Health Coverage in a Migration Hub: Comparing Insurance Access Among Immigrants and Ghanaians

Health Coverage in a Migration Hub: Comparing Insurance Access Among Immigrants and Ghanaians | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Health Coverage in a Migration Hub: Comparing Insurance Access Among Immigrants and Ghanaians Alberta Teye Agudey, Delali Magaret Badasu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8866865/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract As Ghana transitioned into a key destination for international migrants, understanding the health coverage landscape for this growing population is increasingly vital; Particularly in the context of global health crises. Using an explanatory sequential mixed method design, this study investigated disparities in health insurance coverage between 116 immigrants and 116 non-migrants in Ghana. The quantitative result revealed that, only 41.4% of all the respondents were registered with a health insurance scheme in Ghana with a stark gap by migration status: 75% of immigrants had never enrolled, compared to just 7.8% of non-migrants. Among the insured, the National Health Insurance Scheme (NHIS) was the dominant provider (88.5%). Qualitative insights further explain low enrolment among immigrants, citing limited knowledge of NHIS registration procedures, reliance on self-medication, and aversion to Ghana’s paper- and card-based insurance system particularly among digitally oriented migrants accustomed to electronic health platforms. The study identifies these factors as structural and informational barriers that function as disabling conditions within Andersen’s Behavioural Model of Health Services Use. We recommend that Ghana’s National Health Insurance Authority fully transition toward a digital, user-friendly enrolment and verification system and integrate pre-arrival health insurance orientation into visa processing for prospective immigrants. Such reforms could significantly improve equitable access to care in an increasingly mobile society. Health Policy Health Coverage Health Insurance Immigrants Non-migrants Health Financing Figures Figure 1 Background Globally, international migration is reshaping health systems, particularly in low- and middle-income countries (LMICs) that are increasingly becoming destinations not just transit points or origins for migrants. In sub-Saharan Africa, Ghana has emerged as a notable hub for regional and international migration, hosting an estimated 400,000 immigrants. This is about 1.5% of its population as of the 2010 census, with numbers likely higher today (GSS, 2014; GMFA&RI, 2016). Recent analyses suggest that Ghana’s appeal as a destination for students, professionals, and entrepreneurs from West Africa, Asia, and beyond has grown steadily, especially in urban centres like Greater Accra (Kwarteng-Nantwi, 2019 ; Boafo-Arthur et al., 2017 ; Nyarko & Ephraim, 2016 ). While much attention has historically focused on Ghana as a migrant-sending country, its evolving role as a receiving nation demands urgent examination of how its health financing mechanisms operates. Particularly how the National Health Insurance Scheme (NHIS) serves the non-citizen populations. Health insurance is widely recognized as a critical tool for mitigating financial barriers to care and advancing universal health coverage (UHC) (WHO, 2000; Okoroh et al., 2018 ). Ghana’s NHIS, launched in 2003, was designed to reduce out-of-pocket expenditures and improve equitable access to health services (Witter et al., 2007 ). Despite notable achievements, challenges persist including administrative inefficiencies, reliance on paper-based systems, delayed provider reimbursements, and uneven enrollment (Jehu-Appiah et al., 2011 ; Addae-Koranche, 2013; Gajate-Garrido & Owusu, 2013 ). Crucially, existing research on NHIS has overwhelmingly focused on Ghanaian citizens. Recent national studies on insurance enrollment, equity, and health-seeking behavior such as those by Ayanore et al. ( 2019 ), Kwarteng et al. ( 2020 ), and Van Der Wielen et al. ( 2018 ) rarely disaggregate findings by migration status or consider the unique institutional positioning of non-citizens. This gap is significant: immigrants whether students, labour migrants, or expatriates often face structural and informational barriers that differ from those of native-born populations, including limited awareness of local health financing procedures, exclusion from employer-based coverage, reliance on informal care, and difficulties navigating bureaucratic processes (Lattof, 2018 ; Juárez et al., 2019 ). In Ghana, where health insurance enrollment is voluntary and heavily dependent on individual initiative, such barriers may disproportionately affect non-citizens. Lattof’s ( 2018 ) qualitative study of female migrants in Accra found that many were unaware they were eligible for NHIS or assumed it was only for Ghanaians. Similarly, Adu-Boahene and Dapaah-Afriyie ( 2017 ) noted that West African immigrants in diaspora settings often rely on transnational health strategies, including self-medication and cross-border care, which may reduce perceived need for local insurance. To understand these dynamics, this study draws on Andersen’s Behavioral Model of Health Services Use (1968, 1995), which posits that health care access is shaped by predisposing (e.g., education, culture), enabling (e.g., income, insurance, institutional support), and need-based factors. While the model has been widely applied in Ghanaian contexts (Awoke et al., 2017 ; Kuuire et al., 2016 ), it has rarely been used to examine how migration status intersects with these factors to shape insurance coverage especially when considering both formal insurance and informal affiliation-based coverage (e.g., through universities or employers). Against this backdrop, we ask: How does health insurance coverage and access to care through institutional affiliation differ between immigrants and non-migrants in urban Ghana. We also sort to understand the underlying factors explaining these disparities? Using an explanatory sequential mixed-methods design, this study compares insurance enrollment patterns among 116 immigrants and 116 non-migrants in Greater Accra and explores the lived experiences behind the statistics. By concentrating on the voices of an often-invisible population, this research contributes to more inclusive health financing policies in an era of increasing mobility. Theoretical Review Understanding disparities in health insurance coverage requires a framework that accounts for both individual agency and structural context. This study employs Andersen’s Behavioral Model of Health Services Use (Andersen, 1995 ) a widely validated and adaptable theoretical lens that explains health care access as the interplay of predisposing, enabling, and need-based factors. Predisposing factors such as age, education, migration status, and health belief systems shape an individual’s propensity to seek care. Enabling factors, including income, health insurance, social support, and institutional arrangements (e.g., workplace-based coverage), determine the practical means to access services. Need factors, whether perceived or clinically assessed, activate care-seeking behavior. Crucially, Andersen’s 1995 revision expanded the model to incorporate external environmental influences, such as health system organization and national policy making it especially suited for analyzing access in complex, pluralistic systems like Ghana’s. The model has been extensively applied in Ghanaian health research. Awoke et al. ( 2017 ) used it to show that wealth and education increase the likelihood of private facility use. While Kuuire et al. ( 2016 ) found that NHIS enrollment alone does not guarantee care-seeking among the poor highlighting gaps between formal coverage and actual access. Harvey ( 2014 ) further demonstrated that cultural and socioeconomic predisposing factors significantly influence health service utilization among Ghanaians. However, these studies focus almost exclusively on citizen populations. Migration status introduces unique dynamics that challenge standard applications of the model. Immigrants may possess strong predisposing factors (e.g., high education levels, as seen in our sample) and enabling resources (e.g., employment), yet remain uninsured due to structural barriers such as lack of information about NHIS eligibility, bureaucratic complexity, or reliance on transnational health strategies (Lattof, 2018 ; Adu-Boahene & Dapaah-Afriyie, 2017 ). These are not merely absences of enabling factors but active disabling conditions that deter enrollment despite apparent capacity. This study therefore extends Andersen’s framework by treating migration status as a cross-cutting variable that reshapes the relationship between predisposing/enabling factors and health insurance uptake. Moreover, by integrating qualitative insights with survey data, we uncover how systemic features like Ghana’s paper- and card-based insurance system function as disabling mechanisms, particularly for digitally oriented migrants accustomed to streamlined, electronic platforms. In doing so, we move beyond using the model as a predictive tool and instead leverage it to interpret the lived experience of exclusion in an emerging migrant destination. Application of the Andersen Model in Contemporary Studies The Andersen Behavioral Model has been widely applied across global health contexts to unpack disparities in health service utilization (Azfredrick 2016 ; Smith and Scheid 2014 ), with over 300 empirical studies identified in a systematic review covering 1998–2011 alone (Babitsch et al., 2012 ). In Ghana, the model has proven particularly useful in explaining patterns of health care access among diverse populations. Awoke et al. ( 2017 ) found that higher education, wealth, and age key predisposing and enabling factors significantly increased the likelihood of using private health facilities among older adults. Similarly, Kuuire et al. ( 2016 ) demonstrated that despite NHIS enrollment, poor adults in resource-limited settings were less likely to seek formal care, underscoring that insurance alone does not guarantee access when other enabling resources (e.g., transportation, trust in providers) are lacking. Harvey’s ( 2014 ) analysis of Demographic and Health Survey data further confirmed that socio-cultural predisposing factors such as religion and education shape health-seeking behavior in Ghana. Collectively, these studies validate the model’s utility in the Ghanaian context but share a critical limitation: they focus exclusively on citizen populations, treating “immigrants in Ghana” as an unexamined norm. Globally, only a handful of studies have applied Andersen’s framework to migrant populations. Dias et al. ( 2008 ) identified language barriers and legal status as key disabling conditions for migrants in Portugal, while Wassink ( 2018 ) found that return migrants in Mexico faced administrative exclusion from insurance systems. Closer to home, Lattof ( 2018 ) documented how female migrants in Accra often assumed NHIS was unavailable to non-citizens a misconception rooted in poor information dissemination and institutional invisibility. These findings suggest that migration status itself reshapes the operation of predisposing