A Case for Telehealth: Leveraging the Telehealth Model to Reduce Structural Health System Barriers in Uganda
by Sam Biraro Muhumuza
Bachelor of Statistics, April 1998, Makerere University Kampala Master of Business Administration, May 2006, Pacific Lutheran University Master of Professional Accounting, March 2016, Seattle University
A Praxis submitted to
The Faculty of The School of Engineering and Applied Science of The George Washington University in partial fulfillment of the requirements for the degree of Doctor of Engineering
January 10, 2019
Praxis directed by
Muhammad Islam Professorial Lecturer of Engineering Management and Systems Engineering
John Fossaceca Professorial Lecturer of Engineering Management and Systems Engineering The School of Engineering and Applied Science of The George Washington University
certifies that Sam Biraro Muhumuza has passed the Final Examination for the degree of Doctor of Engineering as of November 27, 2018 defense. This is the final and
approved form of the praxis.
A Case for Telehealth: Leveraging the Telehealth Model to Reduce Structural Health System Barriers in Uganda
Sam Biraro Muhumuza
Praxis Research Committee:
Muhammad Islam, Professorial Lecturer of Engineering Management and Systems Engineering, Praxis Co-Director
John Fossaceca, Professorial Lecturer of Engineering Management and Systems Engineering, Praxis Co-Director
Amir Etemadi, Assistant Professor of Engineering and Applied Science, Committee Member © Copyright 2018 by Sam Biraro Muhumuza All rights reserved Acknowledgements
This doctorate research study would not have been possible without the assistance, sacrifice and contribution of many people. Here, I would like to recognize all those individuals who helped me to get across the finish line. First and foremost, I would like to extend my sincere gratitude to my committee and advisors Dr. Muhammad Islam, Dr.
John Fossaceca, Dr. Amir Etemadi, Dr. Ali Jarvandi, and Dr. Bentz Tozer for their guidance and support during the research phase.
My debt of gratitude to my brother, Simon Jordan Mugisha and sisters, Ellen Biraro
Muwonge, and Esther Biraro Kuteesa for their unending support and encouragement. My cousins, Dr. Sam Jr. Biraro and Irene Biraro Suguya who offered valuable guidance and support. Above all, I am so grateful to my mother Damali Mirembe Biraro who has always been there to support me in ways that I cannot adequately express. My mother not only fostered my thirst for excellence but also provided me all the life lessons necessary to be successful. My father, Ephraim I. Biraro (RIP) who passed on during my formative years as a young man has always been there for me and my siblings in spirit making sure we know what can be accomplished when we embrace the power of consistence and focus. Likewise, my younger brother Steven Biraro Tumusiime (RIP) who also passed on years ago provided a good example of persistence and triumph amidst constraining circumstances. Without my family’s support this praxis would never have been completed. I am indebted to all of them more than they know.
I am so grateful to my wife, Christine (Tina) Asiimwe for her support and encouragement through all my studies, my anxieties of exasperation and for making sure
I never gave up on chasing any of my dreams – you are the enabler of my success and I
iv am deeply indebted for all your help over the years. Along with her, our daughter Faith
Hannah Biraro who was born after I had embarked on my doctoral journey - arriving just in time with much needed heaps of smiles and laughter. I want to dedicate this work to my wife and to our daughter, Faith.
Many friends contributed their valuable time in helping to refine my ideas by offering valuable suggestions and criticisms. More particularly, Dr. Joseph Babigumira, Dr.
Solomon Lubinga, Ms. Cissy Segujja, and Richard Kyabihende provided useful contributions and prodding making sure that I was on the right course.
My doctoral studies were greatly facilitated by my employer, The Boeing Company who paid for my educational expenses including tuition and books. I am indebted to all the men and women who have made Boeing the world’s greatest aerospace company.
v Abstract of Praxis
A Case for Telehealth: Leveraging the Telehealth Model to Reduce Structural Health System Barriers in Uganda
The ease with which members of a community can access health care services is a key
factor in determining the general health status of their bigger community as a whole.
According to the 2018 National Center for Chronic Disease Prevention and Health
Promotion (NCCDPHP), healthy equity is achieved when each individual has the opportunity to achieve their full health potential. Furthermore, the NCCDPHP (2018) states that “Health inequities are reflected in differences in length of life; quality of life; rates of disease, disability, and death; severity of disease; and access to treatment”.
Needless to say, developing effective health solutions necessitates attention to promoting programs that focus on equity, access, knowledge, treatment, distribution of health facilities, placement of health providers, health outcomes, and allocation of resources.
Transportation barriers including the average long distance traveled to access health care and poor transportation infrastructure, and the lack of health skilled providers are often alluded to as the major obstacles in expanding health care services in remote areas within developing countries. This study discusses the systemic problems in Uganda’s healthcare delivery system with particular reference to maternal health. A methodical review of the literature and the analysis of the 2012 Access, Bottlenecks, Costs, and
Equity (ABCE) survey of health facilities in Uganda confirm the widespread reality of a generally fatigued and underfunded healthcare sector that could benefit from a disruptive solution. By recognizing that this research was bound by scope of coverage;
vi potential areas for further research are presented and limitations of the research are
discussed. The purpose of this study approach is to help advance the incubation of
innovative technology-enabled solutions within the healthcare services delivery system.
Telehealth solutions are offered as the disruptive remedy that can help to close the health inequity gap between regions and income, thereby helping to expand access and coverage of maternal health care in Uganda.
vii Table of Contents
Acknowledgements ...... iv
Abstract of Praxis ...... vi
List of Figures ...... vi
List of Tables ...... vii
List of Acronyms and Abbreviations ...... viii
Chapter 1. Introduction and Research Overview ...... 1
1.1 Introduction ...... 1
1.2 Problem Statement ...... 3
1.3 Problem Elaboration ...... 8
1.4 Thesis Statement ...... 19
1.5 Research Questions ...... 19
1.6 Research Objective ...... 20
1.7 Hypothesis ...... 21
1.8 Praxis Structure ...... 23
Chapter 2. Literature Review ...... 25
2.1 Maternal Health in Uganda ...... 25
2.2 Introduction to Telehealth ...... 32
2.3 Impact of Telehealth ...... 34
2.4 Telehealth in Africa ...... 35
2.5 Impact of Telehealth in sub-Saharan Africa ...... 36
2.6 Lessons from the Use of Telehealth in Native American Communities and Rural
Areas in Mongolia ...... 37
iii Chapter 3. Research Methodology ...... 40
3.1 Introduction ...... 40
3.2 Research Strategy ...... 40
3.3 Research Design, Survey Data Definition & Data Analysis ...... 41
3.4 Research Questions ...... 43
3.5 Research Hypotheses ...... 44
Chapter 4. Discussion of Results ...... 48
4.1 Introduction ...... 48
4.2 Regression Diagnostics: The Assumption of Normality, Linearity,
Homoscedasticity, and Outliers ...... 48
4.3 The Quantile - Quantile (Q-Q) Plot—Test of Assumption of Normality ...... 49
4.4 The Residual Plot ...... 50
4.5 Results ...... 51
4.6 Discussion of Results ...... 61
Chapter 5. Suggestions for Future Research and Conclusion ...... 72
5.1 Conclusion ...... 72
5.2 Research Contributions ...... 73
5.3 Future Research Recommendation – Impact of Telehealth in Consideration of
Variations in Health Care Utilization ...... 78
5.4 Future Research Recommendation – Impact of Telehealth on Recruitment and
Retention of Health Care Professionals in Rural Areas ...... 79
5.5 Future recommendation: Education, Innovation and Research...... 81
5.6 Future Recommendation: Telehealth and Quality of Care ...... 83
iv References ...... 86
Appendix B: Organization and Function of Uganda Health Care Services...... 94
Appendix C: Roles at Various Levels of the Health System in Uganda ...... 94
Appendix D: Relative Fill Rates in 2010 and 2011 for Doctors, Clinical Officers,
Nurses, and Midwives for five Facility Types ...... 95
Appendix E: Antenatal Care ...... 96
Appendix F: Selected Health Financing Indicators for Uganda and Comparison to
Average for Peer Countries ...... 97
Appendix G: SDG Goal 3 ...... 98
Appendix H: Number of Urban Centers by type and Urban Population, 1991– 2016 ... 100
v List of Figures
Figure 1: Current Health Expenditure...... 5
Figure 2: Heath Care Sector in Uganda ...... 10
Figure 3. Fertility Rates in Uganda (1995 – 2011) ...... 16
Figure 4. World Map showing Total Fertility Rate in 2016 (Births per Woman) ...... 16
Figure 5. Fertility by Background Characteristics ...... 17
Figure 6. Causal Loop Diagram Illustrating Demand and Supply Side Interactions
for Maternal and Newborn Services ...... 19
Figure 7. Education and Literacy in Uganda ...... 31
Figure 8. The Quantile - Quantile (Q-Q) Plot ...... 49
Figure 9. The Residual Plot (Residuals versus Predicted Values) ...... 50
Figure 10. Interaction between Telehealth and User Fees on Maternal Death Rate ...... 56
Figure 11. Maternal Death Rates by Telehealth Service and Location ...... 60
Figure 12. Predicted Death Rate by Facility Type and Location ...... 62
Figure 12.1. Differences in Predicted Death Rate ...... 62
Figure 13. Management of Telehealth Candidate Facilities ...... 63
Figure 14. Telehealth Model Process Flow ...... 68
Figure 15. Proposed Hub & Spoke Telehealth Model & Approach ...... 70
Figure 16. Integration of Evidence Based Medicine (EBM) and Telehealth ...... 81
vi
List of Tables
Table 1: Functional Classification of Central Government Recurrent Expenditure by
Percentage Share, 2011/12 – 2015/16 ...... 7
Table 2: Overall Model Fit Using Seven Measures of Health Care Cost ...... 53
Table 3: Moderation of Effect of Existence of Telehealth Service with Measures of
Health Care Cost ...... 54
Table 4: Model Coefficients Using Cesarean Delivery Fees as a Measure of Health
Care Cost ...... 55
Table 5: ANOVA Table for Analysis Role of Telehealth on Access (location) ...... 58
Table 6: Coefficients for a Model with Interaction Effects of Telehealth and Access
(location) ...... 59
Table 7: Profile of clinics and telehealth candidate facilities ...... 64
Table 8: Profile of rural and urban facilities ...... 65
vii
List of Acronyms and Abbreviations
ATA American Telemedicine Association
ABCE Access, Bottlenecks, Costs, and Equity
CDC Center for Disease Control and Prevention
DHS Demographic and Health Surveys
GOU Government of Uganda
HCI Health Care Center 1
HCII Health Care Center 2
HCIII Health Care Center 3
HCIV Health Care Center 4
MOH Ministry of Health
MDG Millennium Development Goals
NCCDPHP National Center for Chronic Disease Prevention and Health Promotion
SDG Sustainable Development Goal
UBOS Uganda Bureau of Statistics
USAID United States Agency for International Development
UDHS Uganda Demographic Health Survey
WHO World Health Organization
MNH Maternal and Newborn Health (MNH)
TFR Total Fertility Rate
UNESCO The United Nations Educational, Scientific and Cultural Organization
viii
Chapter 1. Introduction and Research Overview
1.1 Introduction
This chapter outlines the idea and purpose of this research study, discussing why it is important to find innovative and technologically-enabled solutions that can help solving problems distressing the delivery of maternal health services in Uganda, how health facilities in Uganda are ill-equipped to meet the needs of expecting mothers within their catchment areas, and how this study can assist in the effort to craft effective maternal health care programs in Uganda. This chapter also demarcates the boundaries of this study by providing clear research questions and a hypothesis to help in providing a better understanding of the central purpose of this study.
