Top

Applied Health Economics and Health Policy

Published in:

01-09-2006 | Original Research Article

Patients’ Preferences for Healthcare System Reforms in Hungary

A Conjoint Analysis

Authors: Baktygul Akkazieva, Laszlo Gulacsi, Agnes Brandtmuller, Márta Péntek, John F. P. Bridges

Published in: Applied Health Economics and Health Policy | Issue 3/2006

Abstract

Objectives: To illustrate how conjoint analysis can be used to identify patient preferences for healthcare policies, and to measure preferences for healthcare reforms in Hungary.

Data source/study setting: Data was collected via a mail-based survey and a direct survey administered in a rheumatology out-patient centre in Flór Ferenc County Hospital, Budapest, Hungary (n = 86).

Study design: We designed and administered a conjoint analysis to the study population. Attributes and attribute levels were developed on the basis of key informant interviews and a literature review. Additional demographic, occupation and healthcare utilisation data were also collected using surveys. A mixed effects linear probability model was estimated holding respondent characteristics constant and correcting for clustering.

Data collection: Conjoint analysis questionnaires were administered by a physician to 50 consecutive rheumatology patients in a clinic and an additional 36 were mailed by post.

Principal findings: The response rate for the physician-administered survey was 98% (but 18% of these were excluded for inconsistent preferences) and 53% for the mail survey, leaving a final sample of 59. Regression results (R² = 56.8%) indicated that patients preferred a health system that was not cost constrained (p = 0.003), was based on solidarity (p < 0.001) and where patients were empowered (p = 0.024). Further, they would choose a system with no choice of provider to avoid co-payments (p = 0.005).

Conclusions: This study demonstrates that patients have clear preferences for healthcare system policy. In order to develop evidence-based healthcare policy and to empower patients in the healthcare system, methods such as conjoint analysis offer a simple yet theoretically grounded basis for policy making.

Available only for authorised users

Sachs JD. Macroeconomics and health: investing in health for economic development. Report of the Commission on Macroeconomics and Health. Geneva: World Health Organization (WHO), 2001

Docteur E, Oxley H. Health-care systems: lessons from the reform experience. Economic Department Working Paper no.: 374. OECD Health Working Papers Delsa/elsa/WD/ HEA(2003)9. Paris: Organization for Economic Co-operation and Development (OECD), 2003

Palmer G. Evidence-based health policy-making, hospital funding and health insurance. Med J Aust 2000; 172(3): 130–3PubMed

Bridges J. Reconsidering the role of private health funds in Australia: a dynamic model. Appl Health Econ Health Policy 2003; 2(2): 109–17PubMed

Ham C. Priority setting in health care: learning from international experience. Health Policy 1997; 42: 49–66PubMedCrossRef

Farrar S, Ryan M, Ross D, et al. Using discrete choice modelling in priority setting: an application to clinical service developments. Soc Sci Med 2000; 50: 63–75PubMedCrossRef

Hanney S, Gonzalez-Block M, Buxton M, et al. Utilisation of health research in policy-making: concepts, examples, and methods of assessment. Health Economics Research Group Research report no. 28. Uxbridge: Brunei University, 2002

Fulop N, Allen P, Clark A, et al. From health technology assessment to research on the organization and delivery of health services: addressing the balance. Health Policy 2003; 63(2): 155–65

Ryan M, McIntosh E, Shackley PH. Using conjoint analysis to assess consumer preferences in primary care: an application to the patient health card. Health Expect 1998; 1: 117–29PubMedCrossRef

10.

Hutton J, Engqvist L. Making publicly funded health services more responsive. Eurohealth 2003; 9(3): 1–6

11.

Thomson S, Dixon A. Choices in health care: the European experience. EuroObserver 2004; 6(4): 1–4

12.

Litva A, Coast J, Donovan J, et al. The public is too subjective: public involvement at different levels of health-care decision making. Soc Sci Med 2002; 54(12): 1825–37PubMedCrossRef

13.

Ryan M. Discrete choice experiments in health care. BMJ 2004; 328: 360–1PubMedCrossRef

14.