and enabling factors, introducing barriers not captured in standard applications of the model. Notably, none of these studies explicitly conceptualize structural features of health systems such as paper-based bureaucracy or lack of digital infrastructure as “disabling conditions.” This is a critical oversight in contexts like Ghana, where administrative complexity may deter even highly educated, employed migrants from enrolling. By combining quantitative data with qualitative narratives on care seeking logic, our study advances the Andersen framework beyond its traditional predictive function, using it instead as a lens to interpret how policy design can inadvertently mobile populations. Methodology This study employed an explanatory sequential mixed-methods design (Creswell & Plano Clark, 2017; Teye et al 2015 ), wherein quantitative data were collected and analysed first to identify patterns in health insurance coverage. After which qualitative interviews to explain and contextualize these findings particularly the stark disparities observed between immigrants and non-migrants were conducted. Study Setting and Sampling Data were collected between November and December 2018 in the Greater Accra Region of Ghana a major destination for international migrants, hosting an estimated 60% of the country’s foreign-born population (GSS, 2014). A total of 232 participants were recruited: 116 international migrants and 116 non-migrants (Ghanaians). Migrants were eligible if they had resided continuously in Ghana for at least six months; non-migrants were required to have remained in Ghana during the same period and were sampled from the same neighbourhoods as migrant participants to ensure contextual comparability. Purposive and snowball sampling were used to identify migrants across ten communities (Accra Central, Alajo, Legon, Weija, Osu, Tema, Tetteh Quarshie, New Aplaku, New Bortianor, and Valley View/Oyibi), while non-migrants were selected using convenience sampling within the same localities. Quantitative Data Collection and Analysis A structured questionnaire design for the purpose of this study was administered electronically using the Census and Survey Processing System (CSPro). The instrument captured socio-demographic characteristics, migration status, employment, and health coverage including formal health insurance enrollment and health coverage by institutional affiliation. The latter was assessed through two questions: Are you affiliated with a workplace or institution that provides access to a health facility without direct payment? “Are you covered by a health insurance scheme through your own or a relative’s institutional affiliation?” A composite variable health affiliation was created, coded as “yes” if a participant answered affirmatively to either question. This approach captured informal or indirect coverage (e.g., dependents of university employees or corporate expatriates), which is common in Ghana but often overlooked in insurance studies. Quantitative data were analysed using SPSS version 23. Descriptive statistics summarized sample characteristics, while Chi-square tests assessed associations between migration status and health insurance/affiliation outcomes (P = 0.05). Qualitative Data Collection and Analysis: Following quantitative analysis, semi-structured in-depth interviews were conducted with a purposive subsample of 24 participants (12 migrants, 12 non-migrants). The interview guide was designed purposely for this study and to explore the reasons behind observed coverage patterns. The interview guide, informed by preliminary quantitative results and Andersen’s Behavioral Model, probed participants’ knowledge of NHIS, experiences with enrollment, care-seeking behaviours, and perceptions of barriers. Interviews were audio-recorded, transcribed verbatim, and anonymized using pseudonyms (e.g., “Mr. Sue,” “Borla”). Thematic analysis followed Attride-Stirling’s (2001) thematic network approach, beginning with open coding, followed by the development of a coding frame grounded in both empirical data and theoretical constructs (e.g., “disabling conditions,” “transnational health strategies”). Coding was iterative and reflexive, with constant comparison across migrant and non-migrant narratives to identify convergences and divergences. Limitation A potential weakness of this study is its non-probability sampling methodology, specifically the employment of purposive and snowball sampling for immigrants and convenience sampling for non-migrants. The snowball method may have resulted in the recruitment of individuals possessing similar characteristics. Nevertheless, this concern was addressed in the study by enlisting initial participants with diverse characteristics based on location, institution, and origin. The regions include the eastern, western, northern, and southern parts of Greater Accra (Tema, Alargo, Tetteh Quarshie, Oyibi, and surrounding towns). Results and Discussion Socio-Demographic Profile of Immigrants and Non-Migrants. The study sample comprised 232 participants 116 international migrants and 116 non-migrant recruited from ten communities in Greater Accra. As shown in Table 1, the groups were broadly comparable in age (mean = 31.1 years) and gender distribution (50.4% female). Though statistically significant differences emerged in education, employment, and migration-related characteristics, education levels were high across both groups, but notably higher among immigrants: 46.6% held a bachelor’s degree compared to 31.0% of non-migrants, and 23.3% of immigrants reported postgraduate qualifications versus 13.8% of non-migrants. No immigrant reported having no formal education, whereas 1.7% of non-migrants did. This reflects the composition of Ghana’s migrant population, which includes a large share of international students and skilled professionals. Qualitative interviews confirmed this trend. Most migrants were students: Nigerian participants like Amala (PhD candidate in Public Health) and Forlake (Biomedical Engineering student) were pursuing long-term degrees. Whereas Francophone West African students like Robert (Ivory Coast) and Lola (Ivory Coast) were enrolled in short-term English-language programs to facilitate onward migration or employment. As Robert explained: I came to Ghana to learn English… When I am done with my studies I will move on to the US. In contrast, non-migrants were more likely to be engaged in full-time employment (81.6% vs. 46.7% among migrants), while migrants were overrepresented in part-time work (28.3% vs. 12.2%) or non-employment (25.0% vs. 6.1%), often due to student status or temporary residency. For example, Borla, a Nigerian student, described informal campus work: I do some cleaning work for the Valley View University… the pay is credited to my fees in dollars. These patterns align with Ghana’s role as an educational hub for West African migrants and a destination for Asian and Western expatriates groups whose socio-economic profiles differ markedly from the general Ghanaian population. The high educational attainment among migrants, coupled with their employment precarity, underscores a key paradox: despite possessing strong predisposing factors (per Andersen’s model), many migrants lack stable enabling resources such as employer-sponsored coverage or long-term residency that facilitate health insurance enrollment. Marital status further reflected the youthfulness of the sample: 65.1% were never married, with no significant difference by migration status. Overall, this profile sets the stage for interpreting the stark disparities in health coverage that follow not as a function of poverty or low education, but of structural positioning within Ghana’s health financing system. Table 1 Background Characteristics of Study Participants Total Sample Non-Migrants Immigrants Mean Age = 31.12 Mean Age = 31.62 Mean Age = 30.62 Age group % % % 18–27 52.2 44 60.3 28–37 21.6 25 18.1 38–47 12.5 17.2 7.8 48–57 6.9 6 7.8 58–67 4.7 4.3 5.2 68+ 2.2 3.4 0.9 Total 100 100 100 P = 0.063 Sex Male 49.6 45.7 53.4 Female 50.4 54.3 46.6 P = 0149 Level of Education No education 0.9 1.7 0 Primary 2.6 5.2 0 Middle/JSS/JHS 8.6 14.7 2.6 Voca/Tech/Comm 5.2 3.4 6.9 SHS/SSS 10.8 12.9 8.6 Post Sec Diploma 14.7 17.2 12.1 Bachelor 38.8 31 46.6 Postgraduate 18.5 13.8 23.3 Total 100 100 100 P = 00 Employment Status 64.7 81.6 46.7 Full Time 20 12.2 28.3 Part Time 15.3 6.1 25 Not Employed P = 00 Marital Status Never Married 65.1 62.1 68.1 Married/Living Together 29.7 29.3 30.2 Out of Marriage 5.2 8.3 1.7 Source: Survey Nov-Dec 2018 Disparities in Health Insurance Enrollment by Migration Status A striking disparity in health insurance enrollment emerged between immigrants and non-migrants in Greater Accra. While 59.5% of non-migrants reported current enrollment in a health insurance scheme, only 23.3% of immigrants were similarly covered (Table 2 ). Most alarmingly, 75% of immigrants had never enrolled in any health insurance scheme in Ghana, compared to just 7.8% of non-migrants a tenfold difference that underscores a profound gap in access to formal health financing. This disparity persisted despite the fact that immigrants in the sample were, on average, highly educated (46.6% held bachelor’s degrees or higher) and largely employed (73.3% in part- or full-time work). According to Andersen’s Behavioral Model, such characteristics would typically function as strong enabling and predisposing factors favouring insurance uptake. Yet, structural and informational barriers appear to override these individual advantages Table 2 Health Insurance status among Immigrants and Non-migrant in Ghana Total Sample Immigrants Non-migrants Health Insurance Status % % % Currently Registered 41.4 23.3 59.5 Never Registered 41.8 75 8.7 Previously Registered 16.8 1.7 P = 000 Source: Survey Nov-Dec 2018 Qualitative interviews illuminated the mechanisms behind this exclusion. Many immigrants expressed limited awareness of their eligibility for Ghana’s National Health Insurance Scheme (NHIS). As Borla, a Nigerian student, explained: I am not on any health insurance because I did not know how I could register with the NHIS. Others, like Mr. Sue, a Chinese businessman, voiced frustration with Ghana’s analog administrative system: Ghanaians like paper and card too much… In China, everything is on my phone, insurance, bank account. I do not have to carry paper and card. These narratives reveal that lack of information, reliance on transnational or informal care (e.g., self-medication, private clinics), and aversion to bureaucratic processes particularly among digitally accustomed migrants’ function as disabling conditions that deter enrollment, even when formal eligibility exists. In contrast, non-migrants who were uninsured often cited low perceived need or lack of incentive due to prior non-use of coverage. As Donkor, a Ghanaian trader, noted: I am not on the health insurance because when I first did, I never used it… I take pain killer when I have body pains after work. While both groups engaged in self-medication, the reasons differed: immigrants were often excluded by design (unfamiliarity, system incompatibility), whereas non-migrants were disengaged by choice (low utilization, perceived redundancy). Together, these findings demonstrate that migration status operates as a critical