In 2015, The United Nations proposed 17 broad goals under the Sustainable
Development Goal (SDG) framework to establish broad targets covering a wide range of social-economic development concerns, including health. The SDG framework supplanted the Millennium Development Goals (MDGs), which were terminated in 2015.
The intention of SDG Goal 3 (ensure healthy lives and promote well-being for all at all ages) is to promote “good health and well-being for people” by improving reproductive, maternal and child health (SDG Report, 2016). More pertinent to this study is subsection
3.1 of SDG 3 which aims to “reduce the global maternal mortality ratio to less than 70 per 100,000 live births by 2030.” All subsections of SDG 3 are included in Appendix G.
Uganda, like many developing countries, has made great strides in meeting the maternal and child health indicators of SDG 3. For example, pregnancy-related deaths per
100,000 live births dropped from 438 between 2004 and 2011, to 368 between 2009 and
2016 (Uganda DHS, 2016). Additionally, infant mortality decreased from 71 deaths per
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1,000 live births in 2006 to 43 deaths per 1,000 live in 2016 (Uganda DHS, 2016).
Notwithstanding this overall progress, regional differences exist among rural and urban
regions of the country. The Uganda DHS (2016) report showed that 94% of births in
Kampala (mostly urban) were delivered in a health facility. On the other hand, the
number of births delivered in a health facility in the Bugisu region (mostly rural) was a
mere 56%, accounting for a 38% regional difference between these two areas. These
regional differences point to a lack of access to health facilities in rural areas and
weaknesses in the healthcare system as a whole.
The performance of Uganda’s healthcare system is still ranked as one of the worst in the world. It ranked 186th out of 191 nations by the World Health Organization (WHO) in terms of health care performance in 2009 (Sisay, 2009). The bottlenecks in Uganda’s health delivery system have been well documented in the USAID funded report, “The
Uganda Health System Assessment Report of 2011.” This report identified numerous challenges faced by the health system: governance issues, limited capacity particularly at the local level, high health financing costs of up to 54% that make health care unaffordable for many, inconsistent quality of care, and difficulty in accessing primary health care. Other challenges noted in this report included the high costs of secondary and tertiary care, lack of financial and human resources, and a health information system that relies heavily on paper-based medical records.
Telemedicine, or telehealth—the use of electronic information and communications technologies to provide and support health care when distance separates participants— has been lauded for its contribution to healthcare systems all over the world. Some of the benefits as promoted by the American Telemedicine Association (ATA) include
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increasing patient access, enhancing reach of healthcare services, reducing provider costs,
24/7 coverage, and reducing health care costs.
1.2 Problem Statement
Uganda lacks an appropriate number of health care providers and adequate functional health facilities that results in high rates of maternal deaths. Generally, the lack of an acceptable number of healthcare providers and health care facilities in Uganda is largely a function of the inadequate level of expenditure (public and private) on health care. In fact, the Current Health Expenditure (CHE) as a percent of GDP decreased to 7.3% in
2015 from a high of 12% in 2006 according to WHO. Doctors and other medical professionals are constantly on strike — protesting low salaries, poor housing, inadequate transportation, and shortage of essential supplies like gloves and sterilizers at hospitals all across Uganda. The situation is worse in rural areas where health care providers are paid late, sometimes having to wait for up to four months for their salaries. It doesn’t help that a good number of healthcare facilities in Uganda are dilapidated, having been left vandalized by wars and neglect. As a result of the poor working conditions across the entire healthcare sector, young Ugandans are less incentivized to seek careers as doctors or nurses. In fact, there is an increasing influx of young health care providers (especially doctors) who are leaving Uganda for better prospects overseas (mostly in Europe, North
America, Middle East, and South Africa), to seek higher pay and better facilitation. The
issue of brain drain is not limited to Uganda; it’s a problem that has spread all over the
developing world but most especially in Africa. This issue has also exacerbated health
care inequity with regard to the distribution of health care workers across the world.
According to WHO, “The African region suffers more than 24% of the global burden of
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disease but has access to only 3% of health workers and less than 1% of the world’s financial resources” (WHO, 2018).
The bigger part of public expenditure on the healthcare sector in Uganda comes from the coffers of the central government with the remaining portion disbursed from the decentralized local governments. According to the 2011 Health Sector Strategic and
Investment Plan (HSSIP 2010/11 - 2014/15), the government of Uganda allocated an average of 7.8% of its annual budget to the health care sector between 2010 and 2015, which is below the HSSIP target of 9.8%. The gap left by inadequate public health expenditure is partially filled by external donors through grants and subsidized loans.
Increasingly, the private sector is also investing in the health care sector. However, the majority of Ugandans, especially women and rural dwellers, cannot afford to pay for health care services at private hospitals. Overall, Uganda’s total expenditure on health care per capita is mostly very low compared to both developed and developing countries.
The Abuja declaration of 2001 set a 15% (as a percent of the annual budget) health financing target for all member states of the African Union as a means to fulfill the
Sustainable Development Goals (SDGs) framework designed to help shrink poverty, promote environment sustenance, and to boost economic development (WHO, 2018).
Health expenditure per capita includes preventive and curative health services, family planning services, nutrition and general emergency health intervention outlay per WHO guidelines. Uganda’s health expenditure per capita was US Dollar (USD) $52.29 U.S.
Dollars (USD) in 2014 which ranked Uganda on the WHO list at 160 out of 186 countries in the world (WHO, 2014). Switzerland appeared first on the list with a health expenditure per capita of USD 9,673.52; The United States (USA) appeared third with a
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per capita health expenditure of USD 9,402.54, and Madagascar at the bottom of the list at USD 13.67. Given the low level of health expenditure in Uganda, there is need for the health care sector to adopt innovative strategies that will help to promote efficiency and resource optimization. This study examines if telehealth is the optimal innovative solution that could be harvested to increase maternal health outcomes in light of limited health expenditure.
Current Health Expenditure (CHE) as % Gross Domestic Product (GDP) - Uganda 14.0
12.0 11.7 12.0 11.3 10.7 10.5
10.0 9.4 9.2 8.6 8.6 8.0 7.6 7.7 7.8 8.0 7.2 7.3 7.3
% of DGP 6.0
4.0
2.0
- 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Source: WHO Database
Figure 1: Uganda Current Health Expenditure
Overall, the Ugandan government spends a disproportionate amount of its budget on defense and security than on health (UBOS, 2016). The government expenditure on the community and social services sector, which significantly impacts health services
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delivery, is also very low. The 2016 UBOS report also indicates that the largest share of
the Ugandan budget goes to general public administration (47.3% in 2015/16); defense
(12.7% in 2015/16), and public order and safety (10.7%)—whereas education (9.4% in
2016), water (0.1% in 2016), and other community and social services (1.8% in 2016) get
less allocations from the budget on a comparative basis (see 2016 UBOS data on
expenditure in Table 1 below). Without increasing government expenditure on health, the
high level of Out-of-Pocket expenditure on health, estimated at 40%, will only increase
(National Health Expenditure (NHA) Report, Ministry of Health, Uganda, 2016). The
World Health Organization (WHO) recommends 15% as the maximum amount of
household Out-of-Pocket health care expenditure, according to the 2016 NHA report. The
non-public sector has played a part in bridging the gap, but over-reliance on donors,
charity, and foreign aid is not a sustainable strategy in the effort to reduce Out-of-Pocket expenditures (National Health Expenditure Report, Ministry of Health - Uganda, 2016).
The revenue from private and development partner financing schemes fluctuates
regularly, and can be difficult to predict, as the government has little or no control over
these financing sources. This impedes effective planning and can lead to disruptions in
maternal and other health delivery services. The contribution by financing source to
Uganda’s total current health expenditure in 2014 shows that government funds
underwrote 17.7%, private funds 41.1%, and development partner funds 41.2% (National
Health Expenditure Report, Ministry of Health - Uganda, 2016). This shows that private
and development partner financing sources impact Uganda’s health expenditure budget
far greater than government funds. Furthermore, increased pressure caused by an increase
of population will impact the future level of expenditure on health. The Ugandan
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government will have to ensure the pace of expenditure on health is at par or above the rate of population growth. As the population grows, Uganda will need additional health services and healthcare infrastructure.
Accordingly, Uganda’s under-facilitated educational sector has not been able to produce an adequate number of well-trained health care providers over the years. This issue has also been aggravated by the poor state of water and sanitation services which also increase Uganda’s disease burden level. That being said, innovative telehealth solutions can mitigate the consequences of underfunding in the health sector through efficiencies and optimization of resources. This mitigation is further enabled by the use of remote technologies in delivering health care services to remote areas.
