The Effect of Health Insurance on Healthcare Access in Pregnant Women. (Case Study of Mengo Hospital)

THE EFFECT OF HEALTH INSURANCE ON HEALTHCARE ACCESS IN PREGNANT WOMEN. (CASE STUDY OF MENGO HOSPITAL)

BY RONAH MUSIIMA REG: 2016/HD06/993U B. COM MAKERERE UNIVERSITY

A RESEARCH REPORT SUBMITTED TO THE SCHOOL OF ECONOMICS, IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF A MASTER OF ARTS DEGREE IN ECONOMIC POLICY AND PLANNING OF MAKERERE UNIVERSITY

DECEMBER 2018

Dedication

To my Mother Alice Debora Byenkya, my brothers Raymond & Solomon, Sisters Racheal, Rhoda, Shella, Joan, Jose, Esther, Michelle Nephew and Niece Jeriel & Jolah, Aunt Justine and friends. “Everyday until my life withers”

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Acknowledgement

I want to take this opportunity to thank my University supervisor Dr Edward Bbaale for the tireless endeavors and guidance. Without your academic and moral support, this work could be far from completion. I also acknowledge the cordial relationship with Mengo Hospital Maternity Department Staff who availed the necessary data that made this work possible. I also acknowledge the contribution of my brother Raymond with whose assistance I managed to enter and analyze the data.

Abbreviations and acronyms

ANC Antenatal care

ASPR Annual Sector Performance Report

CBHI Community based health insurance

DV Dependent Variable

GoU Government of Uganda

IV Independent Variable

LH Life-health

MOH Ministry of Health

NDP National Development Plan

NHI National Health Insurance

NHIF National Health Insurance Fund

NSHIS National Social Health Insurance Scheme

UBOS Uganda Bureau of Statistics

UHC Universal health coverage

UIA Uganda Insurers Association

UNICEF United Nations International Children's Emergency Fund

WHO World Health Organization

Abstract

Uganda’s maternal mortality rate is 336 deaths per 100.000 live births, making it among the highest in Africa and this is partly due to lack of access to maternal health care. Although health insurance is said to improve maternal healthcare access, it has partially been embraced in Uganda. This study sought to investigate the effect of health insurance on access to healthcare for pregnant women in Uganda. Secondary data from Mengo Hospital Maternity Department on pregnant women was used. Bivariate and Ordinary Least Squares regression techniques were used during the analysis. The results revealed that health insurance increases the access to healthcare for pregnant women in Uganda. Employment, education and residence also had a significant effect on access of healthcare for pregnant women. It is therefore recommended that the Government designs strategies to increase health insurance uptake in order to increase access to healthcare for pregnant women. Health insurance coverage should also be extended to the rural areas to increase access to healthcare. Furthermore, women should be encouraged to pursue education to at least the secondary level since both employment and education improve their use of maternal healthcare services.

TABLE OF CONTENTS Dedication ...... iii Acknowledgement ...... iv Abbreviations and acronyms ...... v Abstract ...... vi List of figures ...... ix List of tables...... x CHAPTER ONE ...... 1 INTRODUCTION ...... 1 1.0 Background of the study...... 1 1.1 Statement of the problem ...... 4 1.2 General Objective ...... 4 1.2.1 Hypothesis ...... 4 1.3 Significance of the study ...... 4 1.4 Scope of the study ...... 5 1.5 Organization of the report...... 6 CHAPTER TWO ...... 7 LITERATURE REVIEW ...... 7 2.0 Introduction ...... 7 2.1 Theoretical literature ...... 7 2.2 Empirical literature ...... 9 2.3 Health access ...... 9 2.4 Health insurance ...... 9 2.5 Global Health Insurance and access ...... 10 2.6 Health insurance and access in Africa ...... 11 2.7 Health insurance and access to maternity care in Uganda...... 12 2.8 Literature gaps ...... 13 CHAPTER THREE ...... 14 RESEARCH METHODOLOGY ...... 14 3.0 Introduction ...... 14 3.1 Research Design ...... 14 3.2 Study population and sample size ...... 14

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3.3 Data source/type ...... 14 3.4 Data Analysis ...... 14 3.5 Econometric model ...... 15 3.6 Data presentation ...... 15 3.7 Variable description and measurement ...... 16 3.7.1 The independent variables ...... 16 3.7.2 The Dependent variable ...... 16 3.8 Ethical Considerations ...... 16 CHAPTER FOUR ...... 17 DATA PRESENTATION, INTERPRETATION AND DISCUSSION OF FINDINGS...... 17 4.0 Introduction ...... 17 4.1 Age of pregnant women ...... 17 4.2 Marital status ...... 19 4.3 Education level ...... 21 4.4 Employment ...... 24 4.5 Residence ...... 27 4.6 Health insurance ...... 28 4.7 Health care access ...... 30 4.8 Multiple linear regression ...... 31 4.9 Chapter Summary ...... 34 CHAPTER FIVE ...... 35 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS ...... 35 5.0 Introduction ...... 35 5.1 Summary of findings ...... 35 5.2 Conclusions ...... 36 5.3 Recommendations ...... 36 5.4 Area of future research...... 38 References ...... 39

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List of figures

Figure 4.1 Ages of women with insurance ...... 18

Figure 4.2 Ages of women and health care ...... 19

Figure 4.3 Marital status of women ...... 20

Figure 4.4 Marital status of women and access ...... 21

Figure 4.5 Education of women ...... 22

Figures 4.6 Education of women with insurance ...... 23

Figure 4.7 Employment of women ...... 24

Figure 4.8 Employment of women and insurance ...... 26

Figure 4.9 Insurance among pregnant women ...... 29

List of tables

Table 3.1 Description of explanatory variables ...... 16

Table 4.1 Age ...... 17

Table 4.2 Marital status ...... 20

Table 4.3 Education and ANC visits ...... 24

Table 4. 4 Employment and ANC visits ...... 27

Table 4.5 Residence of pregnant women ...... 28

Table 4.6 Residence and ANC visits ...... 28

Table 4.7 Health access to maternity care ...... 30

Table 4.8 ANOVA ...... 31

Table 4.9 Multiple linear regression ...... 31

CHAPTER ONE

INTRODUCTION

1.0 Background of the study The idea of National Health Insurance (NHI) has its roots in Germany with world's oldest national social health insurance system, and arguably traced to Otto von Bismarck's Sickness Insurance Law of 18831 (Leichter,1979). In recent times, with the exception of the US, all developed countries have universal health coverage for their own citizens through their primary insurance programs. Insurance coverage approaches are 100% of the population in Canada, Germany, Japan, and Singapore (Wenjuan, 2017). There is also evidence that some African countries like Ghana, Tanzania, Kenya, Rwanda and Ethiopia, although dealing with discontent from the public over exorbitant healthcare fees charged by health sector providers, have introduced social health insurance schemes as a way to ensure access to all income groups, especially the poor. Ghana, Tanzania and Kenya have similar social health programmes, although their target groups differ. However, even with these insurance programmes, these countries still struggle with low health access and utilization (Acharya, 2012; Vega, 2015; Maria-Luisa, 2001).