social determinant of health insurance access not because of individual deficits, but because of systemic features that fail to accommodate mobile, non-citizen populations. The near-universal NHIS coverage among insured non-migrants (97.1%) versus the significant share of insured immigrants relying on private schemes (33.3%) further reflects this bifurcation: immigrants who do obtain coverage often do so through employer- or institution-provided private plans, not through Ghana’s public system. This enrollment gap is not merely statistical it represents a policy blind spot in Ghana’s journey toward universal health coverage. As the country hosts an increasingly diverse migrant population, ensuring equitable access to NHIS requires more than legal eligibility; it demands proactive outreach, digital modernization, and culturally responsive enrollment pathways. Patterns of Health Insurance Type Among Immigrants and Non-Migrants Among respondents who reported current health insurance coverage, a clear bifurcation emerged by migration status in terms of insurance modality. While the National Health Insurance Scheme (NHIS) remained the dominant provider overall (88.5% of insured respondents), its uptake was heavily skewed toward non-migrants. A striking 97.1% of insured non-migrants relied on NHIS, compared to only 66.7% of insured immigrants (Table 3 ). Conversely, one-third (33.3%) of insured immigrants were covered by private health insurance, whereas just 1.5% of non-migrants used private schemes Table 3 Health insurance type among immigrant and non-migrants in Ghana Total Sample Immigrants Non-Immigrants Health Insurance Type % % % NHIS/Public 88.4 66.7 97.1 Private 10.5 33.3 1.5 Both Public and Private 1 0 1.4 P = 00 Source: Survey Nov-Dec 2018 This divergence reflects fundamentally different routes to coverage. For most Ghanaian citizens, NHIS is the default and often only accessible public option. Which is embedded in national policy and subsidized through mechanisms like the Social Security and National Insurance Trust (SSNIT). In contrast, many immigrants particularly international students and corporate expatriates gain coverage through institution-mandated private insurance. As a health administrator at the University of Ghana explained: What they do most is, the [foreign] students… are to enrol on a private Health Insurance. The Ghanaian students pay a component of their fees basically for medical services. That is… another form of health insurance. This institutional distinction creates a de facto two-tiered system: citizens are funnelled into the general healthcare system, while many immigrants are channelled into private plans. Often the migrants lack awareness of their eligibility for NHIS or lack the support to navigate its registration process. The qualitative data suggest this is not always a matter of preference, but of structural channelling. For instance, Nigerian student Borla was unaware she could enrol in NHIS, while Chinese businessman Mr. Sue opted out due to frustration with analog bureaucracy yet neither was offered guidance on public alternatives. Notably, no immigrant in the sample reported dual coverage (public + private), whereas 1.4% of non-migrants did further underscoring the exclusivity of immigrants’ private insurance pathways. These patterns reveal that migration status shapes not just whether one is insured, but how one is insured with implications for cost, continuity, and equity. Private schemes may offer faster access but at higher out-of-pocket cost or with limited provider networks, while partial exclusion from NHIS deprives immigrants of a subsidized, nationally integrated safety net. Thus, the disparity in insurance type is not merely administrative it reflects differential inclusion in Ghana’s health financing architecture, where institutional design and informational gaps steer migrants away from public coverage, even when legally eligible. Health Coverage Through Institutional Ties by Migration Status Beyond formal health insurance enrollment, a significant share of respondents accessed care through institutional ties that is, coverage derived from affiliation with an employer, university, or other organization, either directly or as a dependent. Overall, 32.3% of the total sample reported such coverage, with 34.5% of immigrants and 30.2% of non-migrants benefiting from these arrangements (Fig. 1 ). The difference between groups was not statistically significant (p = 0.483), suggesting that institutional affiliation functions as a relatively equitable access pathway though the nature of these ties differed markedly by migration status. For many labour migrants and expatriates, institutional coverage was a condition of employment. As Subor, a Nigerian professional, explained: I was brought to Ghana by my company, and they provided me with accommodation and health insurance. The accommodation was only paid for two years. Now I take care of my own accommodation, but the health insurance is still catered for. This reflects a common practice among multinational firms and international organizations. This often include private health coverage as part of expatriate compensation packages effectively substituting for public NHIS enrolment. In contrast, student migrants frequently lacked such institutional safety nets. Lola, an Ivorian student enrolled in a private English-language institute, noted: My institution has no health facility. I don’t know if foreigners could also register for the Ghanaian national health insurance. Her experience highlights a critical gap: while Ghanaian university students typically receive health coverage through mandatory fee-based schemes (as confirmed by a University of Ghana health administrator), many private institutions catering to international students offer no equivalent. Consequently, student migrants particularly those from Francophone West Africa often fall into a coverage void: ineligible for employer-based plans, unaware of NHIS eligibility, and unsupported by their host institutions. Among non-migrants, institutional coverage was more commonly linked to formal employment in the public or private sector, or to enrollment in public universities. However, even here, coverage was not universal reflecting Ghana’s fragmented health financing landscape. Notably, institutional ties often overlap with private insurance, as seen in the previous section where one-third of insured immigrants relied on private schemes many of which were employer-provided. This suggests that for immigrants, institutional affiliation frequently channels them into private, rather than public, health financing streams. Thus, while institutional ties provide a vital alternative to direct insurance enrollment for both groups, their distribution and reliability are shaped by migration status. For some immigrants, these ties offer robust coverage; for others especially short-term or student migrants they are absent altogether, exacerbating vulnerability. This duality underscores the need for policies that either extend institutional coverage mandates to all educational and employment settings or simplify NHIS access for those without organizational affiliation. Conclusion Ghana’s transformation into a regional migration hub demands a reimagining of its health financing architecture one that moves beyond citizen-centric models to embrace the realities of a mobile, diverse population. This study reveals a stark and systemic disparity: while the National Health Insurance Scheme (NHIS) serves as the backbone of health coverage for Ghanaian citizens, international migrants remain largely excluded, with three-quarters never having enrolled in any health insurance scheme. This gap persists despite migrants’ relatively high levels of education and employment factors that typically function as enabling resources in Andersen’s Behavioral Model. Our mixed-methods analysis shows that this exclusion is not due to individual choice alone, but stems from structural and informational barriers that operate as disabling conditions . Immigrants frequently lack awareness of their eligibility for NHIS, encounter analog bureaucratic processes ill-suited to digitally accustomed populations, and rely on transnational or informal care strategies such as self-medication or private clinics that reduce perceived need for local insurance. In contrast, non-migrants who forgo insurance often do so out of low utilization or lack of incentive, not systemic inaccessibility. Furthermore, the nature of coverage differs profoundly by migration status. Among the insured, one-third of immigrants rely on private insurance, often provided by employers or universities, while 97% of non-migrants are covered by NHIS. This bifurcation points to a de facto two-tiered system: citizens are largely integrated into the public safety net, while many migrants are channelled into privatized, institution-dependent arrangements or left entirely uncovered, as in the case of students from private language institutes. These findings challenge the assumption that legal eligibility equates to meaningful access. As Ghana advances toward universal health coverage (UHC), it must confront the policy blind spot that renders non-citizens invisible in health financing design. We therefore recommend: Completely Digitizing NHIS enrollment and verification to align with the expectations of a globally mobile population; Integrating pre-arrival health insurance orientation into visa and admission processes for students and labour migrants; Mandating inclusive health coverage policies for all educational and employment institutions hosting international populations; and Launching targeted outreach campaigns in multiple languages to clarify NHIS eligibility and benefits for non-citizens. By reframing migrants not as transient outsiders but as integral participants in Ghana’s social and economic fabric, policymakers can transform NHIS from a heavily citizen-oriented scheme into a truly universal system. In doing so, Ghana would not only fulfil its UHC commitments but also set a precedent for inclusive health governance in an increasingly interconnected Africa. Abbreviations NHIS : National Health Insurance Scheme LMIC s: Low- and Middle-Income Countries UHC : Universal Health Coverage SSNIT : Social Security and National Insurance Trust CSPro : Census and Survey Processing System SPSS : Statistical Package for the Social Sciences Declarations Ethics approval and consent to participate This study received ethical approval from the University of Ghana’s Ethics Committee for the Humanities (Reference: ECH 191/17–18). All participants provided voluntary informed consent prior to participation. The study was also conducted following ethical standards in social science and received approval from the University of Ghana’s ethics committee for the Humanities (reference ECH 191/17-18). Its upheld core ethical principles, including voluntary informed consent, confidentiality, respect for participants' autonomy, and data protection. The research adhered to international best practices for non-biomedical studies involving human participants. Although the Declaration of Helsinki primarily governs medical research, the study’s ethical approach is consistent with the fundamental values of participant welfare and ethical oversight Consent for