Willingness-To-Pay for Health Insurance: Protocol for a Comparative Study Between Formal and Informal Health-Workers

Abstract

INTRODUCTION People in low- to middle-income countries (LMICs), such as Bangladesh, have less access to healthcare than those in wealthier nations with less than 1% of the population having access to social health protection, which is mostly limited to those who work in the formal sector (14.9% of all jobs). This comparative study aims to use the contingent valuation method (CVM) to determine the factors affection and compare the mean willingness-to-pay (WTP) for community-based health insurance (CBHI) between formal and informal health workers. METHODS AND ANALYSIS This comparative study will be conducted among 250 doctors who will be selected by a convenience sampling technique from various formal and informal workstations in Dhaka City. Of the 250 participants, 125 will be from each group. To collect data, a semi-structured questionnaire will be used via face-to-face interviews. Data will be processed and analyzed using R (v4.3.0) and RStudio (v2023.03.1). WTP for CBHI will be estimated using the “DCchoice” package. The primary outcome is to estimate the proportion and mean WTP across the groups and compare it using double bound dichotomous choice (DBDC) method. Secondary outcomes include identifying the socio-demographic, job-related and healthcare seeking-related factors that influence the WTP. ETHICS AND DISSEMINATION Ethics approval has been obtained from Institutional Review Board (IRB) of the National Institute of Preventive and Social Medicine (NIPSOM). Informed consent will be taken from each participant before data collection. The results of the study will be published in scientific, peer-reviewed journals. STRENGTHS AND LIMITATIONS OF THIS STUDY – The contingent valuation method is a well-established method of eliciting WTP for health insurance. – The current study will be among the first of its nature as it will focus on formal and informal healthcare workers. – Starting point bias may affect the result as this type of bias comes with the Double bounded dichotomous choice (DBDC) method used in this study.