The World Health Organization (WHO) prioritizes Universal health coverage (UHC) as one of the possible umbrella goals for health in the post-2015 development agenda (Vega, 2015; Bump, 2010; Benjamin, 2018). Scholars Ensor, (2004), Gulliford, (2002) observe that ensuring healthy lives and promoting wellbeing for all at all ages is one of the major goals with focus on reducing the global maternal mortality ratio to less than 70 per 100 000 live births. Antenatal care (ANC) has been a valuable tool in reducing maternal deaths through; early identification and

1 The Sickness Insurance Law came into effect in December 1884. It provided for compulsory participation by all industrial wage earners (i.e., manual laborers) in factories, ironworks, mines, shipbuilding yards, and similar workplaces (Leichter and Howard, 1979).

management of diseases, complications such as pre-eclampsia, and intermittent preventive treatment for malaria during pregnancy. Countless families worldwide continue to suffer undue financial hardship as a result of receiving the health care that they need. Kutzin, (2013), Maruthappu, (2016), Michael, (2016:5) note that the UHC is a unified concept and efforts in this area focus on two issues: “catastrophic spending on health”, which is out-of-pocket spending (without reimbursement by a third party) exceeding a household’s ability to pay; and impoverishing spending on health. Caxton, (2017), Bump, (2010) Harris (2011) argue that healthcare insurance schemes are aimed at ensuring that all people have access to needed health services including prevention, promotion, treatment, rehabilitation and palliation of sufficient quality to be effective while also ensuring that the use of these services does not expose the user the financial hardship and yet (Global Health, 2017) reports indicate that one billion people across the globe have no access to adequate health services.

Mathauer, (2008), Kagumire, (2009), Andrea (2017) contend that despite the clear UHC objectives, its implementation has not been universal. In the 2001 Abuja Declaration2, African countries pledged to allocate 15% or more of national budgets to health, however, majority of these countries have failed to implement this declaration and Uganda like many African countries still has no universal coverage or national insurance policy. Majority of these countries continue to face a range of healthcare challenges, from rising numbers of patients with multiple chronic diseases to ageing population. However, Kagumire, (2009) observes that despite these challenges, some African countries have made progress in regards to social health programs, for example, Tanzania, Ghana, Senegal and Uganda.

Beksinska (2006) notes that every day, approximately 830 women die from preventable causes related to pregnancy and childbirth, 99% of all maternal deaths occur in developing countries and this is widely related to insufficient access to health workers and facilities. Uganda is one of the countries in sub-Saharan Africa with high maternal and neonatal morbidity and mortality rates (Kiwuwa, 2008) and prevalence rates higher in rural areas. According to Ensor, (2004),

2 In April 2001, heads of state of African Union countries met and pledged to set a target of allocating at least 15% of their annual budget to improve the health sector. At the same time, they urged donor countries to "fulfil the yet to be met target of 0.7% of their GNP as official Development Assistance (ODA) to developing countries". This drew attention to the shortage of resources necessary to improve health in low income settings.

Dagne, (2010), to receive adequate health care, rural women in Africa and some few urban residents, have to travel long distances, wait in long queues before being assisted by health care personnel who are often disrespectful and show a non-caring attitude. Women in rural settings tend to use maternal health services far less than women in urban settings. Pacific Prime (2018) reports indicate that overwhelming majority of Ugandans do not have access to healthcare. The Center for Health Market innovations3, states that Uganda intended to implement a National Health Insurance Fund for all residents to improve access to healthcare and service utilization. The initial plan was to cover around 2 million employed Ugandans (6% of the population) including 300,000 government workers and then transition to cover other voluntary members. The National Social Health Insurance Scheme (NSHIS) was expected to commence in 2007 but was tabled before the Parliament of Uganda 2009. However, the National Health Insurance Fund (NHIF) failed to make it to through the parliament because of resistance from employers, trade unions and worker representatives (Kagumire, 2009).

In Uganda, maternity studies; Bbaale & Guloba, (2011), Bbaale, (2011) partially address the effect of health insurance on the health care access for pregnant women. It is imperative that health sector stakeholders are stirred to understanding the effect of health insurance on access with empirical evidence to guide policy formulation and advocacy. Well as Similar to study findings elsewhere; religion, occupation, parity and education level, place of ANC attendance, and place of delivery affect access to maternity care (Kawungezi, P., et al., 2015), there is still no empirical evidence on the association between health insurance and access to maternity care in Uganda. The study, therefore, sought to fill this gap by providing answers to the following pertinent question: Does the attainment of health insurance affect the number of antenatal visits? The Literature presents various explanatory factors that help in establishing the relationship between health insurance and access to health care for pregnant women in Uganda. This literature survey informed our choice of variables used during the analysis. Furthermore, it exposed the fact that there had so far been no empirical study in Uganda on the effect of health insurance on access for pregnant women.

3 CHMI collaborates with a global network of country-based organizations. This international network acts as a facilitator of key local and regional actors, carrying out the dual role of connecting promising programs to opportunities and encouraging system-level change. CHMI's most recent partners were based in India, Kenya, Nigeria, Pakistan, and South Africa https://healthmarketinnovations.org/content/our-network accessed 2rd August 2018.

1.1 Statement of the problem

The effect of health insurance in low-and-middle-income countries with regard to healthcare access for pregnant women has partially been documented. Uganda like many African countries still has no national insurance policy. Government of Uganda (GoU) initiatives to improve health service delivery in Uganda have paid little attention to the quality of healthcare access issues for pregnant women. Maternal mortality rate in Uganda remains high, due to in part a lack of access to maternal health care. In an attempt to increase access to antenatal care, quasi- experimental trials like using vouchers were implemented in Uganda. Whereas such interventions are able to positively address instant access barriers, such as lack of financial resources and transportation, they are heavily reliant on external resources and hence are not sustainable. They also fail to address the core causes contributing to women’s lack of access, including the unavailability of incentives such as health insurance. In Uganda today, there is currently no empirical study on health care insurance and access to health care for pregnant women in Uganda. The basis of this research is therefore to investigate the effect health insurance on access to healthcare among pregnant women in Uganda.

1.2 General Objective The main objective of this study is to investigate the effect of health insurance on healthcare access of pregnant women specifically the number of ANC visits.