publication Not applicable. The manuscript contains no individually identifiable data or images requiring specific participant consent for publication. Availability of data and materials The datasets generated and analysed during this study are not publicly available due to confidentiality and ethical restrictions but may be made available from the corresponding author on reasonable request and with appropriate ethical clearance. Competing Interests The authors declare that they have no financial, personal, professional, or other relationships that could inappropriately influence or be perceived to influence the work reported in this manuscript. Dr. Alberta Teye Agudey and Prof. Margaret Delali Badasu affirm that there are no competing interests related to employment, consultancy, patents, products in development, or marketed products that pertain to this study. The research was conducted independently, without involvement from insurance providers, government agencies, or private institutions that might benefit from the findings. Funding This research was conducted as part of the author’s self-funded PhD program. While tuition fees were borne personally by the author, partial financial support was provided through a part-time Graduate Assistantship awarded by the Centre for Migration Studies, and the College of Humanities (University of Ghana). The assistantship contributed to modest research-related expenses but did not influence the study design, data collection, analysis, interpretation, or manuscript preparation Authors' Contributions Dr. Alberta Teye Agudey: Conceptualization, methodology, data collection, formal analysis, writing the original draft, project administration. Prof. Margaret Delali Badasu: Supervision, critical review, theoretical framing, writing review & editing, validation. Both authors read and approved the final manuscript. Acknowledgements The authors thank all the participants (both immigrants and Ghanaians) in the study areas. We, the authors, are grateful for the participants' generosity in sharing their time and experiences. We also acknowledge the support of the Centre for Migration Studies and the Regional Institute for Population Studies at the University of Ghana. Special thanks to the field assistants George FiiFi Botchway and Beula Esther Sunday. We are also thankful to research mentors Professor Joseph Kofi Teye and Professor John K. Anarfi, who contributed to the successful execution of this study. References Adu-Boahene, A. B., & Dapaah-Afriyie, K. (2017). Health-needs assessment for West African immigrants in Greater Providence, RI. Rhode Island Medical Journal, 100 (1), 47–49. Andersen, R. M. (1968). A behavioral model of families’ use of health services . Center for Health Administration Studies, University of Chicago. Andersen, R. M. (1995). Revising the behavioral model and access to medical care: Does it matter? Journal of Health and Social Behavior, 36 (1), 1–10. https://doi.org/10.2307/2137284 Awoke, M. A., Negin, J., Moller, J., Farrell, P., Yawson, A. E., Biritwum, R. B., & Kowal, P. (2017). Predictors of public and private healthcare utilization and associated health system responsiveness among older adults in Ghana. 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D. (2017). Strategies and initiatives in acculturation: Voices from Ghana. Journal of International Students, 7 (4), 1065–1079. https://doi.org/10.32674/jis.v7i4.185 Dias, S. F., Severo, M., & Barros, H. (2008). Determinants of health care utilization by migrants in Portugal. BMC Health Services Research, 8 , Article 207. https://doi.org/10.1186/1472-6963-8-207 Donaldson, C., & Gerard, K. (1993). Economics of health care financing: The visible hand . Macmillan. Gajate-Garrido, G., & Owusu, R. (2013). The National Health Insurance Scheme in Ghana: Implementation challenges and proposed solutions . Innovations for Poverty Action. Ghana Immigration Service. (2008). Migration to and from Ghana (compilation from 2000 to 2008) . Ghana Statistical Service. (2014). 2010 Population & housing census: District analytical report—Agotime Ziope District . Ghana Statistical Service. (2017). Ghana living standards survey round 7 (GLSS 7): Main report . https://statsghana.gov.gh/ Harvey, V. A. A. (2014). Socio-economic and cultural determinants of health care services utilization in Ghana [Master’s thesis, University of Nevada, Las Vegas]. UNLV Theses, Dissertations, Professional Papers and Capstones. https://digitalscholarship.unlv.edu/thesesdissertations/2321 Jehu-Appiah, C., Aryeetey, G., Spaan, E., De Hoop, T., Agyepong, I., & Baltussen, R. (2011). Equity aspects of the National Health Insurance Scheme in Ghana: Who is enrolling, who is not and why? Social Science & Medicine, 72 (2), 157–165. https://doi.org/10.1016/j.socscimed.2010.10.023 Juárez, S. P., Honkaniemi, H., Dunlavy, A. C., Aldridge, R. W., Barreto, M. L., Katikireddi, S. V., & Rostila, M. (2019). Effects of non-health-targeted policies on migrant health: A systematic review and meta-analysis. The Lancet Global Health, 7 (4), e420–e435. https://doi.org/10.1016/S2214-109X(19)30034-1 Kuuire, V. Z., Bisung, E., Rishworth, A., Dixon, J., & Luginaah, I. (2016). Health-seeking behaviour during times of illness: A study among adults in a resource poor setting in Ghana. Journal of Public Health, 38 (4), e545–e553. https://doi.org/10.1093/pubmed/fdw019 Kwarteng, A., Akazili, J., Welaga, P., Dalinjong, P. A., Asante, K. P., Sarpong, D., Soremekun, S., & Sankoh, O. (2020). The state of enrollment on the National Health Insurance Scheme in rural Ghana after eight years of implementation. International Journal for Equity in Health, 19 (1), Article 133. https://doi.org/10.1186/s12939-020-01248-3 Kwarteng-Nantwi, E. (2019). Adjustment needs and coping strategies of international students of universities in Southern Ghana [Doctoral dissertation, University of Cape Coast]. Lattof, S. R. (2018). Health insurance and care-seeking behaviours of female migrants in Accra, Ghana. Health Policy and Planning, 33 (4), 505–515. https://doi.org/10.1093/heapol/czy005 Nyarko, F., & Ephraim, L. (2016). Student mobility in international education: The case in Ghana. International Journal of Academic Research in Business and Social Sciences, 6 (6), 177–188. https://doi.org/10.6007/IJARBSS/v6-i6/2220 Okoroh, J. S., Essoun, S., Seddoh, A., Harris, H. G., Weissman, J. S., Dsane-Selby, L., & Riviello, R. (2018). Evaluating the impact of the National Health Insurance Scheme of Ghana on out-of-pocket expenditures: A systematic review. BMC Health Services Research, 18 (1), Article 501. https://doi.org/10.1186/s12913-018-3299-5 Roth, R. J., Sr., & Kunreuther, H. (Eds.). (1998). Paying the price: The status and role of insurance against natural disasters in the United States . Joseph Henry Press. Smith, G. H., III, & Scheid, T. L. (2014). An application of the Andersen Model of Health Utilization to the understanding of the role of race-concordant doctor–patient relationships in reducing health disparities. In J. Kronenfeld (Ed.), Social determinants, health disparities and linkages to health and health care (pp. 187–214). Emerald Group Publishing. https://doi.org/10.1108/S0275-495920140000031008 Teye, J. K., Arhin, A. A., & Anamzoya, A. S. (2015). Achievements and challenges of the National Health Insurance Scheme in Ghana. Current Politics and Economics of Africa, 8 (3), 487–508. Van Der Wielen, N., Channon, A. A., & Falkingham, J. (2018). Does insurance enrolment increase healthcare utilisation among rural-dwelling older adults? Evidence from the National Health Insurance Scheme in Ghana. BMJ Global Health, 3 (1), e000590. https://doi.org/10.1136/bmjgh-2017-000590 Wassink, J. (2018). Uninsured migrants: Health insurance coverage and access to care among Mexican return migrants. Demographic Research, 38 , Article 37. https://doi.org/10.4054/DemRes.2018.38.37 Witter, S., Arhinful, D. K., Kusi, A., & Zakariah-Akoto, S. (2007). The experience of Ghana in implementing a user fee exemption policy to provide free delivery care. Reproductive Health Matters, 15 (30), 61–71. https://doi.org/10.1016/S0968-8080(07)30332-4 World Health Organization. (2000). The world health report 2000: Health systems—Improving performance . WHO. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8866865","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":590605764,"identity":"85a815bb-0eb3-4a81-8f28-f48f7f5e6238","order_by":0,"name":"Alberta Teye Agudey","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYDACHgY2MM0PIhIKiNdiwCDZANJiQIoWgwMMYJow4O85Y/bg454/8sbnVyd+eGDAIM8vdgC/FomzPeaGM54ZGG678XazBNBhhjNnJxCw5jyPmTTPAQPGbTfObgBpSTC4TUCLPEjLnwMG9ptnnN38gygtBmd7zKQZDhgkbuDv3UacLYZnjpUb9hwwTp5xg3ebRYKBBGG/yJ1J3vbgxwE52/7+s5tv/qiwkeeXJqAFASTAKiWIVQ4C/AdIUT0KRsEoGAUjCQAAmkBFiouFToIAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-3242-9373","institution":"Ensign Global University","correspondingAuthor":true,"prefix":"","firstName":"Alberta","middleName":"Teye","lastName":"Agudey","suffix":""},{"id":590606921,"identity":"0ebffebd-7e93-403b-9025-7cf5571249d3","order_by":1,"name":"Delali Magaret Badasu","email":"","orcid":"https://orcid.org/0000-0001-6481-9582","institution":"University of Ghana, Regional Institute for Population Studies","correspondingAuthor":false,"prefix":"","firstName":"Delali","middleName":"Magaret","lastName":"Badasu","suffix":""}],"badges":[],"createdAt":"2026-02-13 03:16:13","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8866865/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8866865/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102743071,"identity":"849e363c-6ca3-46ea-af94-9f19fea7d012","added_by":"auto","created_at":"2026-02-16 08:11:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":56758,"visible":true,"origin":"","legend":"\u003cp\u003eHealth coverage by virtue of affiliation to a workplace/institution\u003c/p\u003e\n\u003cp\u003eSource: Survey Nov-Dec 2018 (Chi-Square; P=0.483)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8866865/v1/c717fda82b8bcafb835685cf.png"},{"id":102748791,"identity":"3d0b977b-0885-41c7-8494-58d2506dc30c","added_by":"auto","created_at":"2026-02-16 09:11:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":977575,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8866865/v1/4470f0e1-d5d0-4ba6-87f4-56c127f9f0c2.