Saltman R, Figueras J, Sakellarides C. Critical challenges for health care reform in Europe. Buckingham: Open University Press, 1998

15.

Bridges J. What can economics add to health technology assessment? Please not just another cost-effectiveness analysis! Expert Rev Pharmacoeconomics Outcomes Res 2006; 26(1): 19–24CrossRef

16.

McKee M, Rechel B, Schwalbe N. The European Union, South Eastern Europe and the wider European neighborhood. Eurohealth 2004; 10(3–4): 7–10

17.

Gulácsi L, Boncz I, Kovács A. The impacts of the EU enlargement on the Hungarian health care system. Tijdschrift voor Gezondheidswetenschappen 2004; 82(5): 281–4

18.

Orosz E, Burns A. The healthcare system in Hungary. Economics Department working paper no.: 241. Paris: Organization for Economic Co-operation and Development (OECD), 2000CrossRef

19.

Boncz I, Nagy J, Sebestyen A, et al. Discrete choice experience in health economics. Eur J Health Econ 2004; 5: 252–8PubMedCrossRef

20.

Gaal P. Health care systems in transition: Hungary. Copenhagen: World Health Organization, Regional Office for Europe on behalf of the European Observatory on Health Systems and Policies, 2004

21.

Birch S, Donaldson C. Valuing benefits and costs of health care programmes: where’s the ‘extra’ in extra welfarism. Soc Sci Med 2003; 15: 1121–33CrossRef

22.

Mooney G. What else do we want from our health services? Soc Sci Med 1994; 39(2): 151–4PubMedCrossRef

23.

Bridges J. Stated preference methods in health care evaluation: an emerging methodological paradigm in health economics. Appl Health Econ Health Policy 2003; 2(4): 213–24PubMed

24.

Bridges J. Future challenges for the economic evaluation of healthcare: patients preferences, risk attitudes and beyond. Pharmacoeconomics 2005; 23(4): 317–27PubMedCrossRef

25.

Ryan M. Using conjoint analysis to take account of patient preferences and go beyond health outcomes: an application to in vitro fertilization. Soc Sci Med 1999; 48: 535–46PubMedCrossRef

26.

Ryan M. A role for conjoint analysis in technology assessment in health care? Int J Technol Assess Health Care 1999; 15(3): 443–57PubMed

27.

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

28.

Louviere J, Hensher D, Swait J. Stated choice methods: analysis and application. Cambridge, UK: Cambridge University Press, 2000CrossRef

29.

Ryan M, Scott D, Reeves C, et al. Eliciting public preferences for healthcare: a systematic review of techniques. Health Technology Assessment 2001; 5(5): 1–186PubMed

30.

Ryan M, McIntosh E, Shackley PH. Methodological issues in the application of conjoint analysis in health care. Health Econ 1998; 7: 373–8PubMedCrossRef

31.

Ratcliffe I, van Haselen R, Buxton M, et al. Assessing patients ‘preferences for characteristics associated with homeopathic and conventional treatment of asthma: a conjoint analysis study. Thorax 2002; 57: 503–8PubMedCrossRef

32.

Ross M, Avery A, Foss A. Views of older people on cataract surgery options: an assessment of preferences by conjoint analysis. Qual Saf Health Care 2003; 12: 13–7PubMedCrossRef

33.

Phillips K, Johnson F, Maddala T. Measuring preference for health care interventions using CA: an application to HIV testing. Health Serv Res 2002; 37(6): 1681–705PubMedCrossRef

34.

Ubach C, Scott A, Awramenko M, et al. What do hospital consultants’ value about their jobs? A discrete choice experiment. BMJ 2003; 326: 1432–8PubMedCrossRef

35.

Ryan M, Hughes J. Using conjoint analysis to assess women’s preferences for miscarriage management. Health Econ 1997; 6: 261–73PubMedCrossRef

36.

Phillips K, Johnson F, Maddala T. Measuring what people value: a comparison of ‘attitude’ and ‘preference’ surveys. Health Serv Res 2002; 37(6): 1659–79PubMedCrossRef

37.