1.2.1 Hypothesis Ha: Health insurance increases the number of ANC visits for pregnant women in Uganda.

1.3 Significance of the study Many scholars (Ernst, 2012; Beksinska, 2006; Kutzin, 2013) largely focus on the effect of health insurance on healthcare utilization. Wenjuan, (2017) emphasizes that health insurance is habitually assessed in terms of improvements in health care utilization, financial protection, and health status. Little attention has been attuned to the effect of healthcare insurance on the access

of healthcare for pregnant women. The research will add knowledge to existing literature on the subject.

Prior studies Aaron et al, (2017) Sommers, (2017, 2018), Watson, (2017). show that the coverage extension is associated with satisfactory changes in access to medical care, financial security, and in some studies (Schlesinger,2017) improved health. Although studies have shown that uptake of health insurance care can improve health care utilization and access, the study examined whether – and, if so, how – health insurance would affect the number of ANC visits for women in Uganda.

The academic debates in Ssengooba, (2010), Leichter, (1979) Uganda Insurers Association, UIA, (2016) and UNICEF (2008) view the absence of ample health insurance arrangements as an impediment towards ensuring access to needed health care. The protagonist (Leichter, 1979) argues that this exposes many pregnant women to the risk of catastrophic out-of-pocket payments in the event of illness. While statistics from UIA (2016) indicate that existing community health insurance schemes cover about 1% of the population while the private commercial health insurance equally covers a very small segment, this research seeks further the debate with the view that health insurance as a health financing intervention can improve access, especially among pregnant women hence the utilization and uptake of services, are low cost.

1.4 Scope of the study

Subject Scope; The study focuses on understanding the effect of health insurance on healthcare access. The aim is to investigate the association between health insurance and access to maternal health care among pregnant women in Uganda. Geographical Scope: Geographically, the study was carried out in Kampala District because it constitutes majority of the population that is covered by insurance since Uganda currently runs on private insurance and has no national insurance coverage. Mengo hospital is the oldest health facility in Uganda and is strategically located within the urban center where most insurance users reside. It has both the private and general maternity wards which offer antenatal, delivery and postnatal care and other pregnancy related issues. Many pregnant women visit due to the specialized obstetric services offered by

the hospital hence giving a wide mix of patients of diverse age and socioeconomic status and in theory provides a balance of supply and demand. Furthermore, the facility has substantial data and records on pregnant women. Time Scope: The study will mainly cover a period of one year that is 2017 – 2018. Within this period secondary data sets will be analyzed and interpreted to draw conclusions and recommendations in regards to health insurance and healthcare access among pregnant women in Uganda.

1.5 Organization of the report. The report is organized in five chapters. Chapter one included the background of the study, statement of the problem, objectives, hypothesis, significance of the study and the scope of the study. Chapter two reviewed secondary literature from books, journals, articles and internet on the variable. It also reviewed the theoretical approaches that related to the dependent and independent variable. Chapter three discussed the research methods and the instruments used by the researcher to carry out the research. It provided a description of the research design, data collection and analysis procedures. Chapter four revealed data that was analyzed to examine the effect of health insurance on access to healthcare. The data was analyzed statistically using STATA. The detailed findings and analysis were made and illustrated using tables, charts and graphs from STATA. Chapter five provided the summary, conclusions and recommendations derived from the findings of the study in chapter four. These findings will provide a basis for uptake of health insurance, increase in access to ANC, ANC provision, and ANC services utilization in Uganda.

CHAPTER TWO LITERATURE REVIEW 2.0 Introduction This chapter covers the facts and other information generated by other researchers and scholars in regards health insurance and access to healthcare for pregnant women. The work constitutes theoretical and empirical literature.

2.1 Theoretical literature The theory of Behavior Economics; Behavioral economics integrates the study of psychology into the investigation of the decision-making behind an economic outcome, such as the factors that influence a consumer to purchase one product instead of another. Different from the field of classical economics, in which decision-making is totally based on logic, behavioral economics permits for irrational behavior and attempts to appreciate why this may be the case. Francesco, (2004) Mathis, (2007) note that empirical knowledge attained by social psychologists from experiments and field studies partly refute rational choice theory. The initial fundamental criticism is directed against the assumption of rational behavior was as early as the 1970 by (Herbert, 1979:51) who stated that “there can no longer be any doubt that the micro assumptions of the theory. The assumptions of perfect rationality are contrary to fact. It is not a question of approximation; they do not even remotely describe the processes that human beings use for making decisions in complex situations” While calling to question the theory of self-interest (Fehr, 2002; Gintis, 2005) have attempted to explain how social, economic and legal conditions influence the tendency to engage in reciprocal conduct i.e. providing mutual satisfaction.

Liebman, (2008) affirms that the behavioral revolution in economics has established that human beings often have trouble making wise choices. The most widely reported difficulties arise for decisions made under conditions of uncertainty. Decisions whose consequences unfold over significant amounts of time, and those made in multifaceted environments. These are precisely the basics involved when individuals choose a health insurance policy or decide whether to consume health care services. Kahneman, (1979), observes that human decisions are not always optimal. The willingness to take risks is influenced by the means in which choices are constituted, i.e. prospect theory. This is a behavioral model that expression how people choose

between alternatives that involve risk and uncertainty. It reveals that people think in terms of expected utility relative to a reference point rather than absolute outcomes (Fehr 2002).

The traditional economic models of insurance are insufficient for directing policy analysis of the coverage involved in giving consumers better responsibility for making health care choices. Studies by Joseph, (2006), Michael, (2007) specify that the traditional models need to be complemented with key concepts from behavioral economics. The distinctive analysis that views the design of an optimal health insurance program as setting the accurate coverage between risk spreading and appropriate incentives captures not current realities in health care and humans’ abilities to make rational decisions. Certainly, the argument of this study provides much more than the normative justification for many of the features of Uganda’s existing health care policies. If this argument is valid, the logical implication is that, because of these justifications, behavioral economics features are not well understood and many current health care policies are poorly designed in Uganda.

Governments make decisions (policies) that directly impact maternity outcomes. These decisions can be influenced by many factors, including social norms, myths and misinformation, impulsivity and procrastination. These policies largely account for women’s deaths during and following childbirth (WHO, 2014). Further women suffer physical or mental disabilities as a result of complications from pregnancy. The majority of these deaths and disabilities could be prevented with basic orientation with behavioral economics principles. Behavioral economics allows policymakers to understand how and when to intervene, for example when an individual’s biased decision-making affects the maternity health and welfare of others. It provides useful insights in situations where individuals make decisions that are not in their own best interest. Behavioral concepts could be leveraged to promote maternal and child health that is through messaging. choice architecture and program tools. Governments can leverage the positive aspects of behavioral economics (social proof) that can guide policy makers with evidence-based knowledge to reduce the maternal mortality rates and improve access to health care for pregnant women.

2.2 Empirical literature

Empirical literature in the study was collected from books and academic journals. The literature was analyzed to generate debate on health insurance and access to health care for pregnant women, and further determine existing research gaps.

