusion of social disparities/equity and sustainability; (c) institutional capacity to set evidence-based priorities based on a variety of explicit criteria; (d) political will to engage with stakeholders in a transparent and inclusive consultation process about health priorities.

Keywords

Health technology assessmentPriority settingUniversal health coverage
Type
Theme Submissions
Information
International Journal of Technology Assessment in Health Care , Volume 33 , Issue 5: Assessing Health Technologies in an Integrated Way-Results of the INTEGRATE-HTA Project , 2017 , pp. 599 - 604
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Wahlster, P, Brereton, L, Burns, J, et al. Guidance on the integrated assessment of complex health technologies – The INTREGRATE-HTA Model. 2016. http://www.integrate-hta.eu/downloads/ (accessed August 4, 2017).Google Scholar
2. Lopez, AD. Global burden of disease and risk factors. World Bank Publications; 2006.Google Scholar
3. Bradshaw, D, Groenewald, P, Laubscher, R, et al. Initial burden of disease estimates for South Africa, 2000. S Afr Med J. 2003;93: 682–688.Google Scholar
4. Peabody, JW. Economic reform and health sector policy: Lessons from structural adjustment programmes. Soc Sci Med. 1996;43: 823–835.Google Scholar
5. , Bijlmakers L. Structural adjustment: Source of structural adversity – Socio-economic stress, health and child nutritional status in Zimbabwe. Dissertation. African Studies Centre, Leiden, Research report 69/2003.Google Scholar
6. WHO. Health in 2015: From MDGs to SDGs. Geneva: World Health Organization; 2015.Google Scholar
7. Atun, R. Health systems, systems thinking and innovation – Commentary. Health Policy Plan. 2012;27 (Suppl 4):iv4-iv8.Google Scholar
8. Adam, T, de Savigny, D. Systems thinking for strengthening health systems in LMICs: Need for a paradigm shift. Health Policy Plan. 2012;27 (Suppl 4):iv1-iv3.Google Scholar
9. Aranda-Jan, CB, Jagtap, S, Moultrie, J. Towards a framework for holistic contextual design for low-resource settings. Int J Design. 2016;10: 43–63.Google Scholar
10. McMahon, SA, Brenner, S, Lohman, J, et al. Evaluating complex health financing interventions: Using mixed methods to inform further implementation of a novel PBI intervention in rural Malawi. BMC Health Serv Res. 2016;16:414. doi:10.1186/s12913-016-1612-2.CrossRefGoogle ScholarPubMed
11. Subramanian, S, Naimoli, J, Matsubayashi, T, Peters, D. Do we have the right models for scaling up health services to achieve the Millennium Development Goals? BMC Health Serv Res. 2011;11:336. doi:10.1186/1472-6963-11-336.Google Scholar
12. Paina, L, Peters, DH. Understanding pathways for scaling up health services through the lens of complex adaptive systems. Health Policy Plan. 2012;27:365–373.Google Scholar
13. Noordam, AC, George, A, Sharkey, AB, et al. Assessing scale-up of mHealth innovations based on intervention complexity: Two case studies of child health programs in Malawi and Zambia. J Health Commun. 2015;20:343–353. doi.org/10.1080/10810730.2014.965363.Google Scholar
14. Chaulagai, CN, Moyo, CM, Koot, J, et al. Design and implementation of health management information system in Malawi: Issues, innovations and results. Health Policy Plan. 2005;20:375–384.Google Scholar
15. Akhlaq, A, McKinstry, B, Bin Muhammad, K, Sheikh, A. Barriers and facilitators to health information exchange in low- and middle-income country settings: A systematic review. Health Policy Plan. 2016;31:1310–1325.CrossRefGoogle ScholarPubMed
16. OECD/DAC. Principles for evaluation of development assistance. Paris: OECD / Development Assistance Committee; 1991.Google Scholar
17. Kruk, ME, Freeman, LP. Assessing health system performance in developing countries: A review of the literature. Health Policy. 2008;85:263–276.Google Scholar
18. WHO. Everybody's business – Strengthening health systems to improve health outcomes: WHO's framework for action. Geneva: World Health Organization; 2007.Google Scholar
19. Lauer, JA, Rajan, D, Bertram, MY. Priority setting for universal health coverage: We need to focus both on substance and on process. Int J Health Policy Manag. 2017;6:1–3.Google Scholar
20. Zida, A, Lavis, JN, Sewankambo, NK, et al. Analysis of the policymaking process in Burkina Faso's health sector: Case studies of the creation of two health system support units. Health Res Policy Syst. 2017;15:10.Google Scholar
21. Baltussen, R, Mitton, C, Danis, M, Williams, I, Gold, M. Global developments in priority setting in health. Int J Health Policy Manag. 2017;6:127–128.Google Scholar
22. Baltussen, R, Jansen, MP, Mikkelsen, E, et al. Priority setting for Universal Health Coverage: We need evidence-informed deliberative processes, not just more evidence on cost-effectiveness. Int J Health Policy Manag. 2016; 5:615–618.Google Scholar
23. Tromp, N. Priority setting in HIV/Aids control: The use of multi-criteria decision analysis in Indonesia and South Africa. Dissertation, Radboud UMC, Nijmegen; 2015.Google Scholar
24. Panteli, D, Kreis, J, Busse, R. Considering equity in health technology assessment: An exploratory analysis of agency practices. Int J Technol Assess Health Care. 2015; 31:314–323. doi:10.1017/S0266462315000549.Google Scholar
25. Hernandez-Villafuerte, K, Li, R, Hofman, KJ. Bibliometric trends of health economic evaluation in Sub-Saharan Africa. Global Health. 2016;12:50. doi:10.1186/s12992-016-0188-2.Google Scholar
26. Chalkidou, K, Li, R, Culyer, A, et al. Health technology assessment: Global advocacy and local realities. Int J Health Policy Manag. 2017;6:233–236.Google Scholar
27. Resources for HTA - HTAi and INAHTA's White Paper to WHO. http://www.inahta.org/hta-tools-resources/ (accessed August 4, 2017).Google Scholar