Skip to main content

Advertisement

SpringerLink
Log in

Comparative analysis of decision maker preferences for equity/efficiency attributes in reimbursement decisions in three European countries

  • Original Paper
  • Published:
The European Journal of Health Economics Aims and scope Submit manuscript

Abstract

Background

In addition to cost-effectiveness, national guidelines often include other factors in reimbursement decisions. However, weights attached to these are rarely quantified, thus decisions can depend strongly on decision-maker preferences.

Objective

To explore the preferences of policymakers and healthcare professionals involved in the decision-making process for different efficiency and equity attributes of interventions and to analyse cross-country differences.

Method

Discrete choice experiments (DCEs) were carried out in Austria, Hungary, and Norway with policymakers and other professionals working in the health industry (N = 153 respondents). Interventions were described in terms of different efficiency and equity attributes (severity of disease, target age of the population and willingness to subsidise others, potential number of beneficiaries, individual health benefit, and cost-effectiveness). Parameter estimates from the DCE were used to calculate the probability of choosing a healthcare intervention with different characteristics, and to rank different equity and efficiency attributes according to their importance.

Results

In all three countries, cost-effectiveness, individual health benefit and severity of the disease were significant and equally important determinants of decisions. All countries show preferences for interventions targeting young and middle aged populations compared to those targeting populations over 60. However, decision-makers in Austria and Hungary show preferences more oriented to efficiency than equity, while those in Norway show equal preferences for equity and efficiency attributes.

Conclusion

We find that factors other than cost-effectiveness seem to play an equally important role in decision-making. We also find evidence of cross-country differences in the weight of efficiency and equity attributes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. The Main Association of Austrian Social Security Institutions) based on the recommendations of the Pharmaceutical Evaluation Board classify the drugs into three different reimbursement categories: red, green and yellow boxes.

  2. (1) Priorities of the health care system, (2) severity of the disease, (3) equity (size of the target population, accessibility), (4) cost-effectiveness and quality of life (ICER, health gain per patient), (5) budget impact, and (6) opinions from Hungary and abroad.

  3. DALY was chosen to define the cost-effectiveness threshold in this study, since the same standardised questionnaire was used previously in lower and middle income countries such as Brazil, Cuba, Nepal, and Uganda [24], where cost-effectiveness thresholds are mostly set by DALYs [32].

  4. Norwegian and Austrian data were presented separately in previous studies [10, 12]. Norwegian data was also used in Mirelman et al. [24] in a cross-country comparison of Brazil, Cuba, Nepal Norway and Uganda.

  5. e.g. National Health Insurance Fund, Ministry of Human Resources, National Institute for Quality and Organisational Development in Healthcare and Medicines.

  6. Purely equitable and purely efficient interventions are those where all equity attributes are set to 1 (with all efficiency attributes to 0) and those where all efficiency attributes are set to 1 (with all equity attributes to 0), respectively.

  7. Results are available from the authors upon request.

  8. Results are available from the authors upon request.

References

  1. Dakin, H., Devlin, N., Feng, Y., Rice, N., O’Neill, P., Parkin, D.: The influence of cost-effectiveness and other factors on nice decisions. Health Econ. (2014). doi: 10.1002/hec.3086

  2. Sabik, L.M., Lie, R.K.: Priority setting in health care: lessons from the experiences of eight countries. Int. J. Equity Health 7, 4 (2008)

    Article  PubMed  PubMed Central  Google Scholar 

  3. Gulacsi, L., Rotar, A.M., Niewada, M., Loblova, O., Rencz, F., Petrova, G., Boncz, I., Klazinga, N.S.: Health technology assessment in Poland, the Czech Republic, Hungary, Romania and Bulgaria. Eur. J. Health Econ. 15(Suppl 1), S13–S25 (2014)

    Article  PubMed  Google Scholar 

  4. Norheim, O.F., Baltussen, R., Johri, M., Chisholm, D., Nord, E., Brock, D., Carlsson, P., Cookson, R., Daniels, N., Danis, M., Fleurbaey, M., Johansson, K.A., Kapiriri, L., Littlejohns, P., Mbeeli, T., Rao, K.D., Edejer, T.T., Wikler, D.: Guidance on priority setting in health care (GPS-Health): the inclusion of equity criteria not captured by cost-effectiveness analysis. Cost Eff. Resour. Alloc. 12, 18 (2014)

    Article  PubMed  PubMed Central  Google Scholar 

  5. Rawlins, M., Barnett, D., Stevens, A.: Pharmacoeconomics: NICE’s approach to decision-making. Br. J. Clin. Pharmacol. 70(3), 346–349 (2010)