Table 1: Functional Classification of Central Government Recurrent Expenditure by percentage share, 2011/12 – 2015/16 (UBOS 2016)
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1.3 Problem Elaboration
Uganda’s health sector challenges are widespread and systemic. The deficiencies in
the physical and human infrastructure base within the healthcare sector, such as the lack
of electricity, trained health care providers, water, good roads, equipment in health
facilities, and so forth, are conspicuous and perennial. The delivery of maternal health
services suffers further burden by the lack of health care providers, a despondent referral
system, and the lack of adequate government funding. The health services delivery model
in Uganda is based on a tiered structure referral system, with the village level health
centers (HC I) residing at the bottom of the hierarchy. Patients that cannot be adequately
and clinically managed at the village level are supposed to be referred to the next higher
level facility. The pecking order for delivering health care services follows a stepladder
pathway model through health centers II, III, IV, V, with final termination points at the
regional and national referral hospitals. The organization hierarchy of Uganda’s health
care sector is represented below in Figure 2.
The lack of coordination among healthcare facilities, poor referral protocols, and the general malaise within the healthcare sector has left Uganda’s referral system largely ineffective (Malgo, 2015). Notwithstanding the significant improvements in both infrastructure development and services delivery since the 1990s, the systemic deficiencies in the healthcare sector are still poor when compared to the developed world.
The inadequacies within the health referral system in Uganda are worsened by the
disproportionate distribution of health care workers, which is, in turn, influenced by
facility type. Health facilities located in urban areas fill the highest share of health care
worker posts compared to rural health facilities, according to the 2011 Uganda Health
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System Assessment Report (UHSA, 2011). Urban centers account for only 13% of
Uganda’s population, and yet urban health care facilities hold the highest percentage of health care workers in the hierarchy. This uneven distribution impedes access to health care services in rural and remote areas (Uganda Health System Assessment, 2011). A research study on the state of the referral system in Uganda and how it influences maternal healthcare concluded that
…the referral system can be labelled as dysfunctional in many respects. A lack of
trust from the care-seekers’ perspective, non-functionality of the health facilities,
limited transportation possibilities at the time of referral and an incomplete registry
which makes the accountability almost non-existent. The result of all this is a high
amount of self-referrals which create a barrier for improvement. As long as the self-
referrals are not reduced, it is hard to change anything within the functionality of the
referral system… Malgo, 2015).
Malaria is one of the leading causes of maternal deaths in Uganda with pregnant women and children suffering the highest morbidity and mortality. “Pregnant women infected with malaria usually have more severe symptoms and outcomes, with higher rates of miscarriage, intrauterine demise, premature delivery, low-birth-weight neonates, and neonatal death. They are also at a higher risk for severe anemia and maternal death”
(Schantz-Dunn et al, 2009). According to the 2014 National Malaria Control Program
(NMCP), malaria is the leading cause of morbidity and mortality in Uganda responsible for up to 50% of outpatient visits at health facilities, 20% of all hospital admissions, and about 20% of the number of death reported in hospitals. Evidently, the high burden of
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malaria in Uganda is an issue that deserves a comprehensive intervention strategy. The
2016 Malaria Indicator Survey (MIS), indicated continued improvement in the control of malaria with all measures of malaria moving in the right direction since 2006, albeit with regression in some areas. Even with increased resources on prevention programs, malaria control programs in Uganda continue to show mixed results - an indication of the need to identify innovative solutions that can rapidly curb the prevalence of the disease especially in places with the highest burden of malaria (rural and swampy areas).
Malaria is transmitted by mosquitoes infected with a parasite called Plasmodium
Falciparum. The parasite-infected mosquitoes spreads the disease from person to person via bite inflictions on human tissue. The poor management of water body ecosystems in
Uganda due to lack of funding is also partly to blame for the proliferation of malaria- carrying mosquitos. These water bodies (especially smaller water pools, water channels, and wetlands) constitute fertile breeding ground for mosquitoes. “The ecology of the disease is closely associated with the availability of water, as the larval stage of mosquitoes develops in different kinds of water bodies” (WHO, 2001). For Uganda’s case, the immense availability of water bodies throughout the country provides a natural ecosystem for mosquito habitation. Uganda is endowed with numerous sources of surface water with almost 16% of the country’s total area covered by open water and swamps
(Nsubuga et.al, 2014). While water resources are important assets to any country in terms of socio-economic development, they can also be a source of disease agents if not managed properly.
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The high prevalence of malaria is partly responsible for the high rate of maternal
mortality in Uganda. As such, any effort to improve maternal health outcomes has to
include a comprehensive strategy to help in controlling Malaria. According to Schantz-
Dunn et al (2009), pregnant women are three times more susceptible to contracting severe
malaria compared to women who are not pregnant, and with severe malaria responsible
for increasing the mortality rate of women to about 50%. Rural areas are especially more
impacted by malaria due to low education levels of rural dwellers, lack of access to health
facilities, and lack of well-trained health care workers. Malaria is relatively easy to prevent if detected and treated early. However, the inability of most people
(disproportionately rural women and children) to pay for diagnosis and treatment only ensures to propagate the lethality of malaria. Furthermore, the lack of an adequate number of places to conduct diagnostic blood tests in Uganda (mostly in rural areas) makes it very difficult to control malaria.
The fight against the malaria epidemic is very costly and consumes a big share of
Uganda’s annual health sector budget. Malaria also adversely impacts socio-economic development as a result of decreased productivity due to loss of workdays, pressure on healthcare services, school-absenteeism, and high Out-of-Pocket health expenditure. The
Uganda National Malaria Control Program (NMCP) recommends the use of Insecticide
Treated Nets (ITNs), Indoor Residual Spraying (IRS), provision of intermittent preventive treatment of malaria in pregnancy, and early treatment and diagnosis of malaria and anemia as the most effective means to avert complications of malaria and pregnancy (Uganda Malaria Indicator Survey, 2015). The Government of Uganda and its development partners have adopted programs all over the country that distribute bed nets
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to children and pregnant mothers at antenatal clinics and community centers (Uganda
Ministry of Health, 2005). However, the slow rate of acceptance and the improper use of bed nets (especially in rural areas) dilutes the intended benefits of using ITNs. According to the Uganda Malaria Indicator Survey (2015), the use of ITNs also correlates with the level of educational attainment of pregnant women, with about 80% of women with no education reported to be using ITNs as related to 70% of women with high school
(secondary) education. For this reason, prevention strategies have to be multi-pronged and holistic. In general, malaria prevention programs in Uganda continue to be hindered in their effectiveness due to the lack of resources, high barriers to health care access, and the lack of well-trained health care workers.
Consequently, the above mentioned obstacles within the health care services delivery system makes malaria a major causation of high maternal death rates. A large number of people all over Uganda (especially in rural areas) opt to seek care from traditional healers and others self-medicate when they get infected with Malaria. And so Malaria in
Pregnancy (MiP) is a major factor that contributes to the state of maternal health in
Uganda and most of the Sub-Saharan Africa region. This study is focused on understanding how telehealth can be used to moderate maternal death rates. With the prevalence of malaria and maternal death highly correlated, understanding what aspects of malaria control programs can be addressed by the deployment of telehealth applications merits the attention of MiP research.
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Figure 2: Health Care Sector in Uganda (Uganda Hospital and Health Centre IV Census Survey, 2014)
1.3.1 Systemic Problems in Uganda’s Healthcare Sector
Over the years, the Ugandan government has not only had to deal with the issue of
health care inequity, but has also encountered challenges concerning how to resolve
widespread systemic inefficiencies in the healthcare sector. These inefficiencies continue
to negatively affect national development. The level of access to health care in Uganda is
determined by several issues, including income, cultural norms, gender, closeness to
health care services, poor infrastructure, and quality of care provided. The healthcare
system in Uganda is comprised of both the private and public sectors, with the public
sector taking most of the burden of providing health care services.
As alluded to above, Uganda’s health system is organized under a referral structure
comprised of national hospitals and village health centers according to the Annual Health
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Sector Performance Report (2010). The national hospitals include the national and
regional referral hospitals. The apex of the healthcare system in Uganda is the Mulago
National Referral Hospital located in Uganda’s capital city, Kampala. However, Mulago
national referral hospital, the most specialized hospital in Uganda, is also understaffed,
overcrowded, and lacks basic amenities and medicine. The lower-level facilities (district and village health centers) refer cases they can’t handle to higher-level facilities (such as the national and regional referral hospitals). Most rural areas are serviced by lower-level village health centers, most of which are staffed by volunteer workers and underpaid staff. The first-level village health centers (HC I), which provide primarily modest health care services, are normally staffed by untrained and often volunteer providers. The second-level village health centers (HC II) provide outpatient services and are normally staffed by volunteers and nurses. The third-level village health centers (HC III) are
normally staffed by a doctor and a nurse, and can provide in-patient services. The fourth-
level village health centers (HC IV) provide all services provided at lower-level centers,
in addition to routine surgical services.
Almost half of Uganda’s population lives within an hour of walking distance to a
health facility capable of both curative and preventive services. Within this landscape,
most Ugandans find it very difficult to access health care services due to the lack of
adequate and accessible transportation. Instead, some opt to self-medicate, while others resort to traditional medicine as an alternative. On top of the need to increase the number of health facilities, empirical analysis suggests that Uganda will not be able to build enough road capacity in the near term to sufficiently improve access to health care, particularly in rural and remote areas. As a result, any intervention designed to increase
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access to health care would need to decrease the average distance between a care-seeker’s place of residence and the nearest health facilities.
1.3.2 Fertility Level in Uganda: Supply and Demand Side Factors
According to the 2011 UDHS survey, Uganda’s total fertility rate (TFR) reduced to
6.2 children per woman in 2011, down from 6.7 in 2006 and 6.9 in 1995 (see Figure 1 below). The 2011 UDHS survey further stated that rural areas have a very high level of fertility—almost twice as high when compared to urban areas. TFR in 2011 was 6.8 in rural areas versus 3.8 in urban areas (see Figure 5). In addition to rural women, fertility rates were very high among less-educated women and those in the lower wealth quintile
(see Figure 5 below). The World Bank (2016) estimated that Uganda’s TFR was 5.6 in
2016, which put the country at number 5 in the world—lower than Niger, which took the top spot with a TFR of 6.7. Even with continuing reduction in fertility rates over the years, Uganda is still considered to have one of the highest fertility levels in the world
(see Figure 4 below). This evidence strongly suggests that the demand for maternal health services remains very high in Uganda, especially in rural areas and among poor people.
