Health insurance in Myanmar: Knowledge, perceptions, and preferences of Social Security Scheme members and general adult population

C.-Y. Myint*, M. Pavlova, W. Groot

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Our study explores the knowledge, perceptions, willingness to pay, and preferences of potential health insurance beneficiaries about health insurance in Myanmar. Methods: Cross-sectional survey data were collected among two samples: the general population and Social Security Scheme (SSS) member. Mann-Whitney U test and independent sample t test were applied to compare the two samples. The data on willingness to pay for health insurance were analyzed using regression analysis. Results: Low level of knowledge and weak positive perception are found in both samples. More than 90% of the SSS sample and 75% of the general sample are willing to pay health insurance premiums. The largest shares of both samples are willing to pay for monthly premiums between 2000 and 4000 MMK (1.8-3.6 USD). Health status, age, gender, income, and trust are significantly associated with willingness to pay for health insurance among general sample while occupation, civil status, income, and positive perception on prepayment principle are found among SSS sample. Conclusions: The government of Myanmar should be aware of the preferences of beneficiaries to pay a relatively low level of monthly health insurance premiums without co‐payment.
Original languageEnglish
Pages (from-to)346-369
Number of pages24
JournalInternational Journal of Health Planning and Management
Issue number1
Publication statusPublished - 2019

JEL classifications

  • i13 - Health Insurance, Public and Private


  • ability to pay
  • health insurance
  • social security
  • willingness to pay
  • adult
  • article
  • case report
  • clinical article
  • female
  • gender
  • government
  • health status
  • human
  • male
  • Myanmar
  • occupation
  • perception
  • population
  • rank sum test
  • regression analysis
  • trust

Cite this