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eHealth Coverage in a Migration Hub: Comparing Insurance Access Among Immigrants and Ghanaians\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eGlobally, international migration is reshaping health systems, particularly in low- and middle-income countries (LMICs) that are increasingly becoming destinations not just transit points or origins for migrants. In sub-Saharan Africa, Ghana has emerged as a notable hub for regional and international migration, hosting an estimated 400,000 immigrants. This is about 1.5% of its population as of the 2010 census, with numbers likely higher today (GSS, 2014; GMFA\u0026amp;RI, 2016). Recent analyses suggest that Ghana\u0026rsquo;s appeal as a destination for students, professionals, and entrepreneurs from West Africa, Asia, and beyond has grown steadily, especially in urban centres like Greater Accra (Kwarteng-Nantwi, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Boafo-Arthur et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nyarko \u0026amp; Ephraim, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile much attention has historically focused on Ghana as a migrant-sending country, its evolving role as a receiving nation demands urgent examination of how its health financing mechanisms operates. Particularly how the National Health Insurance Scheme (NHIS) serves the non-citizen populations. Health insurance is widely recognized as a critical tool for mitigating financial barriers to care and advancing universal health coverage (UHC) (WHO, 2000; Okoroh et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Ghana\u0026rsquo;s NHIS, launched in 2003, was designed to reduce out-of-pocket expenditures and improve equitable access to health services (Witter et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Despite notable achievements, challenges persist including administrative inefficiencies, reliance on paper-based systems, delayed provider reimbursements, and uneven enrollment (Jehu-Appiah et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Addae-Koranche, 2013; Gajate-Garrido \u0026amp; Owusu, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCrucially, existing research on NHIS has overwhelmingly focused on Ghanaian citizens. Recent national studies on insurance enrollment, equity, and health-seeking behavior such as those by Ayanore et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), Kwarteng et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and Van Der Wielen et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) rarely disaggregate findings by migration status or consider the unique institutional positioning of non-citizens. This gap is significant: immigrants whether students, labour migrants, or expatriates often face structural and informational barriers that differ from those of native-born populations, including limited awareness of local health financing procedures, exclusion from employer-based coverage, reliance on informal care, and difficulties navigating bureaucratic processes (Lattof, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ju\u0026aacute;rez et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Ghana, where health insurance enrollment is voluntary and heavily dependent on individual initiative, such barriers may disproportionately affect non-citizens. Lattof\u0026rsquo;s (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) qualitative study of female migrants in Accra found that many were unaware they were eligible for NHIS or assumed it was only for Ghanaians. Similarly, Adu-Boahene and Dapaah-Afriyie (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) noted that West African immigrants in diaspora settings often rely on transnational health strategies, including self-medication and cross-border care, which may reduce perceived need for local insurance.\u003c/p\u003e \u003cp\u003e To understand these dynamics, this study draws on Andersen\u0026rsquo;s Behavioral Model of Health Services Use (1968, 1995), which posits that health care access is shaped by predisposing (e.g., education, culture), enabling (e.g., income, insurance, institutional support), and need-based factors. While the model has been widely applied in Ghanaian contexts (Awoke et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Kuuire et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), it has rarely been used to examine how migration status intersects with these factors to shape insurance coverage especially when considering both formal insurance and informal affiliation-based coverage (e.g., through universities or employers).\u003c/p\u003e \u003cp\u003eAgainst this backdrop, we ask: How does health insurance coverage and access to care through institutional affiliation differ between immigrants and non-migrants in urban Ghana. We also sort to understand the underlying factors explaining these disparities? Using an explanatory sequential mixed-methods design, this study compares insurance enrollment patterns among 116 immigrants and 116 non-migrants in Greater Accra and explores the lived experiences behind the statistics. By concentrating on the voices of an often-invisible population, this research contributes to more inclusive health financing policies in an era of increasing mobility.\u003c/p\u003e"},{"header":"Theoretical Review","content":"\u003cp\u003eUnderstanding disparities in health insurance coverage requires a framework that accounts for both individual agency and structural context. This study employs Andersen\u0026rsquo;s Behavioral Model of Health Services Use (Andersen, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) a widely validated and adaptable theoretical lens that explains health care access as the interplay of predisposing, enabling, and need-based factors.\u003c/p\u003e \u003cp\u003ePredisposing factors such as age, education, migration status, and health belief systems shape an individual\u0026rsquo;s propensity to seek care. Enabling factors, including income, health insurance, social support, and institutional arrangements (e.g., workplace-based coverage), determine the practical means to access services. Need factors, whether perceived or clinically assessed, activate care-seeking behavior. Crucially, Andersen\u0026rsquo;s \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1995\u003c/span\u003e revision expanded the model to incorporate external environmental influences, such as health system organization and national policy making it especially suited for analyzing access in complex, pluralistic systems like Ghana\u0026rsquo;s.\u003c/p\u003e \u003cp\u003eThe model has been extensively applied in Ghanaian health research. Awoke et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) used it to show that wealth and education increase the likelihood of private facility use. While Kuuire et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) found that NHIS enrollment alone does not guarantee care-seeking among the poor highlighting gaps between formal coverage and actual access. Harvey (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) further demonstrated that cultural and socioeconomic predisposing factors significantly influence health service utilization among Ghanaians.\u003c/p\u003e \u003cp\u003eHowever, these studies focus almost exclusively on citizen populations. Migration status introduces unique dynamics that challenge standard applications of the model. Immigrants may possess strong predisposing factors (e.g., high education levels, as seen in our sample) and enabling resources (e.g., employment), yet remain uninsured due to structural barriers such as lack of information about NHIS eligibility, bureaucratic complexity, or reliance on transnational health strategies (Lattof, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Adu-Boahene \u0026amp; Dapaah-Afriyie, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These are not merely absences of enabling factors but active disabling conditions that deter enrollment despite apparent capacity.\u003c/p\u003e \u003cp\u003eThis study therefore extends Andersen\u0026rsquo;s framework by treating migration status as a cross-cutting variable that reshapes the relationship between predisposing/enabling factors and health insurance uptake. Moreover, by integrating qualitative insights with survey data, we uncover how systemic features like Ghana\u0026rsquo;s paper- and card-based insurance system function as disabling mechanisms, particularly for digitally oriented migrants accustomed to streamlined, electronic platforms. In doing so, we move beyond using the model as a predictive tool and instead leverage it to interpret the lived experience of exclusion in an emerging migrant destination.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eApplication of the Andersen Model in Contemporary Studies\u003c/h2\u003e \u003cp\u003eThe Andersen Behavioral Model has been widely applied across global health contexts to unpack disparities in health service utilization (Azfredrick \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Smith and Scheid \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), with over 300 empirical studies identified in a systematic review covering 1998\u0026ndash;2011 alone (Babitsch et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In Ghana, the model has proven particularly useful in explaining patterns of health care access among diverse populations. Awoke et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) found that higher education, wealth, and age key predisposing and enabling factors significantly increased the likelihood of using private health facilities among older adults. Similarly, Kuuire et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) demonstrated that despite NHIS enrollment, poor adults in resource-limited settings were less likely to seek formal care, underscoring that insurance alone does not guarantee access when other enabling resources (e.g., transportation, trust in providers) are lacking.\u003c/p\u003e \u003cp\u003eHarvey\u0026rsquo;s (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) analysis of Demographic and Health Survey data further confirmed that socio-cultural predisposing factors such as religion and education shape health-seeking behavior in Ghana. Collectively, these studies validate the model\u0026rsquo;s utility in the Ghanaian context but share a critical limitation: they focus exclusively on citizen populations, treating \u0026ldquo;immigrants in Ghana\u0026rdquo; as an unexamined norm.\u003c/p\u003e \u003cp\u003eGlobally, only a handful of studies have applied Andersen\u0026rsquo;s framework to migrant populations. Dias et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) identified language barriers and legal status as key disabling conditions for migrants in Portugal, while Wassink (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) found that return migrants in Mexico faced administrative exclusion from insurance systems. Closer to home, Lattof (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) documented how female migrants in Accra often assumed NHIS was unavailable to non-citizens a misconception rooted in poor information dissemination and institutional invisibility. These findings suggest that migration status itself reshapes the operation of predisposing and enabling factors, introducing barriers not captured in standard applications of the model.\u003c/p\u003e \u003cp\u003eNotably, none of these studies explicitly conceptualize structural features of health systems such as paper-based bureaucracy or lack of digital infrastructure as \u0026ldquo;disabling conditions.\u0026rdquo; This is a critical oversight in contexts like Ghana, where administrative complexity may deter even highly educated, employed migrants from enrolling. By combining quantitative data with qualitative narratives on care seeking logic, our study advances the Andersen framework beyond its traditional predictive function, using it instead as a lens to interpret how policy design can inadvertently mobile populations.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methodology","content":"\u003cp\u003eThis study employed an explanatory sequential mixed-methods design (Creswell \u0026amp; Plano Clark, 2017; Teye et al \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), wherein quantitative data were collected and analysed first to identify patterns in health insurance coverage. After which qualitative interviews to explain and contextualize these findings particularly the stark disparities observed between immigrants and non-migrants were conducted.