2.3 Health access

Health access has been defined as entry into or use of the health care system (Susannah 2017). Health access is the opportunity or ability to obtain health services and benefit from financial risk protection. Health care access is a key topic of debate worldwide and (Andrea, 2017) notes that many countries continue to face a range of healthcare challenges in providing health access. According to Susannah, (2017) nearly 5 billion people across the world lack access to safe and affordable surgical care. This access burden is felt most acutely in low- and middle-income countries where among many health emergencies and needs, untreated birth defects impact individuals’ abilities to pursue education or professional opportunities. Gulliford, (2002) observes that health care access is a multifaceted concept and at least four aspects require evaluation and access is measured in terms of; utilization, affordability, physical accessibility and acceptability of services.

2.4 Health insurance

Health insurance is a contract between a client and the health insurer to cover medical expenses Insurance safeguards the assets of its policyholders by transferring risk from an individual or business to an insurance company (Luisa 2010). Insurance companies act as financial intermediaries in that they invest the premiums they collect for providing this service. According to the insurance information institute4, Life-health (LH) consists mainly of life insurance and annuity products (Hadley 2003). Across the globe, Health insurance is largely offered by private

4 See The Insurance Information Institute ("I.I.I.") is a U.S. industry association which exists "to improve public understanding of insurance – what it does and how it works https://www.iii.org retrieved 22rd August 2018.

health insurance companies and some LH and PC insurers, and in some development countries through government programs. Luisa (2010) notes that the rationale of health insurance is threefold: increase access and use by making health services more affordable, improve health status through increased access and use, and alleviate the financial consequences of ill health by distributing the costs of health care across all members of a risk pool. The costs and benefits related with extending health insurance coverage depend on the extent and exact ways in which health insurance affects the utilization of medical care (Buchmueller, 2005).

2.5 Global Health Insurance and access

Kruk, (2009) notes that each year many people around the world fall into extreme poverty for health reasons. Robinson, (2016) ascends to the view that Universal healthcare is offered in only five countries that is the United Kingdom, France, Japan, Taiwan, and Canada. Unlike these first-world nations, many countries do not have a universal healthcare system that pays for and provides access to healthcare for its citizens (Jamison, 2013). Low financial barriers can stimulate demand for health services and facilitate early case detection (Weissman, 1991). Maruthappu, (2016) expounds on this view stating that UHC protects against economic downturn, with unemployment associated with a lower mortality in UHC countries compared with those without. Apart from the clinical and economic benefits, there also lies a societal benefit in creating a more equitable and just system of health whereby the poor do not bear a disproportionate burden of disease (WHO, 2013).

Pablo, (2014) note that at least half of the world’s population cannot obtain essential health services. And each year, large numbers of households are being pushed into poverty because they must pay for health care out of their own pockets. Gulliford, (2002) notes that Global Access to Healthcare Index to measure how healthcare systems across 60 countries are working to offer solutions to the most pressing healthcare needs of their populations. The Global Access to Healthcare Index looks at access to specific kinds of care, including child and maternal health services, care for patients with infectious diseases and NCDs, access to medicines, and the extent to which there are inequities in access. The healthcare systems domain in the index measures the conditions that allow for good access to effective and relevant healthcare services, such as

policy, institutions and infrastructure. Key findings indicated that political will and a social compact are prerequisites for both access and sustainable health systems. Most of the countries with the highest scores on the index share a political and financial commitment to improving access to healthcare and a strong civil society in which corruption levels are low, accountability is high, and the public expects services to be available for them. “Access and provision [are] determined by the trust that people have in the state. Furthermore, public investment underpins good access and demonstrates the commitment of governments to ensuring the health of their populations.

2.6 Health insurance and access in Africa

Acharya, (2012) extends the view that some African countries, grappling with discontent from the public over exorbitant healthcare fees charged by health sector providers, have introduced social health insurance schemes as a way to ensure access to all income groups, especially the poor. Despite the fact that some African countries have adopted national insurance programs (Ama 2018, Lambert, 2017). Little is known about how these health insurance schemes influence access to healthcare for pregnant women. There is also very little evidence on the impact of health insurance on quality of care and community empowerment, and no definitive conclusions can be drawn in this regard. Further, still in many African countries like Uganda, health insurance coverage rates remain extremely low (Ama P, 2017, Ernst, et al., 2012).

Ludi, (2018) and Ernst, (2012) observe that health care access in Africa remains the worst in the world. To improve access and the delivery of healthcare, the continent needs to leverage digital technologies, improve knowledge, skills and resources, and create channels for collaboration and consensus among key stakeholders (Sulaiman 2017). Many African countries have struggled to provide the most basic care to their citizens. Danwood, (2016) notes that ensuring all citizens equal and equitable access to health care remains one of the most daunting challenges for

African governments. In Kenya, where efforts to expand access to primary care have been plagued by high levels of rural poverty, underdeveloped infrastructure and political violence.5

2.7 Health insurance and access to maternity care in Uganda

Kagumire, (2009) observes that private insurance has been available for about a decade, but only the elite tend to obtain coverage. In Uganda, very few people have insurance. It is estimated that the average Out-Of-Pocket (OOP) health expenditure as a fraction of total expenditure by Ugandans on health is high. According to UBOS, (2012), the Enrollment in health insurance is low in Uganda. Basaza, (2010) observes that the low figures, especially among pregnant women, are primarily due to the lack of basic understanding of scheme design and operations, affordability of premiums, and supply-side issues such as the absence of a coherent policy framework to promote community based health insurance (CBHI) amidst a backdrop of user-fee abolition in the public sector.

Alfonso, (2015) accentuates that most maternal deaths can be prevented with access to quality and skilled antenatal care (ANC), appropriate facilities for deliveries, postnatal care, and family planning. The documented barriers to women’s use of maternal health services in Uganda include transport costs, long distances to health facilities, high service fees, insufficient supplies of drugs and equipment, poor provider training, and poor treatment of patients. In Uganda, various demand side financing interventions have been tried which involve the use of subsidies or vouchers. Ekirapa, (2011) stresses that an evaluation of a maternal health voucher programme operating in both public and private facilities in Uganda showed that voucher revenues were used to obtain supplies to improve quality and to pay health workers. However, such interventions are able to positively address instant access barriers, such as lack of financial resources and transportation, they are heavily reliant on external resources to sustain (Kawungezi et al., 2015; Kanya, 2014;

5 See World Health Organization, Curriculum Vitae: Dr Tedros Adhanom Ghebreyesus: Candidate for Director-General of the World Health Organization Endorsed by the African Union. Viewed on 27th August 2018 http://www.who.int/dg/ election/cv-tedros-en.pdf.