    Article  PubMed  PubMed Central  Google Scholar 

  6. Green, C., Gerard, K.: Exploring the social value of health-care interventions: a stated preference discrete choice experiment. Health Econ. 18(8), 951–976 (2009)

    Article  PubMed  Google Scholar 

  7. Baltussen, R., Niessen, L.: Priority setting of health interventions: the need for multi-criteria decision analysis. Cost Eff. Resour. Alloc. 4, 14 (2006)

    Article  PubMed  PubMed Central  Google Scholar 

  8. Baltussen, R., Stolk, E., Chisholm, D., Aikins, M.: Towards a multi-criteria approach for priority setting: an application to Ghana. Health Econ. 15(7), 689–696 (2006)

    Article  PubMed  Google Scholar 

  9. Marsh, K., Lanitis, T., Neasham, D., Orfanos, P., Caro, J.: Assessing the value of healthcare interventions using multi-criteria decision analysis: a review of the literature. Pharmacoeconomics 32(4), 345–365 (2014)

    Article  PubMed  Google Scholar 

  10. Defechereux, T., Paolucci, F., Mirelman, A., Youngkong, S., Botten, G., Hagen, T.P., Niessen, L.W.: Health care priority setting in Norway a multicriteria decision analysis. BMC Health Serv. Res. 12, 39 (2012)

    Article  PubMed  PubMed Central  Google Scholar 

  11. Koopmanschap, M.A., Stolk, E.A., Koolman, X.: Dear policy maker: have you made up your mind? A discrete choice experiment among policy makers and other health professionals. Int. J. Technol. Assess Health Care 26(2), 198–204 (2010)

    Article  PubMed  Google Scholar 

  12. Mentzakis, E., Paolucci, F., Rubicko, G.: Priority setting in the Austrian healthcare system: results from a discrete choice experiment and implications for mental health. J. Ment. Health Policy Econ. 17(2), 61–73 (2014)

    PubMed  Google Scholar 

  13. Watson, V., Carnon, A., Ryan, M., Cox, D.: Involving the public in priority setting: a case study using discrete choice experiments. J. Public Health (Oxf) 34(2), 253–260 (2012)

    Article  Google Scholar 

  14. Ratcliffe, J., Bekker, H.L., Dolan, P., Edlin, R.: Examining the attitudes and preferences of health care decision-makers in relation to access, equity and cost-effectiveness: a discrete choice experiment. Health Policy 90(1), 45–57 (2008)

    Article  PubMed  Google Scholar 

  15. Lim, M.K., Bae, E.Y.: Eliciting stated preferences for drugs reimbursement decision criteria in South Korea. Korean J. Health Policy Adm. 19(4), 98–120 (2009)

    Article  Google Scholar 

  16. Buchholz, P.: ISPOR Global Health Systems Road Map. http://www.ispor.org/htaroadmaps/Austria.asp (2009). Accessed 15 October 2014

  17. Räpple, T.: Pricing and Reimbursement Handbook. Baker & McKenzie. http://www.bakermckenzie.com/files/Uploads/Documents/Germany/LifeSciences/EuropeanPricingReimbursement.pdf (2011) Accessed 15 October 2014

  18. Endrei, D., Molics, B., Agoston, I.: Multicriteria decision analysis in the reimbursement of new medical technologies: real-world experiences from Hungary. Value Health 17(4), 487–489 (2014)

    Article  PubMed  Google Scholar 

  19. Dankó, D.: Health technology assessment in middle-income countries: recommendations for a balanced assessment system. J. Market Access Health Policy 2(23181), 1–10 (2014)

    Google Scholar 

  20. Gulacsi, L., Orlewska, E., Pentek, M.: Health economics and health technology assessment in Central and Eastern Europe: a dose of reality. Eur. J. Health Econ. 13(5), 525–531 (2012)

    Article  CAS  PubMed  Google Scholar 

  21. Ringard, A., Morland, B., Larsen, B.I.: Quality and priorities in the health services. Tidsskr. Nor. Laegeforen. 132(3), 312–314 (2012)

    Article  PubMed  Google Scholar 

  22. Ryan, M., Gerard, K.: Using discrete choice experiments to value health care programmes: current practice and future research reflections. Appl. Health Econ. Health Policy 2(1), 55–64 (2003)

    PubMed  Google Scholar 

  23. Baltussen, R., ten Asbroek, A.H., Koolman, X., Shrestha, N., Bhattarai, P., Niessen, L.W.: Priority setting using multiple criteria: should a lung health programme be implemented in Nepal? Health Policy Plan 22(3), 178–185 (2007)