\u003c/p\u003e\n\u003ch3\u003eStudy Setting and Sampling\u003c/h3\u003e\n\u003cp\u003eData were collected between November and December 2018 in the Greater Accra Region of Ghana a major destination for international migrants, hosting an estimated 60% of the country\u0026rsquo;s foreign-born population (GSS, 2014). A total of 232 participants were recruited: 116 international migrants and 116 non-migrants (Ghanaians). Migrants were eligible if they had resided continuously in Ghana for at least six months; non-migrants were required to have remained in Ghana during the same period and were sampled from the same neighbourhoods as migrant participants to ensure contextual comparability. Purposive and snowball sampling were used to identify migrants across ten communities (Accra Central, Alajo, Legon, Weija, Osu, Tema, Tetteh Quarshie, New Aplaku, New Bortianor, and Valley View/Oyibi), while non-migrants were selected using convenience sampling within the same localities.\u003c/p\u003e\n\u003ch3\u003eQuantitative Data Collection and Analysis\u003c/h3\u003e\n\u003cp\u003eA structured questionnaire design for the purpose of this study was administered electronically using the Census and Survey Processing System (CSPro). The instrument captured socio-demographic characteristics, migration status, employment, and health coverage including formal health insurance enrollment and health coverage by institutional affiliation. The latter was assessed through two questions:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAre you affiliated with a workplace or institution that provides access to a health facility without direct payment?\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e\u0026ldquo;Are you covered by a health insurance scheme through your own or a relative\u0026rsquo;s institutional affiliation?\u0026rdquo;\u003c/p\u003e \u003cp\u003eA composite variable health affiliation was created, coded as \u0026ldquo;yes\u0026rdquo; if a participant answered affirmatively to either question. This approach captured informal or indirect coverage (e.g., dependents of university employees or corporate expatriates), which is common in Ghana but often overlooked in insurance studies.\u003c/p\u003e \u003cp\u003eQuantitative data were analysed using SPSS version 23. Descriptive statistics summarized sample characteristics, while Chi-square tests assessed associations between migration status and health insurance/affiliation outcomes (P\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e\n\u003ch3\u003eQualitative Data Collection and Analysis:\u003c/h3\u003e\n\u003cp\u003eFollowing quantitative analysis, semi-structured in-depth interviews were conducted with a purposive subsample of 24 participants (12 migrants, 12 non-migrants). The interview guide was designed purposely for this study and to explore the reasons behind observed coverage patterns. The interview guide, informed by preliminary quantitative results and Andersen\u0026rsquo;s Behavioral Model, probed participants\u0026rsquo; knowledge of NHIS, experiences with enrollment, care-seeking behaviours, and perceptions of barriers.\u003c/p\u003e \u003cp\u003eInterviews were audio-recorded, transcribed verbatim, and anonymized using pseudonyms (e.g., \u0026ldquo;Mr. Sue,\u0026rdquo; \u0026ldquo;Borla\u0026rdquo;). Thematic analysis followed Attride-Stirling\u0026rsquo;s (2001) thematic network approach, beginning with open coding, followed by the development of a coding frame grounded in both empirical data and theoretical constructs (e.g., \u0026ldquo;disabling conditions,\u0026rdquo; \u0026ldquo;transnational health strategies\u0026rdquo;). Coding was iterative and reflexive, with constant comparison across migrant and non-migrant narratives to identify convergences and divergences.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLimitation\u003c/h2\u003e \u003cp\u003eA potential weakness of this study is its non-probability sampling methodology, specifically the employment of purposive and snowball sampling for immigrants and convenience sampling for non-migrants. The snowball method may have resulted in the recruitment of individuals possessing similar characteristics. Nevertheless, this concern was addressed in the study by enlisting initial participants with diverse characteristics based on location, institution, and origin. The regions include the eastern, western, northern, and southern parts of Greater Accra (Tema, Alargo, Tetteh Quarshie, Oyibi, and surrounding towns).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003e \u003cb\u003eSocio-Demographic Profile of Immigrants and Non-Migrants.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe study sample comprised 232 participants 116 international migrants and 116 non-migrant recruited from ten communities in Greater Accra. As shown in Table\u0026nbsp;1, the groups were broadly comparable in age (mean\u0026thinsp;=\u0026thinsp;31.1 years) and gender distribution (50.4% female). Though statistically significant differences emerged in education, employment, and migration-related characteristics, education levels were high across both groups, but notably higher among immigrants: 46.6% held a bachelor\u0026rsquo;s degree compared to 31.0% of non-migrants, and 23.3% of immigrants reported postgraduate qualifications versus 13.8% of non-migrants. No immigrant reported having no formal education, whereas 1.7% of non-migrants did. This reflects the composition of Ghana\u0026rsquo;s migrant population, which includes a large share of international students and skilled professionals.\u003c/p\u003e \u003cp\u003eQualitative interviews confirmed this trend. Most migrants were students: Nigerian participants like Amala (PhD candidate in Public Health) and Forlake (Biomedical Engineering student) were pursuing long-term degrees. Whereas Francophone West African students like Robert (Ivory Coast) and Lola (Ivory Coast) were enrolled in short-term English-language programs to facilitate onward migration or employment. As Robert explained:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eI came to Ghana to learn English\u0026hellip; When I am done with my studies I will move on to the US.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn contrast, non-migrants were more likely to be engaged in full-time employment (81.6% vs. 46.7% among migrants), while migrants were overrepresented in part-time work (28.3% vs. 12.2%) or non-employment (25.0% vs. 6.1%), often due to student status or temporary residency. For example, Borla, a Nigerian student, described informal campus work:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eI do some cleaning work for the Valley View University\u0026hellip; the pay is credited to my fees in dollars.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThese patterns align with Ghana\u0026rsquo;s role as an educational hub for West African migrants and a destination for Asian and Western expatriates groups whose socio-economic profiles differ markedly from the general Ghanaian population. The high educational attainment among migrants, coupled with their employment precarity, underscores a key paradox: despite possessing strong \u003cem\u003epredisposing\u003c/em\u003e factors (per Andersen\u0026rsquo;s model), many migrants lack stable \u003cem\u003eenabling\u003c/em\u003e resources such as employer-sponsored coverage or long-term residency that facilitate health insurance enrollment.\u003c/p\u003e \u003cp\u003eMarital status further reflected the youthfulness of the sample: 65.1% were never married, with no significant difference by migration status. Overall, this profile sets the stage for interpreting the stark disparities in health coverage that follow not as a function of poverty or low education, but of structural positioning within Ghana\u0026rsquo;s health financing system.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;1 Background Characteristics of Study Participants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal Sample\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eNon-Migrants\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003eImmigrants\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMean Age\u0026thinsp;=\u0026thinsp;31.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMean Age\u0026thinsp;=\u0026thinsp;31.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMean Age\u0026thinsp;=\u0026thinsp;30.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u0026ndash;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38\u0026ndash;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e48\u0026ndash;57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e58\u0026ndash;67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e68+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of Education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle/JSS/JHS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVoca/Tech/Comm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSHS/SSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost Sec Diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostgraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFull Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePart Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever Married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMarried/Living Together\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOut of Marriage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eSource: Survey Nov-Dec 2018\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eDisparities in Health Insurance Enrollment by Migration Status\u003c/h3\u003e\n\u003cp\u003eA striking disparity in health insurance enrollment emerged between immigrants and non-migrants in Greater Accra. While 59.5% of non-migrants reported current enrollment in a health insurance scheme, only 23.3% of immigrants were similarly covered (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Most alarmingly, 75% of immigrants had never enrolled in any health insurance scheme in Ghana, compared to just 7.8% of non-migrants a tenfold difference that underscores a profound gap in access to formal health financing.\u003c/p\u003e \u003cp\u003eThis disparity persisted despite the fact that immigrants in the sample were, on average, highly educated (46.6% held bachelor\u0026rsquo;s degrees or higher) and largely employed (73.3% in part- or full-time work). According to Andersen\u0026rsquo;s Behavioral Model, such characteristics would typically function as strong \u003cem\u003eenabling\u003c/em\u003e and \u003cem\u003epredisposing\u003c/em\u003e factors favouring insurance uptake. Yet, structural and informational barriers appear to override these individual advantages\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHealth Insurance status among Immigrants and Non-migrant in Ghana\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImmigrants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-migrants\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth Insurance Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently Registered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever Registered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreviously Registered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSource: Survey Nov-Dec 2018\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eQualitative interviews illuminated the mechanisms behind this exclusion. Many immigrants expressed limited awareness of their eligibility for Ghana\u0026rsquo;s National Health Insurance Scheme (NHIS). As Borla, a Nigerian student, explained:\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eI am not on any health insurance because I did not know how I could register with the NHIS.