Dennis, 2018). Jaskiewicz, (2016), observes that Uganda's absolute shortage and inadequate geographic distribution of health workers with appropriate skill mix to provide services across the continuum hinders achievement of healthcare access significantly. Konde, (2010) notes that Uganda is at the stage of promoting and even formalizing linkages between public and private health care systems with the aim of improving access to health care. However, knowledge from health insurance providers in regards to maternal health is limited and this (Birungi 2001) observes makes it difficult to guide policy makers to make effective policies.

Demographics and health survey, (2016) depict that median pregnancy related mortality ratio is high. A fraction of women in Uganda deliver in hospitals or a health facility supervised by a midwife. Majority deliver either alone or with the help of a traditional birth attendant. Inadequate access to quality services contributes to high mortality and morbidity rates. Healthcare Insurance is one of the many interventions provided for in the NDP II 2015/16 – 2019/20 plan to improve healthcare (UBOS and ICF, 2017; MOH Annual Sector Performance Report, 2010; UHP, 2010). Despite improvements in maternal mortality, Neonatal mortality remains high in Uganda (world health statistics report, 2015).

2.8 Literature gaps The literature reveals that information from health insurance providers on maternal health is limited in Uganda. Little is known about how these health insurance schemes influence access to healthcare for pregnant women. It further shows that there is currently no empirical study on health care insurance and access to health care for pregnant women in Uganda. There is also no empirical evidence on the impact of health insurance on maternity care access and no definitive conclusions can be drawn in this regard in Uganda. There are both information and policy gaps in Uganda’s health policy as a result of the absence of empirical evidence on the relationship between health insurance and access to ANC. The study denotes facts with evidence-based essence on health insurance and access to ANC specifically ANC visits. This is crucial in guiding government policy design, implementation, monitoring and evaluation.

CHAPTER THREE

RESEARCH METHODOLOGY 3.0 Introduction This section discusses the research methods and the instruments used by the researcher to carry out the research. It provides a description of the research design, data collection and analysis procedures. 3.1 Research Design The research was a quantitative cross sectional study using descriptive and analytical methods. In a cross-sectional study, the study sought to measure the outcomes at the same time. The participants in a cross-sectional study were selected based on the inclusion and exclusion criteria set for the study.

3.2 Study population and sample size The study population was of 660 insured and uninsured women in Mengo Hospital. The study used data from 250 participants in the population because only these participants had all their bio, demographic, ANC visits records well documented. The other participants did not have the required details needed for the study.

3.3 Data source/type The secondary data in this study was from records on pregnant women at Mengo hospital in 2018. The data presents various explanatory factors that help in establishing the effect of health insurance on access to antennal care for pregnant women, that is; age, marital status, level of education, residence, and employment status.

3.4 Data Analysis Data from Mengo hospital maternity records 2018 was quantitatively analyzed. Bivariate and OLS techniques were used to describe the features the data set by giving short summaries about the data respectively. OLS was used because the study estimated that the outcome variable is directly affected by one or more independent variables. Furthermore, number of ANC visits is continuous therefore the use of OLS helped examine the complex relationships between variables progressively.

3.5 Econometric model The study covered cross-sectional datasets. The main purpose of linear regression analysis is to assess associations between dependent and independent variables. The variables Yi (dependent variable) and Xi (independent variable) are two variables representing the population and the study is interested in explaining Yi in terms of Xi and studying how Yi varies with changes in Xi.

Multiple linear regression

Y= β0 + β1insi+ β2agei + β3msi + β4educi+ β5resi+ β5emplyi + εi Where: Y Number of ANC visits

β0 constant Ins Insured Age Age of respondent Ms Marital Status of respondent Educ Education of respondent Res Residence of respondent Empy Employment of respondent

εi Error term

3.6 Data presentation The data was presented as tables, graphs, charts. The STATA computer program was used to analyze data. The package enabled a number of variables to be analyzed simultaneously. Information on the sample characteristic was generated using frequencies. The relationship between the dependent and independent variables was tested using multi regression.

3.7 Variable description and measurement 3.7.1 The independent variables Health Insurance viewed in reference to its capability to render insurance coverage for pregnant Women in Uganda. It is measured as: 1: Yes (insured), 0: No (uninsured). The other independent variables include the demographic composition of the sample. These include; age, education level, employment, residence and marital status.

3.7.2 The Dependent variable Healthcare Access is viewed in regards to the number of Antenatal care visits. It is measured as 1,2,3,4 (number of ANCs). Table 3.1 Description of independent variables

IV Description Measurement/ Coding Data type 1 Age (14-25, 26-35, 36 and above) Ordinal 2 Marital status (0= Divorced, 1= Single mother, 3=Married) Nominal 3 Level of education (0=No education, 1=Primary level, 2=secondary Nominal level, and 3= Post-secondary level) 4 Employment (1= Employed, 0= Unemployed) Nominal 5 Residence (1=Urban, 0=Rural) Nominal

3.8 Ethical Considerations The researcher ensured that ethics are observed in the study. The researcher requested for permission through a written communication addressed to the concerned official at Mengo hospital. The researcher also attributed, referenced and cited all literature in the study. Peoples’ health information attained in the study was kept confidentially. The names, contacts, health status of the participants were kept concealed. Furthermore, a non-disclosure agreement was signed with the maternity section to ensure that the data specific sections of the data were not made public (names, contacts, specifics on residence and health status).

CHAPTER FOUR

DATA PRESENTATION, INTERPRETATION AND DISCUSSION OF FINDINGS.

4.0 Introduction In this chapter, the data was analyzed to examine the effect of health insurance on access to healthcare. The data was analyzed statistically by STATA. The detailed findings and analysis were made and illustrated using tables, charts and graphs from STATA.

4.1 Age of pregnant women The ages of the women in the Data were analyzed. Age was considered as a significant aspect of the explanatory variables to better understand the preparedness, responsibility and readiness for maternity. The findings revealed that 60.8% of the women were between the ages of 26 and 35years, 32.8% were between the ages of 14 and 25, and, 6.4% were above 36 years. This finding depicted that majority of the women were in their youthful stages and were well placed to bare the maternity responsibilities. Table 4.1 illustrates the findings further.

Table 4.1 Age

Frequency Percent Cumulative Percent Valid 14-25 82 32.8 32.8 26-35 152 60.8 93.6 36-above 16 6.4 100.0 Total 250 100.0 Source; author’s computations from Mengo hospital Maternity data

The findings also revealed that pregnant women between the ages of 26-35 attained health insurance as compared to those between 14-25years and above 36 years. It was also proven that women between 26-35-year attend more antenatal visits as compared to those below the ages of 25 and 36 years.

Figure 4.1 Ages of women with health insurance

Source; Author’s computations from Mengo hospital Maternity data

The figure above shows that women between the ages of 26-35 attained more health insurance cover compared to their counterparts below the ages of 25 and above 36 years. This is in concert with secondary data from Rutaremwa G, (2016) and Kawungezi P, (2015) that age affects access to antennal care for pregnant women.

