title: Patients' preferences for healthcare system reforms in Hungary: a conjoint analysis.
abstract: OBJECTIVE
  To illustrate how conjoint analysis can be used to identify patient preferences for healthcare policies, and to measure preferences for healthcare reforms in Hungary.
  
  
  METHODS
  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).
  
  
  METHODS
  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.
  
  
  METHODS
  Conjoint analysis questionnaires were administered by a physician to 50 consecutive rheumatology patients in a clinic and an additional 36 were mailed by post.
  
  
  RESULTS
  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.
authors.affiliation: Department of Tropical Hygiene and Public Health, University of Heidelberg, Heidelberg, Germany.
authors.forename: Baktygul
authors.initials: B
authors.lastname: Akkazieva
authors.forename: Laszlo
authors.initials: L
authors.lastname: Gulacsi
authors.forename: Agnes
authors.initials: A
authors.lastname: Brandtmuller
authors.forename: Márta
authors.initials: M
authors.lastname: Péntek
authors.forename: John F P
authors.initials: JF
authors.lastname: Bridges
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003669:Deductibles and Coinsurance; D005062:European Union; D005260:Female; D017048:Health Care Costs; D018166:Health Care Reform / Q000191:economics / Q000379:methods*; D019538:Health Care Surveys / Q000379:methods; D006301:Health Services Needs and Demand / Q000191:economics; D006766:Hospitals, County; D006801:Humans; D006814:Hungary; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D010044:Outpatient Clinics, Hospital / Q000706:statistics & numerical data; D010358:Patient Participation / Q000191:economics; D017060:Patient Satisfaction / Q000191:economics / Q000706:statistics & numerical data*; D011787:Quality of Health Care / Q000191:economics; D012044:Regression Analysis; D012219:Rheumatology; D011795:Surveys and Questionnaires