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eOthers, like Mr. Sue, a Chinese businessman, voiced frustration with Ghana\u0026rsquo;s analog administrative system:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eGhanaians like paper and card too much\u0026hellip; In China, everything is on my phone, insurance, bank account. I do not have to carry paper and card.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThese narratives reveal that lack of information, reliance on transnational or informal care (e.g., self-medication, private clinics), and aversion to bureaucratic processes particularly among digitally accustomed migrants\u0026rsquo; function as disabling conditions that deter enrollment, even when formal eligibility exists.\u003c/p\u003e \u003cp\u003eIn contrast, non-migrants who were uninsured often cited low perceived need or lack of incentive due to prior non-use of coverage. As Donkor, a Ghanaian trader, noted:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eI am not on the health insurance because when I first did, I never used it\u0026hellip; I take pain killer when I have body pains after work.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhile both groups engaged in self-medication, the reasons differed: immigrants were often excluded by design (unfamiliarity, system incompatibility), whereas non-migrants were disengaged by choice (low utilization, perceived redundancy).\u003c/p\u003e \u003cp\u003eTogether, these findings demonstrate that migration status operates as a critical social determinant of health insurance access not because of individual deficits, but because of systemic features that fail to accommodate mobile, non-citizen populations. The near-universal NHIS coverage among insured non-migrants (97.1%) versus the significant share of insured immigrants relying on private schemes (33.3%) further reflects this bifurcation: immigrants who do obtain coverage often do so through employer- or institution-provided private plans, not through Ghana\u0026rsquo;s public system.\u003c/p\u003e \u003cp\u003eThis enrollment gap is not merely statistical it represents a policy blind spot in Ghana\u0026rsquo;s journey toward universal health coverage. As the country hosts an increasingly diverse migrant population, ensuring equitable access to NHIS requires more than legal eligibility; it demands proactive outreach, digital modernization, and culturally responsive enrollment pathways.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePatterns of Health Insurance Type Among Immigrants and Non-Migrants\u003c/h2\u003e \u003cp\u003eAmong respondents who reported current health insurance coverage, a clear bifurcation emerged by migration status in terms of insurance modality. While the National Health Insurance Scheme (NHIS) remained the dominant provider overall (88.5% of insured respondents), its uptake was heavily skewed toward non-migrants. A striking 97.1% of insured non-migrants relied on NHIS, compared to only 66.7% of insured immigrants (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Conversely, one-third (33.3%) of insured immigrants were covered by private health insurance, whereas just 1.5% of non-migrants used private schemes\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHealth insurance type among immigrant and non-migrants in Ghana\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImmigrants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-Immigrants\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth Insurance Type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNHIS/Public\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoth Public and Private\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSource: Survey Nov-Dec 2018\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThis divergence reflects fundamentally different routes to coverage. For most Ghanaian citizens, NHIS is the default and often only accessible public option. Which is embedded in national policy and subsidized through mechanisms like the Social Security and National Insurance Trust (SSNIT). In contrast, many immigrants particularly international students and corporate expatriates gain coverage through institution-mandated private insurance. As a health administrator at the University of Ghana explained:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWhat they do most is, the [foreign] students\u0026hellip; are to enrol on a private Health Insurance. The Ghanaian students pay a component of their fees basically for medical services. That is\u0026hellip; another form of health insurance.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThis institutional distinction creates a de facto two-tiered system: citizens are funnelled into the general healthcare system, while many immigrants are channelled into private plans. Often the migrants lack awareness of their eligibility for NHIS or lack the support to navigate its registration process. The qualitative data suggest this is not always a matter of preference, but of structural channelling. For instance, Nigerian student Borla was unaware she could enrol in NHIS, while Chinese businessman Mr. Sue opted out due to frustration with analog bureaucracy yet neither was offered guidance on public alternatives.\u003c/p\u003e \u003cp\u003eNotably, no immigrant in the sample reported dual coverage (public\u0026thinsp;+\u0026thinsp;private), whereas 1.4% of non-migrants did further underscoring the exclusivity of immigrants\u0026rsquo; private insurance pathways. These patterns reveal that migration status shapes not just whether one is insured, but how one is insured with implications for cost, continuity, and equity. Private schemes may offer faster access but at higher out-of-pocket cost or with limited provider networks, while partial exclusion from NHIS deprives immigrants of a subsidized, nationally integrated safety net.\u003c/p\u003e \u003cp\u003eThus, the disparity in insurance type is not merely administrative it reflects differential inclusion in Ghana\u0026rsquo;s health financing architecture, where institutional design and informational gaps steer migrants away from public coverage, even when legally eligible.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHealth Coverage Through Institutional Ties by Migration Status\u003c/h2\u003e \u003cp\u003eBeyond formal health insurance enrollment, a significant share of respondents accessed care through institutional ties that is, coverage derived from affiliation with an employer, university, or other organization, either directly or as a dependent. Overall, 32.3% of the total sample reported such coverage, with 34.5% of immigrants and 30.2% of non-migrants benefiting from these arrangements (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The difference between groups was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.483), suggesting that institutional affiliation functions as a relatively equitable access pathway though the nature of these ties differed markedly by migration status.\u003c/p\u003e \u003cp\u003eFor many labour migrants and expatriates, institutional coverage was a condition of employment. As Subor, a Nigerian professional, explained:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eI was brought to Ghana by my company, and they provided me with accommodation and health insurance. The accommodation was only paid for two years. Now I take care of my own accommodation, but the health insurance is still catered for.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThis reflects a common practice among multinational firms and international organizations. This often include private health coverage as part of expatriate compensation packages effectively substituting for public NHIS enrolment.\u003c/p\u003e \u003cp\u003eIn contrast, student migrants frequently lacked such institutional safety nets. Lola, an Ivorian student enrolled in a private English-language institute, noted:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eMy institution has no health facility. I don\u0026rsquo;t know if foreigners could also register for the Ghanaian national health insurance.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eHer experience highlights a critical gap: while Ghanaian university students typically receive health coverage through mandatory fee-based schemes (as confirmed by a University of Ghana health administrator), many private institutions catering to international students offer no equivalent. Consequently, student migrants particularly those from Francophone West Africa often fall into a coverage void: ineligible for employer-based plans, unaware of NHIS eligibility, and unsupported by their host institutions.\u003c/p\u003e \u003cp\u003eAmong non-migrants, institutional coverage was more commonly linked to formal employment in the public or private sector, or to enrollment in public universities. However, even here, coverage was not universal reflecting Ghana\u0026rsquo;s fragmented health financing landscape.\u003c/p\u003e \u003cp\u003eNotably, institutional ties often overlap with private insurance, as seen in the previous section where one-third of insured immigrants relied on private schemes many of which were employer-provided. This suggests that for immigrants, institutional affiliation frequently channels them into private, rather than public, health financing streams.\u003c/p\u003e \u003cp\u003eThus, while institutional ties provide a vital alternative to direct insurance enrollment for both groups, their distribution and reliability are shaped by migration status. For some immigrants, these ties offer robust coverage; for others especially short-term or student migrants they are absent altogether, exacerbating vulnerability. This duality underscores the need for policies that either extend institutional coverage mandates to all educational and employment settings or simplify NHIS access for those without organizational affiliation.\u003c/p\u003e "},{"header":"Conclusion","content":"\u003cp\u003e Ghana\u0026rsquo;s transformation into a regional migration hub demands a reimagining of its health financing architecture one that moves beyond citizen-centric models to embrace the realities of a mobile, diverse population. This study reveals a stark and systemic disparity: while the National Health Insurance Scheme (NHIS) serves as the backbone of health coverage for Ghanaian citizens, international migrants remain largely excluded, with three-quarters never having enrolled in any health insurance scheme. This gap persists despite migrants\u0026rsquo; relatively high levels of education and employment factors that typically function as \u003cem\u003eenabling resources\u003c/em\u003e in Andersen\u0026rsquo;s Behavioral Model.