Figure 4.2 Ages of women and access to maternity care

Source; Author’s computations from Mengo hospital Maternity data

The findings are justified by other secondary studies Yibeltal, (2015) and Jackson, (2016) that observe that access and utilization of health facilities is high among younger age groups compared to older women. 4.2 Marital status The marital status of women was also statistically analyzed in the study. This was to further understand the variances between the women who had the support of their male counterparts and those without. It was also to further evaluate the significance of this relationship with health insurance and access. The findings revealed that majority of the women were married with 90% statistical finding, 1.6% were divorced and 8.4% were single mothers. This implies that married

women attain more healthcare ANC visits and Insurance compared to the divorced and single mothers. Table 4.2 illustrates the statistical analysis of the marital status. Table 4.2 Marital status

Frequency Percent Cumulative Percent Valid Married 225 90.0 90.0 Divorced 4 1.6 91.6 Single mother 21 8.4 100.0 Total 250 100.0 Source; Author’s computations from Mengo hospital Maternity data

This finding further revealed that married women attained more insurance and accessed ANC compared to the divorced and single mothers. Statistics indicate that 90% on married 1.6% who were divorced and 8.4% were single mothers attained access to maternity care. Figure 4.3 Marital status of women and insurance

Figure 4.4 Marital status of women and access to maternity care (ANC visits)

Source; Mengo hospital Maternity data

The study findings are similar to studies Kawungezi, (2015) and the United Nations, “Report of the International Conference on Population and Development) that women attain maternity care with reasons such as ‘my husband decided’. That male involvement in maternal health care has been described as a process of social and behavioral change that is needed for men to play more responsible roles in MHC with the purpose of ensuring pregnant women’s wellbeing.

4.3 Education level The education level in the data was analyzed. This was crucial in understanding whether the women had an understanding and knowledge on basic health insurance and access to maternity

care. The findings revealed that majority of the women had attained a decent education that is at secondary and post-secondary level with either a degree, diploma, certificate. This majority was represented by 41.2%, post-secondary, 54.8% had secondary level education, 1.2% attained primary education and 2.8% had no education. The finding further cemented the validity of the sample because the elements in the study had attained decent education that enabled them to have clear understanding of the variables. Figure 4.5 Education of women

Source; Mengo hospital Maternity data

The study also investigated how education history effected insurance and access to antenatal care. The findings indicated that majority of the women with insurance were either post- secondary or had attained secondary level education. This is the group with descent jobs, incomes that had more insurance cover. None of the women with primary education and those with no education had insurance. This indicated that insurance among pregnant women is more

attained by the educated women as compared to those with minimal (primary level) or no education. This is because this group had not sufficient knowledge on insurance and had low incomes. The findings further revealed that the educated women (Post-secondary and secondary education level) attained more antenatal visits as compared to those that had minimal (Primary level) and no education. Figures 4.6 Education of women with insurance

Source; Mengo hospital Maternity data

Table 4.3 Education * ANC visits

ANC visits 1-2 2-4 4-6 6-8 and more Total Education Graduate 51 33 18 1 103 Secondary 38 87 12 0 137 Primary 0 1 2 0 3 No education 3 2 2 0 7 Total 92 123 34 1 250 Source; Author’s computations from Mengo hospital Maternity data

The study findings are similar to studies Rutaremwa, (2015), and Bbaale, (2011) that state that women with secondary and higher education were more likely to utilize the desirable maternal health care package compared to those who had none. The level of education was equally found to influence ANC attendance, number of ANC visits and booking time.

4.4 Employment The employment of the women was also analyzed. It was important to assess whether employment would have an effect on attaining insurance cover and access to antenatal care for women. The findings revealed that majority of the women had a formal or informal job. It also revealed that the women who were employed attained more antenatal visits. The statistical findings indicated that 75.6% of the women were employed and 24.4% were unemployed.

Figure 4.7 Employment of women

Source; Mengo hospital Maternity data

The study further investigated the insurance and access to antenatal care among pregnant women. The findings revealed that majority of employed women were insured compared to the unemployed women. The findings further revealed that employed accessed more ANC visits compared to those with no employment. The statistical data indicated that among the 99% of women with insurance were employed, 99% of unemployed were insured. This indicated that the presence or absence of employment affects the attainment of insurance for pregnant women in Uganda.

Figure 4.8 Employment of women and insurance

Source; Mengo hospital Maternity data

The findings indicated that women who had a job were in position to afford healthcare insurance. This was a depiction that health insurance was affordable to women who were in position to generate income. On the other hand, women with no employment cannot afford healthcare insurance as depicted in the finding.

Table 4. 4 Employment * ANC visits

ANC visits

1-2 3-4 5-6 8 and more Total Employment Employed 77 84 27 1 189

Unemployed 15 39 7 0 61 Total 92 123 34 1 250 Source; Author’s computations from Mengo hospital Maternity data

Earlier studies Bbaale, (2011, 2011b) on Factors influencing timing and frequency of antenatal care in Uganda and Factors influencing the utilization of antenatal care content in Uganda both state similar findings with the study. Education of the mother, wealth status is significantly associated with ANC visits. However, these studies don’t make mention that the employment status of pregnant women influences their attainment of health insurance, a finding that has be depicted in this study.

4.5 Residence The data was analyzed to establish the residence of the women. The location of these women was indicated to establish the ease with which they were able to access healthcare. The findings indicated that majority of the women were from urban areas. The statistics revealed that 80.8% of the women resided in urban areas while 19.2% were from rural areas. Case summaries revealed that majority of women in urban centers had ease access to healthcare because their composition on ANC visits were higher than their counterparts in rural areas. The table 4.4 indicates the residence distribution of the women. Sou Table 4.5 Residence of pregnant women rce ; Frequency Percent Cumulative Percent Aut Valid Urban 202 80.8 80.8 hor Rural 48 19.2 100.0 ’s Total 250 100.0 co mputations from Mengo hospital Maternity data

The study also sought to find out how the location of the women affected their access to health care and influenced their insurance attained. The findings revealed that women in urban centers had more insurance compared to those in rural areas. The findings further indicated that women in urban centers attained more ANC visits compared to the women in rural areas. Among the women that were found to be insured, 90.4% women live in urban centers while only 9.6% women reside in rural areas.