The demand for maternal health services and the related health infrastructure is expected to grow exponentially given Uganda’s high rate of population growth.
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Figure 3: Fertility Rates in Uganda (1995 – 2011) (UBOS, 2014)
Figure 4: World Map showing Total Fertility Rate in 2016 (Births per Woman) (The World Bank Data, 2017)
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Figure 5: Fertility by Background Characteristics (UDHS, 2011) This research study discovered a significant deficit in supply-side factors with respect to maternal health services in Uganda, especially in rural areas where the need is highest.
In a reproductive study conducted in mostly rural Eastern Uganda to assess the changes
in Ugandan maternal and newborn services in health facilities, Muhumuza, Kananura, et
al. (2017) found “distinct influences on both demand and supply-side, which restrain both
health care uptake and its quality.” This study identified gaps between health care facility
readiness to make health care services available to their catchment population, and the
17
readiness of women to make use of those services. On the supply side, Muhumuza,
Kananura et al. (2017) found that the majority of the health facilities in Eastern Uganda had a supply shortage of essential lifesaving drugs, including misoprostol, IV Ampicillin,
Ergometrine, IV Gentamycin, IV Metronidazole, and so forth. This study also found that most health facilities in Eastern Uganda were not adequately supplied with equipment
“for the management of labor and abortions such as Manual vacuum aspirator for abortion care, blank partographs.”
On the demand side, Muhumuza, Kananura et al. (2017) conducted qualitative interviews and regarded “long distances and inadequate transport to the health facilities, inadequate information, poverty, and poor services at the health facilities as major factors that impede women to utilize and access maternal and newborn services.” The demand side factors that influence the utilization of health services according to this study included individual factors (education, age, income, and so forth), household factors
(influence from family members), and community factors (geographical location, distance to health services, ease of access to transport, and others). Given the reality on the ground in Uganda as evidenced here, the significance of engaging in the effort to find solutions to moderate both demand and supply-side barriers in order to help reduce maternal deaths cannot be overemphasized. Both supply and demand-side factors affect each other, and are concordant in their corresponding effects (see Figure 6 below).
Against the backdrop of the persistent gap in demand and supply-side factors, the focus of this praxis is directed toward examining whether or not technology-enabled solutions can help close the gap between the demand and supply of maternal health services in Uganda. In light of this focus, however, it should also be noted here that Uganda’s health care problems require holistic
18
solutions of which telehealth itself is a single component to the overall, countrywide solution to
Ugandan health care infrastructure.
Figure 6: Causal loop diagram illustrating demand and supply side interactions for maternal and newborn services (Kananura et al. Reproductive Health (2017) 14:136)
1.4 Thesis Statement
A comprehensive telehealth model that focuses on applying technologically-enabled
solutions and tools will improve maternal health care outcomes in Uganda.
1.5 Research Questions
This research explores the telehealth model as a solution to Uganda’s health system
challenges. Specifically, this research will seek answers to the following three questions:
1. Which telehealth model and tools can be applied to the healthcare delivery system
in Uganda to increase access?
2. What is the impact of telehealth on health care cost and access in Uganda?
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3. Are there differential impacts of telehealth use on identifiable regional sub-
groups?
1.6 Research Objective
Uganda’s healthcare system is adversely impacted by many problems, including a shortage of health care providers, subpar healthcare quality, poor infrastructure, and inadequate government funding. This research will determine whether or not telehealth can be leveraged to improve maternal health care outcomes in Uganda given the above- mentioned systemic problems. Past research has shown that telehealth can be leveraged in health promotional activities, prevention of occurrence and incidence of disease, medical diagnosis, and clinical consultation and therapy (Hebda & Czar, 2013).
For the purpose of this research study, the use of the term “mobile clinic” or
“fac_mobile” denotes the availability of telehealth services at a health facility. Telehealth services at a given health facility can include a combination of different capabilities from any of the four common practical applications of telehealth listed below (Center for
Connected Health Policy, 2008):
1. Use of live-video as a substitute for in-person meetings to provide medical
diagnosis, clinical consultation and treatment services.
2. Asynchronous electronic transmission of a patient’s recorded health history and
digital images (x-rays and photos) to a healthcare provider seeking to access non-
real time (NRT) services.
3. Use of remote patient monitoring (RPM) to track a patient’s healthcare data
without having the patient travel for in person doctor visitation.
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4. Use of Mobile health (m-Health) devices and applications by relying on mobile
devices such as smart phones and tablet computers to promote healthcare
education and training.
1.7 Hypothesis
1.7.1 Hypothesis on the impact of Health Care Costs (H1)
Study Null Hypothesis Study Alternative Hypothesis Hypothesis H10: There is no difference in Hypothesis H1A: Health facilities in
mortality rates per capita among health Uganda with high health care costs are
facilities in Uganda regardless of health associated with high mortality rates per
care costs. capita.
This study hypothesizes that health facilities with high health care costs are associated
with high mortality (maternal death) rates per capita. Accordingly, introducing a
telehealth model moderates costs and reduces maternal death rates per capita. To test the relationship between telehealth, health care costs, and maternal death rates, this research study applied the concept of “statistical interaction effect” which happens when one independent variable (health care costs) interacts with another independent variable
(telehealth) on a dependent variable (maternal death rates). Simply put, the presence of an interacting term effect conveys how two or more independent variables work together to influence the dependent variable. Accordingly, we added to the main study hypothesis on health care costs the following sub-hypothesis in order to understand the interaction effects of the independent variables on the dependent variable:
• Null sub-hypothesis - There is no difference in mortality rates per capita among
health facilities in Uganda regardless of health care costs and telehealth.
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• Alternative sub-hypothesis - The existence of telehealth at health facilities in
Uganda moderates costs and reduces mortality rates per capita.
The correlation between the existence of telehealth at health facilities in Uganda and health care costs at those facilities was tested to understand the linear relationship between the independent variables (telehealth and health care costs) in relation to the hypothesis on the impact of health care costs (H1). Correlation measures the association between variables. However, this research does not presuppose association between two independent variables that have a predictive interaction effect on a dependent variable.
1.7.2 Hypothesis on the Impact of Health Care Access (H2)
Study Null Hypothesis Study Alternative Hypothesis Hypothesis H20: There is no difference in Hypothesis H2A: Health facilities in
mortality rates per capita among health Uganda with lower levels of access
facilities in Uganda regardless of the level barriers are associated with lower
of access. mortality rates per capita
This study hypothesizes that health facilities with lower levels of access barriers are
associated with lower mortality rates per capita. Accordingly, introducing a telehealth
model moderates the impact of access barriers and reduces maternal death rates per
capita. To test the relationship between telehealth, health care access, and maternal death
rates, this research study applied the concept of “statistical interaction effect” which
happens when one independent variable (health care access) interacts with another
independent variable (telehealth) on a dependent variable (maternal death rates).
Accordingly, we added to the main study hypothesis on health care access the following
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sub-hypothesis in order to understand the interaction effects of the independent variables
on the dependent variable:
• Null sub-hypothesis - There is no difference in mortality rates per capita among
health facilities in Uganda regardless of the level of access barriers (location) and
telehealth.
• Alternative sub-hypothesis - The existence of telehealth at health facilities in
Uganda moderates access barriers (location) and reduces mortality rates per
capita.
Likewise, the correlation between the existence of telehealth at health facilities in
Uganda and health care access was tested to understand the linear relationship between the independent variables (telehealth and health care access) in relation to the hypothesis on the impact of health care access (H2).
1.8 Praxis Structure
This praxis is comprised of five chapters, including supplemental information in the
appendix section. The chapters are organized linearly to describe the adopted research
path and cross-examine whether or not telehealth solutions can be applied to Uganda’s
healthcare delivery system in order to improve maternal health outcomes.
• Chapter 1 provides the general idea of the research looking to establish and
validate the theoretical argument of the research. This chapter discusses the
research approach and describes the research questions. Also presented in this
chapter are the research hypotheses.
• Chapter 2 provides the review of the literature looking to support the theoretical
argument that introducing telehealth solutions can help to improve maternal
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health outcomes by way of increasing access to health services in remote
locations particularly in rural areas.
• Chapter 3 provides the methodology and design used in the research so that the
study could be repeated in the future. Secondary analysis techniques were used to
analyze the data. Also, this chapter provides an overview of the ABCE facility
survey data used and provides the basis of the premise for this research.
• Chapter 4 provides the results and findings of the research taking into account the
research questions that were posed in Chapter 1. Conclusions are then provided
centering on the results and findings of the research. The strengths and limitations
of this research are also deliberated upon within this chapter.
• Chapter 5 discusses the likely implications of this study, suggestions for future
research in the area of maternal technology-enabled health care solutions, and
concludes with a discussion on the promise of telehealth as a potential disruptive
solution.
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Chapter 2. Literature Review
2.1 Maternal Health in Uganda
This chapter connects the praxis to previous research by providing a contextual framework of the issues affecting the delivery of health care services (with particular emphasis on maternal health) in Uganda, and the potential domain of solutions that could be adopted to close the gap. First, this literature review discusses Uganda’s state of maternal health in relation to the rest of the world. Next, while acknowledging improvements in the health care sector, this literature review also discusses Uganda’s big health care inequity gap and points out the potential areas within the health care delivery system where telehealth can be used as a solution. Overall, this chapter reviews literature on telehealth as an innovative solution generally, and showcases examples across the world where such telehealth technology has succeeded. By doing so, this chapter helps identify the knowledge gap in the area of maternal health services delivery—in other words, the basis for this research and areas of further research.
First, a discussion of the country under review is necessary for this study. Uganda is a landlocked country located in East Africa. The estimated population of Uganda was 41 million in 2016 (UBOS, 2014). Uganda covers an area of 241,038 square kilometers, with 15% of the area mass covered by water bodies. Uganda’s nominal Gross Domestic
Product (GDP) was estimated at USD 26 billion in 2017, with per capita income at a meagre USD 700 (UBOS 2014). Uganda’s economy grew an average annual rate of 7% in the 1990s following the cessation of the costly civil war ushered in by the current government of now Ugandan President Yoweri Museveni in 1986. Uganda’s economic growth (GDP), however, had shrunk to an annual average of 4.5% from 2010 through
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2016. This decrease in economic growth (GDP) weakened Uganda’s efforts to revamp its health care sector in the rapid manner described in its earlier projections. The World
Bank currently expects Uganda’s economic growth (GDP) to rise above 5% in 2018 and could further improve to more than 6% in 2019. This increase would provide an opportunity for the country to re-invigorate efforts to invest in health care related programs it previously bypassed as a result of shrinking economic growth (GDP).