    Article  CAS  PubMed  Google Scholar 

  24. Mirelman, A., Mentzakis, E., Kinter, E., Paolucci, F., Fordham, R., Ozawa, S., Ferraz, M., Baltussen, R., Niessen, L.W.: Decision-making criteria among national policymakers in five countries: a discrete choice experiment eliciting relative preferences for equity and efficiency. Value Health 15(3), 534–539 (2012)

    Article  PubMed  Google Scholar 

  25. Noorani, H.Z., Husereau, D.R., Boudreau, R., Skidmore, B.: Priority setting for health technology assessments: a systematic review of current practical approaches. Int. J. Technol. Assess Health Care 23(3), 310–315 (2007)

    Article  PubMed  Google Scholar 

  26. Youngkong, S., Kapiriri, L., Baltussen, R.: Setting priorities for health interventions in developing countries: a review of empirical studies. Trop. Med. Int. Health 14(8), 930–939 (2009)

    Article  PubMed  Google Scholar 

  27. Hensher, D.A., Rose, J.M., Greene, W.H.: Applied choice analysis: a primer. Cambridge University Press, Cambridge (2005)

    Book  Google Scholar 

  28. McFadden, D.: Conditional logit analysis of qualitative choice behavior. In: Zarembka, P. (ed.) Frontiers in econometrics. pp. 105–142. Academic, New York (1974)

  29. DeShazo, J.R., Fermo, G.: Designing choice sets for stated preference methods: the effects of complexity on choice consistency. J. Environ. Econ. Manag. 44(1), 123–143 (2002)

    Article  Google Scholar 

  30. Hensher, D., Greene, W.: The Mixed Logit model: the state of practice. Transportation 30(2), 133–176 (2003)

    Article  Google Scholar 

  31. Lancsar, E., Louviere, J., Flynn, T.: Several methods to investigate relative attribute impact in stated preference experiments. Soc. Sci. Med. 64(8), 1738–1753 (2007)

    Article  PubMed  Google Scholar 

  32. Shillcutt, S.D., Walker, D.G., Goodman, C.A., Mills, A.J.: Cost effectiveness in low- and middle-income countries: a review of the debates surrounding decision rules. Pharmacoeconomics 27(11), 903–917 (2009)

    Article  PubMed  PubMed Central  Google Scholar 

  33. Whitty, J.A., Lancsar, E., Rixon, K., Golenko, X., Ratcliffe, J.: A systematic review of stated preference studies reporting public preferences for healthcare priority setting. Patient 7(4):365–386 (2014)

  34. Whitty, J.A., Scuffham, P.A., Rundle-Thielsee, S.: Public and decision maker stated preferences for pharmaceutical subsidy decisions. Appl. Health Econ. Health Policy 9(2), 73–79 (2009)

    Article  Google Scholar 

Download references

Acknowledgments

The authors are grateful for Georg Rubiko, University of Innsbruck, Austria, Prof. Terje P. Hagen, Department of Health Management and Health Economics, University of Oslo, Norway, Dr. Márta Péntek, Department of Health Economics, Corvinus University of Budapest, Hungary, Dr. Valentin Brodszky, Department of Health Economics, Corvinus University of Budapest, Hungary for their assistance in the data collection. Petra Baji was supported by the Hungarian Scientific Research Fund OTKA (PD 112499). Manuel García-Goñi’s research was supported by the research project Evaluating Preferences for Equity and Efficiency among National/Regional Health Policy Makers” financed by the Spanish Instituto de Estudios Fiscales.

Author information

Authors and Affiliations

  1. Department of Health Economics, Corvinus University of Budapest, Fővám tér 8., Budapest, 1093, Hungary

    Petra Baji & László Gulácsi

  2. CERGE-EI, Prague, Czech Republic

    Petra Baji

  3. Departamento de Economía Aplicada II, Universidad Complutense de Madrid, Madrid, Spain

    Manuel García-Goñi

  4. Economics Department, School of Social Sciences, University of Southampton, Southampton, UK

    Emmanouil Mentzakis

  5. University of Bologna, Bologna, Italy

    Francesco Paolucci

  6. Murdoch University, Murdoch, Australia

    Francesco Paolucci

Authors
  1. Petra Baji
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manuel García-Goñi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. László Gulácsi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Emmanouil Mentzakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Francesco Paolucci
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Petra Baji.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Baji, P., García-Goñi, M., Gulácsi, L. et al. Comparative analysis of decision maker preferences for equity/efficiency attributes in reimbursement decisions in three European countries. Eur J Health Econ 17, 791–799 (2016). https://doi.org/10.1007/s10198-015-0721-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10198-015-0721-x

Keywords

JEL Classification

Search

Navigation