Table 4.5 Residence of pregnant women

Insurance Insured Not insured Total Residence urban 76 126 202 Rural 8 40 48 Total 84 166 250 Source; Author’s computations from Mengo hospital Maternity data

Table 4.6 Residence * ANC visits

ANC visits 1-2 3-4 5-6 8 and more Total Residenc urban 81 92 28 1 202 e Rural 11 31 6 0 48 Total 92 123 34 1 250 Source; Author’s computations from Mengo hospital Maternity data

Previous studies Cherniak, (2017), Okonofua, (2018) agree with the study findings that most of the rural women practiced inadequate ANC. They unanimously conclude that women in urban centers attained more ANC visits compared to the women in rural areas a finding stated in this study. However, these studies make little or no mention at all on how the residence of pregnant women effect their insurance decisions: a finding observed in this study that women in urban centers are more likely to attain health insurance compare to their counterparts in rural areas in Uganda.

4.6 Health insurance The data was also analyzed to establish the number of insured women. The findings indicated that the minority of women in the data sets were insured. The statistical findings depicted that

only 33.6% women were insured. Majority of the women 66.4% of women were uninsured. This depicted that there were low rates of insurance among pregnant women. Figure 4.9 Insurance among pregnant women

Source; Mengo hospital Maternity data

Earlier studies on health insurance justify the findings of the study. Kagumire, (2009) argues that households pay too great a share of the costs of maternal health services, or do not seek insurance because they cannot afford the costs. Others studies Wang, (2017) note that enrollment in health insurance increases the probability of using general health care in various settings. The fact that maternal and child health services are typically covered in health insurance benefit packages attests to these findings that insurance increases the attainment of antennal care.

4.7 Health care access The data was analyzed to establish the access to healthcare for pregnant women. The standard measure for this variable were the number of ANC visits and the residence of the women. Statistical findings indicated that majority of the women had attended between 1-2 ANC visits with a 36.8%, 49.2% had attained 3-4 visits, 13.6% attained 5-6 visits and 4% attained 8 and more ANC visits. This indicated that there was commitment by pregnant women to visit the hospital for maternal. It further indicated that majority of the women who have access to maternity care attend a minimum of 1 and maximum of 4 ANC visits. Table 4.7 Health access to maternity care. ( ANC visits)

Number of ANC visits Frequency Percent Cumulative Percent Valid 1-2 92 36.8 36.8 3-4 123 49.2 86.0 5-6 34 13.6 99.6 8 and more 1 .4 100.0 Total 250 100.0 source; Author’s computations from Mengo hospital Maternity data

Mrisho (2012) attests to the finding in this study stating that despite its reduction over the last decade, the maternal mortality rate in Uganda remains high, due to in part a lack of access to maternal health care. Studies (Cherniak, 2017 and Okonofua, 2018) also affirm that women in urban areas attain for ANC compared to rural areas.

4.8 Multiple linear regression

A bivariate linear regression analysis was done to investigate the association between the dependent, independent and explanatory variables that is access to antenatal care; health insurance; and age, marital status, education, employment, and residence respectively. The findings are explained by the R square, P values, t values and ANOVA as illustrated below; Table 4.9 Multiple linear regression. ANC visits Coef. Std. Err. t P>|t| [95% Interval] Conf. Age 14-25 .1986042 .1641949 1.21 0.228 -.1248498 .5220582 26-35 .5794502 .4520034 1.28 0.201 -.310969 1.469869 36-above*** Marital status Married .2028729 .1647436 1.23 0.174 -.121662 .5274079 Divorced .6175508 .4524621 1.36 0.219 -.2737721 1.508874 Single mother*** Employment Employed .0575334 .1229647 0.47 0.023 -.2997665 -.1846996 Unemployed *** Education Post-secondary .12708 .2986868 0.43 0.005 -.7154748 -.4613149 Secondary .0378143 .2848985 0.13 0.030 -.5990471 -.5234184 Primary .3522125 .5612178 0.63 0.008 -.7533525 -1.457778 No education*** Insurance Insured 1.205854 .1761352 0.085 0.024 .1412843 .2463361 Non Insured *** Residence Urban -.040995 .1329773 - 0.31 0.032 -.3029523 -.2209623 Rural *** _cons | 1.856561 .3559191 5.22 0.000 1.155422 2.5577 Number of obs 250 R-squared 0.8764 Adj R-squared 0.8707 Root MSE 68458

ANOVA; (teat using alpha= 0.5) The overall regression was significant because p≥0.05 1.09≥0.05 F (10, 239) =1.09, R square = 87.6%. This means that there is a significant relationship between the predictors and the dependent variable. This also means we accept the hypothesis that is, there is sufficient evidence to conclude that Health insurance increases the number of ANC visits for pregnant women in Uganda.

P> |t|: revealed whether the coefficient had statistically significant effect on the dependent variable or not. Where p value is 0.05 or less, then the coefficient is to be statistically significant. In the data, the p values for;

Employment was statistically significant at 5%. This indicates that employment has an effect on access to healthcare for pregnant women in Uganda. Employed pregnant women are more likely to access health care compared to their unemployed counterparts. Employment affects access to healthcare for pregnant women since the use of the service is associated with the cost of consultation and the purchase of prescribed medication alongside other indirect costs such as transportation cost. Therefore, this study indicates that employed women are more likely to use ANC because she may be able to afford the cost and other expenses that comes with using the service compared to the unemployed. This is in line with previous studies like Bbaale, (2011, 2011b) on Factors influencing timing and frequency of antenatal care in Uganda indicate that education of the mother, wealth status is significantly associated with ANC visits. . This study revealed that education has a statistical significance of 5% on access to healthcare for pregnant women in Uganda. Therefore, there is 95% confidence that education effects the access to healthcare for pregnant women. This indicates the importance of education on health access by pregnant women. Women with post-secondary education are more likely to attain access to health care than those no education. Furthermore, those with secondary education attained more visits than those without education. This indicates that lack of information poses a serious hindrance to the use of maternal health services. The quantitative results show that most women who were educated accessed more maternal health services than those who did not know about the services offered. Studies Rutaremwa, (2015) and Bbaale, (2011) also agree that state education affects the utilization and access to maternal healthcare.

Insurance was significant at 5%. The coefficient was more than one which indicates that for every increase in the dependent variable, there is a likelihood of one addition change in the access of healthcare for pregnant women in Uganda. In other words, the public and private support through insurance in community increases health care access for pregnant women in Uganda. These results support the case for broadening the uptake of health insurance among pregnant women in Uganda offers comprehensive access to maternal healthcare services. Studies Wang, (2017) notes that enrollment in health insurance increases the probability of using general health care in various settings. Therefore, in this study, there is a 95% confidence that insurance effects access of maternity care.