Historically, Uganda obtained its independence from Britain in 1962 after nearly 70
years as a British protectorate. The period following independence, sadly, included
several civil wars which severely weakened Uganda’s economic development. Just a few
years after independence, the military coup of 1971 began the dictatorship of General Idi
Amin, characterized by many observers as a period of gross abuses of human rights and economic stagnation. Tens of thousands of Ugandans lost their lives during Idi Amin’s rule, including many educated people. Doctors and nurses decided to escape the country in fear for their lives. The wars subsequent to 1979, after the Idi Amin regime, were also responsible for causing brain drain across all of Uganda’s sectors, including health care.
Suffice it to say, civil strife and wars in Uganda are currently responsible for its inadequate number of health care providers and health care facilities. During times of war, the country did not significantly improve its health care infrastructure or develop proper health care practices. In fact, many health care facilities built during Uganda’s colonial period (pre-independence) were either neglected during times of civil strife or were destroyed during post-independence wars.
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Under the supervision of the World Bank and International Monetary Fund (IMF),
Uganda commenced implementing economic reforms in 1986. The multinational-led
structural adjustment programs (SAPs) required Uganda to adhere to numerous
conditionalities as a prerequisite for receiving new loans, or for obtaining lower interest
rates on existing loans. Some of these conditionalities required the cutting of social
expenditures (economic austerity), the devaluation of currency, and trade liberalization.
With decreased expenditure on health, education and government entitlement programs,
some observers in academia and politics have argued that poverty, income inequality, and
health inequity have increased as a result of those cuts in funding.
Even though Uganda has laws on the book criminalizing discrimination, the abuse of
women and human trafficking, research indicates that a large number of women still
suffer subjugation and abuse. These findings are partly due to old-fashioned cultural
norms which give women treatment as second-class citizenship, and also the lack of an effective Ugandan arm of government law enforcement. Uganda retains some elements of a patriarchal society restricting women (especially in rural areas) largely to domestic roles. As such, examples of domestic violence are many and widespread. According to the Uganda 2012 Human Rights Report,
“…a July 19 Center for Basic Research report indicated 70 percent of women
interviewed from eastern and northern regions had been beaten by their husbands. In
addition the findings indicated, 17 percent of the same women had been raped, 23
percent forced into marriage, 1 percent denied inheritance rights, and 10 percent
denied political rights” (US State Department, 2012).
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Also, some communities in Uganda still practice female genital mutilation which can
have severe consequences on the reproductive health of women who undergo such
scientifically-pointless procedures. Female genital mutilation is outlawed, but reports of
women becoming victims of the practice continue to surface every day. It’s important to
note that over the years progress has been registered in the effort to transform Uganda
from a male-dominated society to a society of inclusivity. Nevertheless, it becomes vital
for women to have easy access to maternal health care services, and to provide women
reproductive health education in a vibrant and effective maternal health delivery system.
Such changes in Uganda’s health care sector can help mitigate some of Uganda’s above-
mentioned societal problems.
The state of water, sanitation, and hygiene (WASH) at health care facilities in Uganda
and other parts of Africa remains very poor. According to Water Aid Uganda (WAU), 24 million Ugandans do not have access to clean water, and over 4,500 children under 5 die from diarrhea every year due to dirty water and poor toilets (Water Aid Uganda, 2018).
Improving the ease of access to safe and clean water would produce numerous societal benefits, including the suppression of water-borne diseases and improved sanitary conditions in health care facilities. Additionally, the ease of access to water reduces the time spent trapping rain water and/or collecting water from rivers and lakes. According to the government of Uganda, the coverage of water in rural areas increased from 20% in the early 1990s to 60% in 2008, while in urban areas, the coverage of water increased from 54% in the 2000s to around 65% in 2008 (Poverty Eradication Action Plan, 2004/5-
2007/8). As such, it’s no surprise that the state of maternal health in Uganda is negatively impacted by the country’s inadequate state of water, sanitation, and hygiene. Telehealth
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solutions could help to bring maternal health services to areas where local health facilities
are ineffective and impaired due to poor WASH conditions and other barriers to the
delivery of health services.
The lack of adequate electricity supply is another major barrier to implementing effective health care delivery systems. Uganda’s energy consumption needs have increased over the years with the expansion of the economy. As a result, energy consumption has been diverted from other sectors in order to support the growing industrial base. The government agency responsible for energy distribution implemented a load-shedding scheme in the 1990s, a scheme designed to share energy among consumers by turning off electricity from some sectors or areas while maintaining supply in other areas in efforts to ration available electricity. Health care facilities haven’t been spared by the practice of load-shedding, as some hospitals and clinics faced periods of
sometimes more than two weeks without electricity. Consequently, it’s not news for most
Ugandans to hear their local health care facility delaying and rescheduling surgical
procedures with operating theatres impaired due to lack of electricity. This dire state of
affairs is further burdened by a lack of generators and/or solar energy at most health
facilities. Laboratories, offices, pharmacies, and other health care capabilities are also
impacted by the irregular supply of electricity. Likewise, the delivery of maternal health
services in Uganda is compromised by the inadequate supply of electricity. Telehealth
solutions can be used to connect areas where the supply of electricity is low or lacking by
stationing telehealth capabilities at facilities that have regular supply of electricity in
order to support those areas with irregular supply of energy. However, there would also
be a need for an alternative (but inexpensive) source of energy at the facility-in-question
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in the remote area receiving the patient, in order to allow for stronger connections to hubs
at a better-facilitated hospital that provides specialized care via telehealth.
The state of education in any country is a factor that determines the level of health
outcomes. UNESCO (2012) reported that the total adult literacy rate in Uganda was
70.2%, with males at 79.12% and females at 61.97%. Unfortunately, literacy is yet
another area where women lag behind men due to oppressive cultural norms, regressive
government policies, and other factors. Female enrollment for girls in primary education
is actually high, but begins to decrease at the secondary education level due to girls
dropping out by marrying early, becoming pregnant, facing poverty, or facing other
circumstances females face disproportionately more than males. Overall, the total adult
literacy rate in Uganda dropped from a high 82.63% in 2010 to 79.12% in 2012 (see
charts below). Illiteracy is a barrier to maternal health, as under-educated women receive
much lower rates of maternal health services such as antenatal care, general preventative
care, postnatal care, and family planning. Telehealth through mobile health (mHealth),
which relies on the use of mobile phones and other wireless communication devices,
could be deployed to mitigate the low level of illiteracy in Uganda, especially in rural areas, by educating women about their maternal health needs using a preventative approach. A research paper on the use of mHealth in low-income countries demonstrated that
mHealth has the potential to reduce inequalities in care through a variety of
applications that aim to facilitate the communication between clients and providers,
promote women's behavioral change, simplify and extend training, and assist in data
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collection; with the overarching aim to improve access to and quality of obstetric
care. (Colaci, Chaudhhri et al, 2015)
Figure 7: Education and Literacy in Uganda (UNESCO Institute for Statistics)
Research shows that 16 women in Uganda die each day from maternal-related causes.
In this praxis, the use of the term “maternal mortality” refers to the term “pregnancy- related death” which is defined as “the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the cause of death” per the International
Classification of Diseases (ICD-10). According to the 2011 Uganda Demographic Health
Survey (2011 UDHS), Uganda’s maternal mortality ratio was 438 per 100,000 live births for the seven-year period preceding the survey. This survey concluded that maternal death was responsible for 18% of all recorded deaths of women in the 15-49 age bracket in Uganda. Uganda has progressively registered moderate improvements in maternal health according to the 2016 UDHS with pregnancy-related deaths per 100,000 live births declining to 368 in 2016, compared to 438, 418, and 524 in 2011, 2006 and 2001, respectively.
The improvements in maternal death statistics highlighted above echo the push by the Government of Uganda (GOU) and the donor community to increase health care
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access as demonstrated by the surge in the number of antenatal care visits and number of births in health facilities. The number of women attending four or more antenatal care visits increased from 48% in 2011 to 60% in 2016 while the number of births in health facilities increased to 73% in 2016, up from 57% in 2011. However, the decline in maternal mortality in Uganda is still below target 5A of the Millennium Development
Goal (MDG) declaration which calls for all United Nations (UN) member states to reduce maternal mortality by 75% between 1990 and 2015. According to the 2015 Millennium
Development Goals Report for Uganda, the 2015 target for maternal mortality ratio was
131 while the target for the proportion of births attended by skilled health personnel was
100%.
This praxis provides corroboration confirming that rural areas in Uganda are disproportionately burdened by numerous obstacles in the delivery of health care than in urban and semi-urban areas. The rural health sector in Uganda is underfunded particularly in the areas of infrastructure development, doctor and nurse salaries, transportation, and information technology. Conclusively, telehealth can be applied to provide Uganda and other developing nations a direct path to formulate innovative solutions that could help to reduce inequities in maternal health outcomes.
2.2 Introduction to Telehealth
The U.S. Department of Health and Human Services defines “Telehealth as the use of electronic information and telecommunications technologies to support and promote long-distance clinical healthcare, patient and professional health-related education, public health and health administration. Technologies include videoconferencing, the internet,
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store-and-forward imaging, streaming media, and terrestrial and wireless
communications.”
The term “Telehealth” is seen as an all-encompassing classification that describes the use of digital technologies in health care delivery. On the other hand, the term
“Telemedicine” is ordinarily perceived as a subset of telehealth referring to the use of technology-enabled tools to provide remote diagnosis and treatment. Historically, the
American Telemedicine Association (ATA) used the term telehealth and telemedicine
interchangeably. Accordingly, the use of the term “Telehealth” is broad in scope while telemedicine is specifically curved out to denote remotely delivered technology-enabled
clinical care. According to The Center for Connected Health Policy (CCHP), a public interest organization that promotes telehealth, there are four different channels through
which telehealth can be used to provide remote healthcare services:
1. Live Videoconferencing (Synchronous): “Live, two-way interaction between a
person and a provider using audiovisual telecommunications technology.”
