AUTHOR=Zakaria Muhammad , Islam Muhammad Aminul , Islam Md Khadimul , Begum Aklima , Poly Nahida Akter , Cheng Feng , Xu Junfang 

TITLE=Determinants of Bangladeshi patients' decision-making process and satisfaction toward medical tourism in India

JOURNAL=Frontiers in Public Health

VOLUME=11

YEAR=2023

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2023.1137929

DOI=10.3389/fpubh.2023.1137929

ISSN=2296-2565

ABSTRACT=<sec><title>Objectives</title><p>The aims are to explore the factors influencing Bangladeshi patients' decision-making process and their satisfaction level toward medical tourism in India.</p></sec><sec><title>Methods</title><p>The study used a quantitative research approach with a cross-sectional survey. Data were collected from the patients or their relatives (<italic>N</italic> = 388) who would have decided to travel to India for medical and treatment purposes at the Chittagong Indian visa center (IVAC). Data were collected using a structured, pre-tested, and facilitator-administered questionnaire, which mainly included the social demographic characteristics, health status, medical tourism information and medical tourism index. Hierarchical regression analysis was performed to explore the factors influencing their satisfaction level toward medical tourism in India.</p></sec><sec><title>Results</title><p>More than three-fourths of the participants had visited India for self-treatment. Of the participants, 14% were cardiology patients, and 13% suffered from cancer. The relatives were the key source of information regarding medical tourism for more than one-fourth of the respondents. India's availability of well-experienced doctors, hospital/medical facilities with high standards, well-trained doctors, reputable doctors, and quality treatments and medical materials were top-ranked items. Regression results depict that facility and services appeared as the strongest factor (β = 0.24, <italic>t</italic> = 4.71, <italic>p</italic> &lt; 0.001) followed by tourism destination factor (β = 0.16, <italic>t</italic> = 3.11, <italic>p</italic> = 0.002), medical tourism costs factor (β = 0.16, <italic>t</italic> = 3.24, <italic>p</italic> = 0.001) and country environment factor (β = 0.15, <italic>t</italic> = 2.69, <italic>p</italic> = 0.007).</p></sec><sec><title>Conclusions</title><p>We found that the factor related to facility and services is one of the strongest predictors in our models. Therefore, home countries must strengthen the health care providers' advanced professional training, including service attitudes. Moreover, it is important to lessen the language barrier, reduce the airfare for medical tourists, and make the treatment cost more affordable for patients.</p></sec>