The study also revealed that residence is statistically significant at 5%. This means that residence has an effect on the access of healthcare for pregnant women in Uganda. The pregnant women in the urban areas had more access to health that is attained more antenatal visits compared to those in rural areas. Therefore, in this study, there is a 95% confidence that residence of women has an effects access healthcare for pregnant women. In this study the access to health care for pregnant women in Uganda appears much easier for the urban dwellers than the rural dwellers, thereby increasing the probability of an expectant mother in the urban center using ANC compared to her rural counterpart. This is more likely due to the distance to the health facility and transportation problems one may encounter in accessing health services. Therefore, residing in a rural area can hinder the access to healthcare since the expectant mother may have to travel along bad road networks or may have to travel for long distance before being able to access a health center for ANC. Other studies Cherniak, (2017) and Okonofua, (2018) agree with the study findings that most of the rural women practiced inadequate.

There was no statistical significance between Age and the access to healthcare for pregnant women in the study. The p values for Age p≥0.228 were greater than 0.05 which proved that in this study there a 95% confidence that there is no statistical indication that age has an effect on the access of healthcare for pregnant women in Uganda. However, it can be statistically observed that women between 14-25 years are likely to access healthcare compared to women who are much older. In this study, it was statistically evident that as women grow old they are less likely to attain access to healthcare in Uganda. Health access that is the number of antenatal visits

reduce with increase in age since the older ones are less anxious about the pregnancy as a result of previous experience.

There was no statistical significance between marital status of women and their access to healthcare. Therefore, in this study it which proved that there a 95% confidence that there is no statistical indication that marital status has an effect on the access of healthcare for pregnant women in Uganda. This disputes studies Kawungezi, (2015) and the United Nations, “Report of the International Conference on Population and Development) which suggested that women attain maternity care with reasons such as ‘my husband decided’. It was however observed that married women were more likely to attain access to healthcare than divorced and single mothers.

4.9 Chapter Summary This chapter had an in-depth analysis on data about the effect of health insurance on the access to Antenatal care for pregnant women. The findings formed the basis for the discussion, conclusion, and recommendations in chapter five.

CHAPTER FIVE

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

5.0 Introduction The chapter provides the summary, conclusions and recommendations derived from the findings of the study in chapter four. These findings will provide a basis for uptake of health insurance, increase in access to ANC, ANC provision, and ANC services utilization in Uganda.

5.1 Summary of findings The results of both variable analysis and bivariate regression model established that there is a significant association between health insurance and access to antenatal care for pregnant women in Uganda. It is clear that women with health insurance cover attain more numbers of antenatal visits as compared to those without insurance. The findings of the study further established that there was a significant relationship between the education levels, employment, residence or women, health insurance and access to maternity care. It was established that women who are employed can afford health insurance and consequently attain more ANC visits. It was also ascertained that educated women attained insurance cover and this influenced their access to ANC. It was also established that women who reside in urban centres attain more ANC compared to their counterparts in rural areas.

The results further depicted that there was no significant relationship between age on the attainment of insurance and access to antenatal care. This implies that age ad marital status of women are not good indicators of access to healthcare for pregnant women in Uganda. This disapproves initial suggestions that women who were married were likely to attain more insurance cover and access to ANC. It also nullifies the attempt to suggest that ages of women influence their attainment of health insurance and access to maternal health care in Uganda. However, it was observed that women between 14-25 years are likely to access healthcare compared to women who are much older. In this study, it was statistically evident that as women grow old they are less likely to attain access to healthcare in Uganda.

There was no statistical significance between marital status of women and their access to healthcare. This contested studies Kawungezi, (2015) Moses, (2012) and the United Nations, “Report of the International Conference on Population and Development) which suggested that women attain maternity care with reasons such as ‘my husband decided’. It was however observed that married women were more likely to attain access to healthcare than divorced and single mothers,

5.2 Conclusions Health insurance affects the access to healthcare for women in Uganda. Women who have health insurance covers attain more ANC visits as compared to those without insurance. This revelation proves empirical evidence that there is a significant relationship between health insurance and access to healthcare for pregnant women. Other factors like employment, education levels and residence of women equally affect their attainment of health insurance and subsequently affect their attainment of healthcare for pregnant women in Uganda. It can be substantiated that women in rural areas travel long distances to get healthcare and this is a barrier to maternal health in Uganda. An employed pregnant woman may be able to overcome this barrier easily as compared to an unemployed woman. An educated woman relative to a woman with no formal education may have a better access to health-related information and be more concerned about her health and the health of her unborn baby thereby choosing to deliver in a health facility. It can also be concluded that women with no jobs cannot afford to pay for insurance and consequently this negatively hinders them from frequently attaining healthcare. Pregnant women with a post- secondary level of education are more likely to get health insurance and attend more access to healthcare.

5.3 Recommendations Health insurance positively has an effect on access to healthcare for pregnant women in Uganda. However, there is also little uptake of insurance among pregnant women. This is largely because of the cost of insurance and lack of knowledge and information. It is therefore important that awareness is carried put on the usefulness of insurance and its associated benefits like increasing maternity care. It is equally significant for insurance to be made affordable especially for pregnant women. This can be in form of subsided maternity covers, vouchers, etc. This is likely

to increase the number of women up taking health insurance, and subsequently increase ANC visits hence reduction on maternity mortality rates in Uganda.

There is a need for all stakeholders, government, policy makers, development partners, medical fraternity and civil society to understand the role health insurance can play in increasing healthcare for pregnant women and consequently reducing maternal deaths in Uganda. This understanding can be premised on informed-based decision approaches with empirical findings in this study. Furthermore, exposure to health insurance information is very instrumental in promoting health-seeking behaviour, there is a need for stakeholders to work together with insurance providers to disseminate information on the merits of health insurance especially among pregnant women. Much sensitization and awareness of health insurance have to be done specifically in rural areas to empower pregnant women to improve ANC attendance.

There is a need to improve geographic access to health services. This can be achieved through Community-based Health Planning and Services (CHPS) initiatives with specific attention to pregnant women. This should be coupled with the implementation of either affordable health insurance schemes, National health insurance program or free maternal health care policy in under which pregnant women do not pay user fees to receive ANC health services.

An equity-based health policy approach considering the sociodemographic inequity in terms of wealth index, education and urban–rural divide can prove beneficial in further improving the access to healthcare for pregnant women in Uganda, as well as addressing the possible issues of quality maternal healthcare gaps, which is also likely to be helpful in reducing maternal mortality in Uganda.

In order to improve the access to healthcare for pregnant women in Uganda, stakeholders need to diverse mechanisms necessary to support women within the lowest incomes, like the provision jobs. Furthermore, women should be encouraged to pursue education to at least the secondary level since both employment and education improve their use of maternal healthcare services.

5.4 Area of future research This study sought to investigate whether health insurance affects the access to antenatal care for pregnant women in Uganda. However, it didn’t investigate whether health insurance affects the quality of health care received during ANC visits. If a valid health insurance is associated with health facility delivery, or how expanded maternity access will influence maternity mortality rates in Uganda. Further research needs to be carried out on how attainment of health insurance influences the quality of health care, and how the expansion of access influences maternity mortality in Uganda.

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