2. Store-and-Forward (Asynchronous): “Transmission of recorded health history
through an electronic communications system to a practitioner, usually a
specialist, who uses the information to evaluate the case or render a service
outside of a real-time or live interaction.”
3. Remote Patient Monitoring (RPM): “Personal health and medical data collection
from an individual in one location via electronic communication technologies,
which is transmitted to a provider in a different location for use in care and related
support.”
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4. Mobile Health (mHealth): “Health care and public health practice and education
supported by mobile communication devices such as cell phones, tablet
computers, and PDAs. Applications can range from targeted text messages that
promote healthy behavior to wide-scale alerts about disease outbreaks, to name a
few examples.”
Research studies show that telehealth can eliminate barriers to health care access including average distance to health care facilities, shortage of health care providers,
health care illiteracy, poor transportation infrastructure, high health care cost burden, and
poor health care quality. The use of telehealth to increase health care access is particularly
impactful in rural areas where inequities in health care are more pronounced. Research
also confirms that the use of telehealth is more effective in countries that rely more on
holistic policies to achieve optimization within their healthcare services delivery system.
The research findings supported by the review of the literature provides confirmatory
evidence to the effect that telehealth solutions in Uganda are more successful in urban
and semi-urban areas compared to rural areas where the healthcare delivery system is
generally feeble. Rural areas in Africa could have benefited more from telehealth solutions if it were not for the disproportionately entrenched difficulties faced by rural
areas with regard to inadequate infrastructure, high connectivity costs, limited awareness
of telehealth, and lack of adequate government support (Mars, 2013).
2.3 Impact of Telehealth
According to the World Health Organization (WHO) report on the second global
survey on eHealth (2010),
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“telemedicine holds great potential for reducing the variability of diagnoses as well as
improving clinical management and delivery of health care services worldwide by
enhancing access, quality, efficiency, and cost-effectiveness. In particular,
telemedicine can aid communities traditionally underserved – those in remote or rural
areas with few health services and staff – because it overcomes distance and time
barriers between health-care providers and patients.”
In spite of this, the adoption of telehealth in Africa has been slow. The WHO survey
(2010) found that the African and Eastern Mediterranean regions had the lowest
penetration rates of established telemedicine services, and a higher percentage of
informal telemedicine services compared to other regions of the world. This supports the
observation that the full impact of telehealth in Africa is unrecognized due to
underreported telehealth services. As such, the significance of measuring the contribution
of telehealth in improving health outcomes in Africa cannot be overstressed.
2.4 Telehealth in Africa
The acceptance of telehealth solutions in sub-Saharan Africa continues to be stifled by poor physical infrastructure and manpower limitations across the entire region. For that reason, the promise of telehealth cannot be viewed in isolation. The success rate of implementing an effective telehealth program is not contingent on just having the availability of technological infrastructure, but is also dependent on the level of technical skill and ability needed to maintain and use the technology. Other telehealth-enabling success factors include having a well-developed internet base, a stable supply of electricity, adequate funding, and reliable telecommunication services. The majority of
Africa’s population reside in rural areas and have a high burden of disease compared to
35
those who live in urban areas. According to Mars (2013), “telemedicine is seen as a
means of improving the quality of rural health care, increasing access to scarce
specialists, reducing transportation of patients to doctors, supporting rural doctors,
overcoming the shortage of doctors, delivering education and facilitating research.” The
2015 World Health Assembly resolution on e-health urged member countries to develop
long term strategic plans for developing and executing eHealth solutions within their
health systems, perceiving the benefits that could come from information and
communication technological innovation in improving health-care delivery, public health,
research, and closing the health inequity gap (World Health Organization, 2015).
Telehealth solutions provide a cost-effective strategy that could help to improve maternal healthcare access and quality in Africa.
2.5 Impact of Telehealth in sub-Saharan Africa
There is an increasing body of knowledge that continues to advocate for telehealth as the panacea to sub-Saharan Africa’s poor health service delivery system. The persistent negative impact of inequities in the healthcare sector within the sub-Saharan Africa region irradiate more when viewed through a rural-urban or high-low income dichotomy.
A number of telehealth benefits are discussed in a study conducted in four district hospitals in Mali (Bagayoko, Cheick, et al., 2014). The purpose of this study was “to evaluate the impact of telehealth on 1) the diagnosis, and management in obstetrics and cardiology, 2) health care costs from patients’ perspectives, 3) attendance at health centers located in remote areas of Mali.” The evidence put forth in this study confirms that implementing telehealth in low and middle-income countries is a practical and optimal solution in view of the far-reaching health inequities in sub-Saharan Africa. The
36
benefits discussed in this study were demonstrated through improved care, favorable
patient’s health expenditures and increased attendance in health centers. More
specifically, the authors stated that “telehealth activities contributed to improving medical
diagnoses in cardiology and obstetrics (92.6% of the cases) and the patients’ management
system on site (96.2% of the cases). The attendance records at health centers increased
from 8% to 35% at all project sites during the study period. Patients from project sites
saved an average of 12,380 XOF (CFA Francs) or 25 USD (U.S. Dollars) and a
maximum of 35,000 XOF or 70 USD compared to patients from neighboring sites, who
must go to the capital city to receive the same care.”
2.6 Lessons from the Use of Telehealth in Native American Communities and Rural Areas in Mongolia
The majority of Uganda’s population not only face the problem of having to seek health care services from neglected health care facilities, but must also travel long
distances to seek those services. The low physical access to health care facilities is
generally attributable to disparities in income, place of residence, and the average
distance traveled to the nearest health facility. The burden of low access mostly falls on
the poor and rural dwellers. According to Uganda’s Health Sector Development Plan
2015/16 - 2019/20, the physical access to health facilities, described as the percentage of
the total population living within 5 kilometers (3.1 miles) of a functional health facility was estimated at 72% (Ministry of Health, Uganda, 2015). The issue of low access to health facilities is a major contributing factor to the enormous health inequity gap in
Uganda.
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Just like Uganda’s poor and rural communities, Native American communities have also faced similar health inequities for generations compared to the rest of the general population in North America. A literature review study describing the use of telemedicine in rural Native American communities provides evidence of improvements in health outcomes from a cost, quality, and access perspective. This literature review study indicates that “for every dollar spent in telehealth, $11.50 was saved in travel and child- care expenses and without any decrease in quality” (Kruse, Clemens Scott, et al., 2016).
In this study, it was determined that telemedicine not only reduces patient travel costs but
also reduces the travel costs of health care providers in terms of the time it takes to meet
their patients. The time spent by Native Americans on travel to healthcare facilities
represented an opportunity cost in the form of lost wages incurred from absentia from
work. The high cost of ramping up on specialty care within the Indian Health System
(HIS), a U.S. Department of Health and Human Services (HHS) agency, could be
minimized by up to $36 billion a year by increasing reliance on telemedicine (Kruse,
Clemens Scott, et al., 2016). Uganda could also increase the level of productivity and
efficiency within its healthcare delivery system by optimizing health provider services
through telehealth.
Developing countries account for the majority of all maternal death cases reported in
the world. The following key findings provided by WHO demonstrate that the burden of
maternal mortality is driven by health inequities: “Every day, approximately 830 women
die from preventable causes related to pregnancy and childbirth, 99% of all maternal
deaths occur in developing countries,” and “maternal mortality is higher in women living
in rural areas and among poorer communities.” According to WHO (2015), the majority
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of maternal deaths result from preventable and treatable “complications during pregnancy
and childbirth.” In Africa, the double maladies of Malaria and HIV/AIDs during
pregnancy are some of the principal causes of maternal death.
The deductions proposed in a study conducted to investigate the impact of
telemedicine in promoting maternal and newborn health in Mongolia found that “the
early detection of pregnancy complications and timely management with the distance
consultation of an expert team had contributed significantly to the reduction of maternal
and newborn morbidity and mortality in project-selected provinces compared to non-
project areas” (Baatar, T, et al. 2012). Some of the specific results highlighted in this
study show “Improved Quality and Accessibility of the Maternal and Newborn Services,
including Emergency Obstetric Care (EmOC) in Selected Areas” (Baatar, T., et al.,
2012). Distance communication between specialists located in urban areas who were
remotely enabled to support local rural service providers enabled improved diagnoses and
patient management. Another benefit this study highlights is “improved networking
between rural and urban health professionals and different specialties” (Baatar, T, et al.
2012). This study also indicated that prenatal diagnostics (22.9%) was the most common
sought-after consultation by remote physicians, followed by newborn complications
(15.6%) and pregnancy complications (15.4%). Baatar, T., et al. (2012) provided evidence supporting improvements in the diagnostic capacity of remote physicians on fetal conditions, reduced complications during pregnancy, and childbirth. Specifically, during the period from 2005 to 2009, pregnancy complications decreased to 15.4% in
2009, down from 19.1% in 2005, as a percent of total deliveries, while child birth complications decreased to 9% in 2009 from 25.7% in 2007.
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Chapter 3. Research Methodology
3.1 Introduction
This chapter discusses the basis, strategy and design behind the research methods used in this praxis. First, a review of the literature was performed to support the theoretical argument of the research. The literature review discussion focused on maternal health issues in developing countries with special emphasis on Uganda, and the potential upside impact of using telehealth solutions to support health care delivery services particularly in remote and rural areas. Next, secondary analysis was performed on the 2012 Access, Bottlenecks, Costs, and Equity (ABCE) survey of health facilities in
Uganda. This survey sought to produce substantive data for improving cost-effectiveness and health equity in line with the priorities set by the Ugandan government. The facility survey was also informed by responses obtained from exit interviews with patients as they departed the sampled health facilities. The ABCE Uganda survey is conducted by the University of Washington Institute for Health Metrics and Evaluation (IHME).
3.2 Research Strategy
The research strategy of this praxis provides direction to support the ways and means taken to conduct research. The goal of this study is to determine if telehealth solutions can be applied to the health delivery system (HDS) in Uganda to improve maternal health outcomes. Secondary data analysis is conducted to address research questions of the data that are to a certain degree different from the original investigator questions. By relying on an existing dataset, researchers can address research questions that would have otherwise been cost-prohibitive compared to using prospective studies, according to
Gallin & Ognibene (2012). The facility survey which provided the secondary data for this
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research was executed with the intention of providing understanding of “costs of health
service delivery, facility-based characteristics of antiretroviral therapy (ART) programs,
patient perspectives, and health facility performance across different service-delivery
settings” (IHME, 2015).
