Investigating Effective Factors In Out-Of-Pocket Health Payment And Its Catastrophic Expenditure Among Households With Elderly People In Iran: An Application Of Heckman Model To Control Sample Selection


Introduction: Universal health coverage is a critical goal for low- and middle-income countries, with
equitable access to healthcare services being essential to achieving this objective. With the elderly
population requiring greater healthcare services, it is crucial to plan for their healthcare needs. This study
aims to evaluate the determinants of out-of-pocket payment (OOP) and catastrophic healthcare expenditure
among households with elderly individuals in Iran.
Methods: This study analyzed the 2018 Household Income-Expenditure Survey in Iran to examine the
socio-economic factors affecting OOP (per purchasing power parity International Doller – PPP. Int $) and
catastrophic healthcare expenditure in households with elderly members. Using survey probit regression
model with Heckman selection, the study identified determinants of OOP and catastrophic healthcare
expenditures. A survey probit regression model with Heckman selection has been applied to identify the
determinants of out-of-pocket (OOP) and catastrophic healthcare expenditures. The approach allowed for
the examination of variables that may have impacted the likelihood of incurring OOP and catastrophic
healthcare expenditures, while accounting for potential selection bias.
Results: Rural households (with difference 60.78 PPP. Int$) and non-owning homes (with difference 98.83
PPP.Int$) had higher OOP than their urban and owning counterparts, respectively. Larger households also
had higher OOP, with those with five or more members having the highest. High-income households also
had higher OOP. Additionally, smaller households had a lower chance of facing catastrophic healthcare
expenses. Lastly, the Mills ratio was negative.
Conclusion: Our study reveals insufficient observed out-of-pocket (OOP) payments for healthcare in
Iran to cover the "needed" OOP, indicating a possible financial burden on households. This highlights the
need to address inequalities in healthcare access and expenditure for households with elderly individuals,
particularly in rural areas and larger households. Policymakers should implement targeted interventions to
reduce OOP for these vulnerable groups. Future research should include socio-economic factors that affect
access to healthcare services

1. Navarro V. Assessment of the world health report 2000. The Lancet. 2000;356(9241):1598-601.
2. Zeng Y, Wan Y, Yuan Z, Fang Y. Healthcare-seeking behavior among Chinese older adults: patterns and predictive factors. International Journal of Environmental Research and Public Health. 2021;18(6):2969.
3. Albanese E, Liu Z, Acosta D, Guerra M, Huang Y, Jacob K, et al. Equity in the delivery of community healthcare to older people: findings from 10/66 Dementia Research Group cross-sectional surveys in Latin America, China, India and Nigeria. BMC Health Services Research. 2011;11(1):1-11.
4. Brinda EM, Kowal P, Attermann J, Enemark U. Health service use, out-of-pocket payments and catastrophic health expenditure among older people in India: The WHO Study on global AGEing and adult health (SAGE). Journal of epidemiology and community health. 2015;69(5):489-94.
5. Xu K, Evans DB, Carrin G, Aguilar-Rivera AM, Musgrove P, Evans T. Protecting households from catastrophic health spending. Health affairs. 2007;26(4):972-83.
6. Organization WH. The world health report: health systems financing: the path to universal coverage: executive summary. World Health Organization; 2010.
7. Van Doorslaer E, O'Donnell O, Rannan‐Eliya RP, Somanathan A, Adhikari SR, Garg CC, et al. Catastrophic payments for health care in Asia. Health economics. 2007;16(11):1159-84.
8. Kawabata K, Xu K, Carrin G. Preventing impoverishment through protection against catastrophic health expenditure. SciELO Public Health; 2002. p. 612-.
9. Shahraki M, Ghaderi S. The effect of socioeconomic factors on household health expenditures: Heckman two-step method. Payavard Salamat. 2019;13(2):160-71.
10. Van Minh H, Phuong NTK, Saksena P, James CD, Xu K. Financial burden of household out-of pocket health expenditure in Viet Nam: findings from the National Living Standard Survey 2002–2010. Social science & medicine. 2013;96:258-63.
11. Galimard J-E, Chevret S, Curis E, Resche-Rigon M. Heckman imputation models for binary or continuous MNAR outcomes and MAR predictors. BMC medical research methodology. 2018;18(1):1-13.
12. Hogan DR, Salomon JA, Canning D, Hammitt JK, Zaslavsky AM, Bärnighausen T. National HIV prevalence estimates for sub-Saharan Africa: controlling selection bias with Heckman-type selection models. Sexually transmitted infections. 2012;88(Suppl 2):i17-i23.
IssueVol 8 No 4 (2022) QRcode
Out-of-pocket payment Heckman Model Bias sample selection Catastrophic health expenditure Elderly individuals

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
Aliakbar H, Parsaeian M, Ahmadnezhad E, Tajvar M, Yaseri M. Investigating Effective Factors In Out-Of-Pocket Health Payment And Its Catastrophic Expenditure Among Households With Elderly People In Iran: An Application Of Heckman Model To Control Sample Selection. JBE. 2023;8(4):356-368.