Gates R, McDaniel C, Braunsberger K. Modelling consumer health plan choice behaviour to improve customer value and health plan market share. J Bus Res 2000; 48: 247–57CrossRef

38.

Ryan M, Farrar SH. Using conjoint analysis to elicit preferences for health care. BMJ 2000; 320: 1530–3PubMedCrossRef

39.

Coast J. The appropriate use of qualitative methods in health economics. Health Econ 1999; 8: 345–53PubMedCrossRef

40.

Kutzin J. Toward universal health care coverage: a goal oriented framework for policy analysis. Washington, DC: The World Bank, 2000

41.

Mossialos E, Dixon A, Figueras J, et al. Funding health care: options for Europe. European Observatory on Health Care Systems Series. Buckingham: Open University Press, 2002

42.

Wagstaff A, van Doorslaer E, van der Burg H, et al. Equity in the finance of health care; some further international comparison. J Health Econ 1999; 18(3): 263–90PubMedCrossRef

43.

Donabedian A. Institutional and professional responsibility in quality assurance. Qual Assur Health Care 1989; 1(1): 3–11PubMedCrossRef

44.

Gulacsi L. Hungarian health care in transition; studies on the improvement of the effectiveness of health care in Hungary by implementing quality assurance [PhD dissertation]. Amsterdam: Academic Medical Centre, University of Amsterdam, 2001

45.

Kerssens J, Groenewegen P, Sixma H, et al. Comparison of patient evaluation of health care quality in relation to WHO measures of achievement in 12 European countries. Bull World Health Organ 2004 Feb; 82(2): 106–14PubMed

46.

Gakidou E, Murray C, Frenk J. Measuring preferences on health system performance assessment. GPE Discussion Paper no.: 20. Geneva: World Health Organization, 2000

47.

Orme B. Sample size issues for conjoint analysis. Sawtooth Software Series. Sequim (WA): Sawtooth Software Inc., 1998

48.

Huber P. The behaviour of maximum likelihood estimates under non-standard conditions. Proceedings of the Fifth Berkeley Symposium in Mathematical, Statistics and Probability. Berkeley (CA): University of California Press, 1967; 1: 221–33

49.

White H. A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 1980; 4(4): 817–38CrossRef

50.

Scott A. Identifying and analysing dominant preferences in discrete choice experiments: an application in health care. J Econ Psychol 2002; 23: 383–98CrossRef

51.

Bryan S, Dolan P. Discrete choice experiments in health economics. Eur J Health Econ 2004; 5: 199–202PubMedCrossRef

52.

Porter M, Macintyre S. What is, must be best: a research note on conservative or deferential responses to antenatal care provision. Soc Sci Med 1984; 19(11): 1197–200PubMedCrossRef

53.

Salkeld G, Ryan M, Short L. The veil of experience: do consumers prefer what they know best? Health Econ 2000; 9: 267–70PubMedCrossRef

54.

Vogt F, Schwappach D, Bridges J. Accounting for tastes: a German perspective on the inclusion of patient preferences in health care. Pharmacoeconomics 2006; 24(5): 419–23PubMedCrossRef

Title: Patients’ Preferences for Healthcare System Reforms in Hungary
A Conjoint Analysis
Authors: Baktygul Akkazieva
Laszlo Gulacsi
Agnes Brandtmuller
Márta Péntek
John F. P. Bridges
Publication date: 01-09-2006
Publisher: Springer International Publishing
Published in: Applied Health Economics and Health Policy / Issue 3/2006
Print ISSN: 1175-5652
Electronic ISSN: 1179-1896
DOI: https://doi.org/10.2165/00148365-200605030-00005

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Patients’ Preferences for Healthcare System Reforms in Hungary

A Conjoint Analysis

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 3/2006

Comparing Patient Access to Pharmaceuticals in the UK and US

Community-Based Youth Tobacco Control Interventions

Modelling the Costs and Outcomes of Changing Rates of Screening for Alcohol Misuse by GPS in the Australian Context

To Retain or Remove User Fees?