Generally, this survey examined most factors that would normally determine the
efficacy of any health delivery system. These factors include: access, bottlenecks, costs
and equity. Access refers to the depth with which health services are available to the
population and can be used to measure the ease with which the population are using health facilities. The reason access is normally regarded as a major factor in measuring the efficacy of any health delivery system is rooted in the hypothesis that health services cannot generate the desired health outcomes if they cannot be accessed and used as originally intended. The survey measured access by collecting data on travel time to health facilities, user fees, and cultural preferences, among other factors. To the extent that health facilities are accessible with relative ease, individuals who seek health care services from these facilities may experience supply-side bottlenecks such as the lack of medicine, which would in turn moderate health outcomes. The survey measured costs incurred by facilities in the course of providing health services, and the costs incurred by patients for the care they receive. The survey also probed health equity issues by measuring the extent to which different segments of the population have access to health services, particularly within a rural versus urban dichotomy.
3.3 Research Design, Survey Data Definition & Data Analysis
The research design presents a general idea of the paths taken to perform the praxis research. Analysis of secondary data was performed on the 2012 Uganda Access,
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Bottlenecks, Costs, and Equity (ABCE) facility survey to address the research questions posed in Chapter 1. The ABCE Survey is a comprehensive facility survey administered in
Uganda by the Institute for Health Metrics and Evaluation (IHME) at the University of
Washington. The research study is based on relationship-based and comparative research
questions and hypothesis—hence the reason for adopting a research design reliant upon
statistical techniques, including multiple regression and analysis of variance (ANOVA).
This approach enabled the research to explore relationships between variables and to test
for differences between groups. In this manner, the study wanted to show that the
availability of a telehealth mobile clinic at a facility (X1) exerts influence on cost of care
(X2) and access to care (X3), which in turn influences maternal mortality rate at a health facility (Yi). The mortality rate at a health facility is the “dependent variable” and the
“independent variables” are the proxy variables representing cost of care (X2) and access
to care (X3). The main predictor variable is the “availability of a mobile clinic at facility
(X1).” Accordingly, mathematical models were formulated for each hypothesis.
To determine how the availability of telehealth mobile clinics at a given facility
interact with other variables, the study applied the principle of interaction in multiple regression and ANOVA. Observed interaction occurs when an independent variable produces a different effect on the outcome, depending on the values of a different independent variable. We analyzed the data looking to cross-examine whether the effect
of availability of telehealth services at a facility depends on the level of the other
independent variables, representing “cost” and “access.” The dataset was defined and
coded, and descriptive statistics conducted. The assumption of linearity was tested by
reviewing a bivariate scatterplot of the variables. Multivariate normality which assumes
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that residuals (predicted minus observed values) are normally distributed was tested by examining the distribution of residual values by reviewing histograms for the residuals.
Stepwise selection was used to scale down predictor variables to only those that account for much of the variance to help determine the level of significance of each predictor variable.
3.4 Research Questions
The delivery of effective and accessible maternal health services in Uganda is a demanding undertaking that continues to drag down performance of the country’s health sector as a whole. According to the Institute of Medicine (IOM) of the National Academy of Sciences (2001), effective health services goals should strive to enhance and promote the following six essential features: patient safety, effectiveness, timeliness, patient- centered care, efficiency, and equity. As presented and discussed in chapter 1, the research questions in this study explore if telehealth-enabled solutions can be applied to the healthcare delivery system in Uganda to increase access to maternal health services.
In addition, this research explores if there are differential impacts of telehealth use on identifiable regional sub-groups. This research gives due consideration to the abovementioned goals of health services.
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3.5 Research Hypotheses
The high-level hypotheses investigated in this study are presented below (see chapter 1
for the detailed discussion on the hypotheses). The hypotheses below were formulated
using the research questions discussed in chapter 1.
3.5.1 Hypothesis on the impact of Health Care Costs (H1)
Study Null Hypothesis Study Alternative Hypothesis
Hypothesis H10: There is no difference in Hypothesis H1A: Health facilities in
mortality rates per capita among health Uganda with high health care costs are
facilities in Uganda regardless of health associated with high mortality rates per
care costs. capita.
We hypothesized that health facilities with high health care costs are associated with high
mortality rates per capita, and introducing a telehealth model moderates costs and reduces
maternal death rates per capita.
The 2011 Uganda Health System Assessment report identified unaffordable health care costs along with limited financial and human resources as some of the cost challenges facing the healthcare system in Uganda. In addressing the impact of telehealth on health care costs, this research examined routine patient fees that are levied at health care facilities, as well as the dollar amount spent on health care staff salaries and wages in Uganda. This study hypothesizes that health care facilities with high health care costs are associated with high mortality rates per capita. Accordingly, introducing a telehealth model reduces mortality rates per capita.
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3.5.2 Hypothesis on the Impact of Health Care Access (H2)
Study Null Hypothesis Study Alternative Hypothesis Hypothesis H20: There is no difference in Hypothesis H2A: Health facilities in
mortality rates per capita among health Uganda with lower levels of access
facilities in Uganda regardless of the level barriers are associated with lower
of access. mortality rates per capita
Barriers to health care access in developing countries fall into three categories,
namely financial, structural, and cognitive barriers. According to Carrillo, et al. (2011),
the aforementioned barriers are reciprocally reinforcing, thereby affecting health care
access individually, or in concert. Carrillo et al., (2011) define structural barriers as those
barriers often experienced within the healthcare facility. These barriers include waiting time, transportation to healthcare facilities, multiple locations for tests and specialists, telephone access to providers, continuity of care, multi-step care processes, and operating hours of healthcare facilities. This research focuses on such structural barriers to health care access in Uganda. This study hypothesizes that health facilities with lower levels of access barriers are associated with lower mortality rates; consequently, telehealth tools that eliminate these barriers will increase health care access.
3.5.3 Mathematical Models
Multiple regression is a statistical modelling tool that enables the researcher to estimate the relationship between multiple independent variables and the dependent variable (Dekking, F.M., et al., 2005). As a prognostic study on the impact of telehealth on maternal health outcomes, the multiple linear regression mathematical model was
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adopted to describe the relationship between the dependent variable (Yi) and independent
variables (X1, X2, and X3). The model approximated the regression coefficients (β0, β1, β2,
and β3) which then explained the relationship between the dependent variable (maternal
mortality rate) and independent variables (telehealth, health care costs, and health care
access). The error term (residual) in the model specified the accuracy of the predictions
generated by the model (see chapter 4 for the discussion on regression diagnostics).
Accordingly, the multiple linear regression mathematical model utilized in this study
provided the basis for analyzing the hypotheses (hypotheses discussed in chapter 1).
Given the above assumptions, we formulated two mathematical models expressed as
= + + + ------
𝑖𝑖 𝑜𝑜 1 1 1 2 2 Where: 𝑌𝑌 𝛽𝛽 𝑋𝑋 𝛽𝛽 𝑋𝑋 ∗ 𝑋𝑋 𝛽𝛽 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 (1)
= Maternal Mortality Rate at ith facility
𝑖𝑖 𝑌𝑌 = Availability of a mobile clinic (telehealth) at facility
𝟏𝟏 𝑿𝑿 = An interaction effect between telehealth and health care
𝑋𝑋1 ∗ 𝑋𝑋2 cost
= + + + ------
𝑖𝑖 𝑜𝑜 1 1 1 3 3 Where𝑌𝑌 𝛽𝛽: 𝑋𝑋 𝛽𝛽 𝑋𝑋 ∗ 𝑋𝑋 𝛽𝛽 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 (2)
= Health Care Access Measure at a given facility
3 𝑋𝑋 = Availability of a mobile clinic (telehealth) at facility
𝟏𝟏 𝑿𝑿 = An interaction effect between telehealth and health care
𝑋𝑋1 ∗ 𝑋𝑋3 access
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The objective of this research was to show that the availability of a mobile clinic
(telehealth) at a facility ( ) exerts influence on cost and access, both of which then
1 influence maternal mortality𝑋𝑋 rates. Consequently, a significant interaction effect signals the role of telehealth in moderating the relationship.
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Chapter 4. Analysis and Results
4.1 Introduction
This chapter presents results from the secondary analysis of the 2012 ABCE Uganda facility survey. The statistical methodologies used in testing the stated hypothesis are discussed in detail at the beginning of this chapter to help lay the footing for the succeeding discussion of the results analysis and observations. The discussion on statistical methods also covers the approach taken to assess the data for normality, linearity and outliers. More instinctively, the researcher provides a discussion of the findings by ensuring the connections between the results and existing literature draws suitable parallels with the prevailing body of knowledge. The chapter also discusses the key contributions and the confines of this research study, while providing links to the research goals, hypothesis, and results. The chapter then concludes with an overview of all the ideas discussed herein.
4.2 Regression Diagnostics: The Assumption of Normality, Linearity, Homoscedasticity, and Outliers
This study used standard regression diagnostic techniques to visually check the following assumptions of linear regression: normal distribution of residuals (multivariate normality), linearity (confirm if the relationship between the dependent and independent variables is linear), and homoscedasticity (confirm if the variance of error terms are equal for all values of the independent variable). The Shapiro-Wilk test generated a P value of
0.624107.
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4.3 The Quantile - Quantile (Q-Q) Plot—Test of Assumption of Normality
The Q-Q plot technique was used to determine if the sample and theoretical data sets originated from populations that have the same distribution (assumption of normality).
We generated a normal probability plot of the residuals to test the normality of the error terms (see figure 8 below). The plot was constructed by running sample quantiles of the differences between the actual and predicted values (residuals) against theoretical quantiles (predicted values generated from the regression equation) on the x-axis. By using a visual check, the resulting relationship is approximately linear. Thus the hypothesis that the error terms are normally distributed is proper.