\u003c/p\u003e \u003cp\u003eOur mixed-methods analysis shows that this exclusion is not due to individual choice alone, but stems from structural and informational barriers that operate as \u003cem\u003edisabling conditions\u003c/em\u003e. Immigrants frequently lack awareness of their eligibility for NHIS, encounter analog bureaucratic processes ill-suited to digitally accustomed populations, and rely on transnational or informal care strategies such as self-medication or private clinics that reduce perceived need for local insurance. In contrast, non-migrants who forgo insurance often do so out of low utilization or lack of incentive, not systemic inaccessibility.\u003c/p\u003e \u003cp\u003eFurthermore, the nature of coverage differs profoundly by migration status. Among the insured, one-third of immigrants rely on private insurance, often provided by employers or universities, while 97% of non-migrants are covered by NHIS. This bifurcation points to a de facto two-tiered system: citizens are largely integrated into the public safety net, while many migrants are channelled into privatized, institution-dependent arrangements or left entirely uncovered, as in the case of students from private language institutes.\u003c/p\u003e \u003cp\u003eThese findings challenge the assumption that legal eligibility equates to meaningful access. As Ghana advances toward universal health coverage (UHC), it must confront the policy blind spot that renders non-citizens invisible in health financing design. We therefore recommend:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eCompletely Digitizing NHIS enrollment and verification to align with the expectations of a globally mobile population;\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIntegrating pre-arrival health insurance orientation into visa and admission processes for students and labour migrants;\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eMandating inclusive health coverage policies for all educational and employment institutions hosting international populations; and\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLaunching targeted outreach campaigns in multiple languages to clarify NHIS eligibility and benefits for non-citizens.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eBy reframing migrants not as transient outsiders but as integral participants in Ghana\u0026rsquo;s social and economic fabric, policymakers can transform NHIS from a heavily citizen-oriented scheme into a truly universal system. In doing so, Ghana would not only fulfil its UHC commitments but also set a precedent for inclusive health governance in an increasingly interconnected Africa.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eNHIS\u003c/strong\u003e: National Health Insurance Scheme\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLMIC\u003c/strong\u003es: Low- and Middle-Income Countries\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUHC\u003c/strong\u003e: Universal Health Coverage\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSSNIT\u003c/strong\u003e: Social Security and National Insurance Trust\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCSPro\u003c/strong\u003e: Census and Survey Processing System\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSPSS\u003c/strong\u003e: Statistical Package for the Social Sciences\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received ethical approval from the University of Ghana’s Ethics Committee for the Humanities (Reference: ECH 191/17–18). All participants provided voluntary informed consent prior to participation. The study was also conducted following ethical standards in social science and received approval from the University of Ghana’s ethics committee for the Humanities (reference ECH 191/17-18). Its upheld core ethical principles, including voluntary informed consent, confidentiality, respect for participants' autonomy, and data protection. The research adhered to international best practices for non-biomedical studies involving human participants. Although the Declaration of Helsinki primarily governs medical research, the study’s ethical approach is consistent with the fundamental values of participant welfare and ethical oversight\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. The manuscript contains no individually identifiable data or images requiring specific participant consent for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed during this study are not publicly available due to confidentiality and ethical restrictions but may be made available from the corresponding author on reasonable request and with appropriate ethical clearance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no financial, personal, professional, or other relationships that could inappropriately influence or be perceived to influence the work reported in this manuscript. Dr. Alberta Teye Agudey and Prof. Margaret Delali Badasu affirm that there are no competing interests related to employment, consultancy, patents, products in development, or marketed products that pertain to this study. The research was conducted independently, without involvement from insurance providers, government agencies, or private institutions that might benefit from the findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was conducted as part of the author’s self-funded PhD program. While tuition fees were borne personally by the author, partial financial support was provided through a part-time Graduate Assistantship awarded by the Centre for Migration Studies, and the College of Humanities (University of Ghana). The assistantship contributed to modest research-related expenses but did not influence the study design, data collection, analysis, interpretation, or manuscript preparation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr. Alberta Teye Agudey: Conceptualization, methodology, data collection, formal analysis, writing the original draft, project administration.\u003c/p\u003e\n\u003cp\u003eProf. Margaret Delali Badasu: Supervision, critical review, theoretical framing, writing review \u0026amp; editing, validation. Both authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all the participants (both immigrants and Ghanaians) in the study areas. We, the authors, are grateful for the participants' generosity in sharing their time and experiences. We also acknowledge the support of the Centre for Migration Studies and the Regional Institute for Population Studies at the University of Ghana. Special thanks to the field assistants George FiiFi Botchway and Beula Esther Sunday. We are also thankful to research mentors Professor Joseph Kofi Teye and Professor John K. Anarfi, who contributed to the successful execution of this study.\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdu-Boahene, A. B., \u0026amp; Dapaah-Afriyie, K. (2017). Health-needs assessment for West African immigrants in Greater Providence, RI. \u003cem\u003eRhode Island Medical Journal, 100\u003c/em\u003e(1), 47\u0026ndash;49.\u003c/li\u003e\n\u003cli\u003eAndersen, R. M. (1968). \u003cem\u003eA behavioral model of families\u0026rsquo; use of health services\u003c/em\u003e. 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A., \u0026amp; Falkingham, J. (2018). Does insurance enrolment increase healthcare utilisation among rural-dwelling older adults? Evidence from the National Health Insurance Scheme in Ghana. \u003cem\u003eBMJ Global Health, 3\u003c/em\u003e(1), e000590. https://doi.org/10.1136/bmjgh-2017-000590\u003c/li\u003e\n\u003cli\u003eWassink, J. (2018). Uninsured migrants: Health insurance coverage and access to care among Mexican return migrants. \u003cem\u003eDemographic Research, 38\u003c/em\u003e, Article 37. https://doi.org/10.4054/DemRes.2018.38.37\u003c/li\u003e\n\u003cli\u003eWitter, S., Arhinful, D. K., Kusi, A., \u0026amp; Zakariah-Akoto, S. (2007). The experience of Ghana in implementing a user fee exemption policy to provide free delivery care. \u003cem\u003eReproductive Health Matters, 15\u003c/em\u003e(30), 61\u0026ndash;71. https://doi.org/10.1016/S0968-8080(07)30332-4\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. (2000). \u003cem\u003eThe world health report 2000: Health systems\u0026mdash;Improving performance\u003c/em\u003e. WHO.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"6242c00d-059e-4a0e-aace-c3b7ad4305ea","identifier":"10.13039/501100005601","name":"University of Ghana","awardNumber":"ID: 10207259","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Ghana Centre for Migration Studies","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Health Coverage, Health Insurance, Immigrants, Non-migrants, Health Financing","lastPublishedDoi":"10.21203/rs.3.rs-8866865/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8866865/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs Ghana transitioned into a key destination for international migrants, understanding the health coverage landscape for this growing population is increasingly vital; Particularly in the context of global health crises. Using an explanatory sequential mixed method design, this study investigated disparities in health insurance coverage between 116 immigrants and 116 non-migrants in Ghana.\u003c/p\u003e \u003cp\u003eThe quantitative result revealed that, only 41.4% of all the respondents were registered with a health insurance scheme in Ghana with a stark gap by migration status: 75% of immigrants had never enrolled, compared to just 7.8% of non-migrants. Among the insured, the National Health Insurance Scheme (NHIS) was the dominant provider (88.5%).\u003c/p\u003e \u003cp\u003eQualitative insights further explain low enrolment among immigrants, citing limited knowledge of NHIS registration procedures, reliance on self-medication, and aversion to Ghana\u0026rsquo;s paper- and card-based insurance system particularly among digitally oriented migrants accustomed to electronic health platforms. The study identifies these factors as structural and informational barriers that function as disabling conditions within Andersen\u0026rsquo;s Behavioural Model of Health Services Use. We recommend that Ghana\u0026rsquo;s National Health Insurance Authority fully transition toward a digital, user-friendly enrolment and verification system and integrate pre-arrival health insurance orientation into visa processing for prospective immigrants. Such reforms could significantly improve equitable access to care in an increasingly mobile society.\u003c/p\u003e","manuscriptTitle":"Health Coverage in a Migration Hub: Comparing Insurance Access Among Immigrants and Ghanaians","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-16 08:11:34","doi":"10.21203/rs.3.rs-8866865/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cd50ee8f-6d0d-4c08-99f7-4997d12235bb","owner":[],"postedDate":"February 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":62848777,"name":"Health Policy"}],"tags":[],"updatedAt":"2026-02-16T08:11:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-16 08:11:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8866865","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8866865","identity":"rs-8866865","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}