Hostname: page-component-7c8c6479df-hgkh8 Total loading time: 0 Render date: 2024-03-29T08:24:22.806Z Has data issue: false hasContentIssue false

IMPLEMENTATION OF EUNETHTA CORE MODEL® IN LOMBARDIA: THE VTS FRAMEWORK

Published online by Cambridge University Press:  22 January 2014

Giovanni Radaelli
Affiliation:
Politecnico di Milano
Emanuele Lettieri
Affiliation:
Politecnico di Milano
Cristina Masella
Affiliation:
Politecnico di Milano
Luca Merlino
Affiliation:
Regione Lombardia
Alberto Strada
Affiliation:
Regione Lombardia
Michele Tringali
Affiliation:
Regione Lombardia

Abstract

Objectives: This study describes the health technology assessment (HTA) framework introduced by Regione Lombardia to regulate the introduction of new technologies. The study outlines the process and dimensions adopted to prioritize, assess and appraise the requests of new technologies.

Methods: The HTA framework incorporates and adapts elements from the EUnetHTA Core Model and the EVIDEM framework. It includes dimensions, topics, and issues provided by EUnetHTA Core Model to collect data and process the assessment. Decision making is instead supported by the criteria and Multi-Criteria Decision Analysis technique from the EVIDEM consortium.

Results: The HTA framework moves along three process stages: (i) prioritization of requests, (ii) assessment of prioritized technology, (iii) appraisal of technology in support of decision making. Requests received by Regione Lombardia are first prioritized according to their relevance along eight dimensions (e.g., costs, efficiency and efficacy, organizational impact, safety). Evidence about the impacts of the prioritized technologies is then collected following the issues and topics provided by EUnetHTA Core Model. Finally, the Multi-Criteria Decision Analysis technique is used to appraise the novel technology and support Regione Lombardia decision making.

Conclusions: The VTS (Valutazione delle Tecnologie Sanitarie) framework has been successfully implemented at the end of 2011. From its inception, twenty-six technologies have been processed.

Type
Policies
Copyright
Copyright © Cambridge University Press 2014 

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. EUnetHTA. HTA Core Model. 2011. https://meka.thl.fi/htacore/ViewHandbook.aspx (accessed January 4, 2014).Google Scholar
2. Lampe, K, Makela, M, Garrido, MV, et al. The HTA Core Model: A novel method for producing and reporting health technology assessments. Int J Technol Assess Health Care. 2009;25:920.Google Scholar
3. Chernew, ME, Sabik, L, Chandra, A, Newhouse, JP. Ensuring the fiscal sustainability of health care reform. N Engl J Med. 2009;362:13.Google Scholar
4. Fisher, ES, Bynum, JP, Skinner, JS. Slowing the growth of health care costs – Lessons from regional variation. N Engl J Med. 2009;360:849852.CrossRefGoogle ScholarPubMed
5. Chandra, A, Skineer, JS. Technology growth and expenditure growth in health care. National Bureau of Economic Research. 2011. http://www.nber.org/papers/w16953 (accessed January 4,2014).Google Scholar
6. Busse, R, Orvain, J, Velasco, M, et al. 2002. Best practice in undertaking and reporting health technology assessments: Working Group 4 report. Int J Technol Assess Health Care. 2002;18:361422.Google Scholar
7. Goetghebeur, MM, Wagner, M, Khoury, H, et al. Evidence and Value: Impact on decision making – the EVIDEM framework and potential applications. BMC Health Serv Res. 2008;8:270285.CrossRefGoogle ScholarPubMed
8. France, G, Taroni, F. The evolution of health-policy making in Italy. J Health Polit Policy Law. 2005;30:169188.Google Scholar
9. Favaretti, C, Cicchetti, A, Guarrera, G, Marchetti, M, Ricciardi, W. Health technology assessment in Italy. Int J Technol Assess Health Care. 2009;25:127133.Google Scholar
10. Donaldson, C, Currie, G, Mitton, C. Cost effectiveness analysis in health care: Contradictions. BMJ. 2002;325:891894.Google Scholar
11. Birch, S, Gafni, A. Information Created to Evade Reality (ICER), Pharmacoeconomics. 2006;24:11211131.CrossRefGoogle ScholarPubMed
12. Brouwer, W, van Exel, J, Baker, R, Donaldson, C. The new myth: The social value of the QALY. Pharmacoeconomics. 2008;26:14.CrossRefGoogle ScholarPubMed
13. EVIDEM. Decision Criteria. Conceptual Backgrounds, definitions, design & instructions, v2.1. 2011. https://www.evidem.org/components-decision.php (accessed January 4, 2014).Google Scholar
14. Goetghebeur, MM, Wagner, M, Khoury, H, et al. Evidence and value: Impact on DEcisionMaking–the EVIDEM framework and potential applications. BMC Health serv res. 2008;8:270.Google Scholar
15. Goetghebeur, MM, Wagner, M, Khoury, H, et al. Combining multicriteria decision analysis, ethics and health technology assessment: Applying the EVIDEM decisionmaking framework to growth hormone for Turner syndrome patients. Cost Eff Resour Alloc. 2010;8:4.Google Scholar
16. Lettieri, E, Masella, C, Nocco, U. Budgeting and health technology assessment: First evidence obtained from proposal forms used to submit the adoption of new technology. Int J Technol Assess Health Care. 2008;24:502510.Google Scholar