Figure 8: The Quantile - Quantile (Q-Q) Plot
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4.4 The Residual Plot
In order to identify non-linearity, unequal error variances, and outliers, a residual
analysis was conducted by constructing a scatterplot of residuals on the y-axis and
predicted values on the x axis (see Figure 9). That resulting plot appeared to generally bounce randomly around the line where “residual” equals zero, suggesting that the assumption of linearity is proper. Furthermore, the plot shaped into a crude horizontal band around the line where “residual” equals zero suggesting that the variances of the error are identical. With exception of one data point, no other residual was considered to be in aberration from the ordinarily-shaped random pattern of residuals, suggesting there are largely no outliers in the relationship.
Figure 9: The Residual Plot (Residuals versus Predicted Values)
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4.5 Results
4.5.1 Hypothesis on the Impact of Health Care Costs (H1)
Sub Hypothesis (Interaction Effect P-Value & F-Value Study Hypothesis between Health Results (See Table 3) Care Costs and Telehealth)
H10: There is no There is no a) Interaction effect Reject null
difference in difference in between Telehealth * hypothesis (H10) mortality rates mortality rates per Average User Fees for per capita among capita among health Maternal Services: (P = Null health facilities facilities in Uganda 0.004; F =8.59) in Uganda regardless of health b) Interaction effect regardless of care costs and between Telehealth * health care costs telehealth Average User Fees for
H1A: Health The existence of Caesarian Delivery (P This study accepts facilities in telehealth at health = 0.029; F =4.9) the alternative
Uganda with facilities in Uganda c) Interaction effect hypothesis (H1A) high health care moderates costs and between Telehealth * and concludes that Alternative costs are reduces mortality Average User Fees for telehealth associated with rates per capita Maternal Ultrasound (P moderates health high mortality = 0.0004; F =13.37) care costs which rates per capita positively impacts maternal health
We hypothesized that health facilities with high health care costs are associated with high mortality (maternal death) rates per capita. Accordingly, introducing a telehealth model moderates costs and reduces maternal death rates per capita.
The Uganda Health System Assessment Report (2011) identified unaffordable health care costs, along with limited financial and human resources, as some of the cost challenges facing the health system. In addressing the impact of telehealth on health care costs, this research examined routine patient fees that are levied at health care facilities,
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along with the dollar amount spent on health care staff salaries and wages in Uganda.
This research hypothesized that health facilities with high health care costs were
associated with high maternal death rates per capita. Accordingly, introducing telehealth
moderates costs and reduces maternal death rates per capita.
The following user fees paid by patients to health care facilities to access maternal
health services represented a measure for health care costs:
• User Fees—First ANC visit (USD)
• User Fees—Normal vaginal delivery (USD)
• User Fees—Caesarian delivery (USD)
• User Fees—Pregnancy tests (USD)
• User Fees—Maternity Ultrasound (USD)
• Average User Fees—Maternity Services (USD)
• Facility Charges User Fees
To test this hypothesis, we examined how existence of telehealth services moderates health care costs while controlling for type of facility (i.e., Health Centre II, Health
Centre III, Health Centre IV or Private Clinic). We also adjusted for facility location
(rural, semi-peri-urban or urban), how long the facility has been in operation, the catchment area as well as its management (externally managed by NGO, externally by government (MOH), both internally & externally managed, or internally managed (self- managed). We used multivariate regression analysis to examine seven cost-related measures, and the results are presented below. The models wherein we used each of the following health care cost measures were found to be generally significant (p-values
<.0001) as presented in Table 2 below.
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Table 2: Overall model fit using seven measures of health care cost
Health Cost Measure F-Value DF P-Value
User Fees - First ANC visit (USD) 7.78 (15, 125) <.0001
User Fees -Normal vaginal delivery (USD) 7.6 (15, 125) <.0001
User Fees - Caesarian delivery (USD) 11.09 (15, 125) <.0001
User Fees - Pregnancy tests (USD) 7.53 (15, 125) <.0001
User Fees - Maternity Ultrasound (USD) 10.71 (15, 125) <.0001
Average User fees - Maternity Services (USD) 9.32 (15, 125) <.0001
Facility Charges User fees 7.57 (15, 125) <.0001
By looking closer at how the existence of telehealth service moderates each of these
health care costs measures, we noted that this effect is only observed when we compare
User Fees - Caesarian delivery (USD), User Fees - Maternity Ultrasound (USD) and
Average User fees - Maternity Services (USD). For all these cost metrics, there is no main effect of existence of telehealth service on maternal death rate F(1,125) = 3.25, p- value=0.07); however, we observed a significant interaction effect between existence of telehealth service and Caesarian delivery fees F(1,125) = 13.4, p-value=0.0004);
Ultrasound fees F(1,125) = 4.9, p-value=0.03); and average user fees for all maternity services F(1,125) = 8.59, p-value=0.004). Presented below are results for the analysis of caesarian delivery cost.
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Table 3: Moderation of Effect of Existence of Telehealth Service with Measures of Health Care Cost
F- P- Interaction Effect Value DF Value Fac_Mobile*Average User fees - Maternity Services (15, (USD) 8.59 125) 0.004 (15, Fac_Mobile*User Fees - Caesarian delivery (USD) 4.9 125) 0.029 (15, Fac_Mobile*User Fees - Maternity Ultrasound (USD) 13.37 125) 0.0004
The model coefficients along with standard errors are presented in Table 4 below. As
presented in the table, maternal death rates are a function of caesarian cost and existing
telehealth services (t=3.66, p=.0004); this would indicate that the relationship between cost of caesarian delivery and maternal death rates depends on the presence of telehealth services (Fac_Mobile). The Point-Biserial correlation average coefficient between telehealth and the proxy measures of health care costs (caesarian delivery user fees, maternity ultrasound user fees, and maternity services user fees) was 0.208073, which indicates a positive correlation between the aforementioned variables.
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Table 4: Model Coefficients Using Cesarean Delivery Fees as a Measure of Health Care Cost
P- Parameter Coefficient SE tValue Value
Intercept 0.00067 0.000764 0.87 0.3835
User Fees - Caesarian delivery (USD) 0.00000 8.97E-06 0.19 0.853
fac_mobile No -0.00045 0.000249 -1.8 0.074
fac_mobile Yes 0
User Fees*fac_mobile - No 0.00004 1.13E-05 3.66 0.0004 ***
Facility Type - Health Centre II -0.00008 0.000604 -0.13 0.8952
Facility Type - Health Centre III 0.00045 0.000641 0.69 0.4884
Facility Type - Health Centre IV 0.00009 0.000791 0.12 0.9053
Facility Type - Hospital 0.00439 0.000962 4.56 <.0001 ***
Facility Type - Other -0.00026 0.003154 -0.08 0.9351
Facility Type - Private Clinic 0
Facility Location - Rural -0.00046 0.000542 -0.85 0.3977
Facility Location - Semi-/Peri-urban -0.00054 0.000643 -0.85 0.3996
Facility Location - Urban 0
Facility years of operation 0.00001 6.5E-06 1.23 0.2199 Facility Management - Externally Managed - NGO 0.00021 0.000385 0.54 0.5911 Facility Management - Externally- Government(MOH) 0.00004 0.000385 0.1 0.9224 Facility Management - Internally & Externally Managed -0.00002 0.000456 -0.04 0.9658 Facility Management - Internally (Self) Managed 0
Catchment Area 0.00000 8.91E-10 0.48 0.6298
As cost of health care increased, so did maternal death rate, but the rates were lower among facilities with telehealth service (Fac_Mobile = yes) as shown in the graph below
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(Figure 10). These results support the hypothesis that high health care costs were associated with high maternal death rates, and by consequence, introducing a telehealth model would lower costs and maternal death rates. We reject the null hypothesis in favor of the alternative hypothesis (p < 0.05; see table 3). Accordingly, this study accepts the alternative hypothesis (H1A) and concludes that telehealth moderates health care costs which positively impacts maternal health.
Figure 10: Interaction between Telehealth and User Fees on Maternal Death Rate
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4.5.2 Hypothesis on the Impact of Health Care Access (H2)
Sub Hypothesis P-Value & F- (Interaction Effect Value (See between Access Result Study Hypothesis Table 5) Barriers and
Telehealth)
H20: There is no There is no Interaction Reject the null hypothesis
difference in difference in effect between (H20) mortality rates per mortality rates per Telehealth * capita among capita among health Facility Null health facilities in facilities in Uganda Location: (P = Uganda regardless regardless of the 0.0002; F of the level of level of access =9.1) access. barriers (location) and telehealth.
H2A: Health The existence of This study accepts the facilities in telehealth at health alternative hypothesis
Uganda with facilities in Uganda (H2A) and concludes that lower levels of moderates access telehealth moderates access Alternative access barriers are barriers (location) barriers (location) which associated with and reduces positively impacts maternal lower mortality mortality rates per health. rates per capita. capita.
To examine the hypothesis that health facilities with lower levels of access barriers were associated with lower maternal death rates, we examined the relationship between presence of telehealth services (Fac_Mobile) and access.
The catchment area as represented by the population size served by a health facility and location is a measure that provides understanding of the level of health care utilization (access) with respect to the broad measures of health care access, such as the size of the health facility, average distance travelled to health facilities, travel time to health facilities, number of health care providers per capita, and the ease of access to
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health facilities. The lower the population size served by a given health facility, the
higher the access to that facility. Health care access was measured using the following measures: population served per capita district (catchment per district) and facility
location (rural, urban, and peri-urban)
When we adjusted for type of facility, management, and years of operation, we didn’t
observe any significant effect of telehealth presence on maternal death rates. Stepwise
regression was then used to select the main predictors of maternal death rates, namely
facility location, and type of facility. We then fit a final model that introduced telehealth
service as an interaction effect with facility location, and adjusted for type of facility as
well as on population served per capital district (catchment per district). The results as
presented in Table 5 below show significant main effects of telehealth (F (1,129) =7.99,
p=.005) and significant interaction effects (F (2,129) =9.1, p=.0002) between telehealth and
facility location. The Point-Biserial correlation average coefficient between telehealth
and health care access (location / catchment) was 0.182390, which indicates a positive
correlation between the aforementioned variables.
Table 5: ANOVA Table for Analysis Role of Telehealth on Access (location)
Source DF SS MS FValue pValue
Facility location 2 0.000196 9.8E-05 3.08 0.0496
Telehealth 1 0.000255 0.000255 7.99 0.0054 ***
Telehealth*Facility location 2 0.00058 0.00029 9.1 0.0002 ***
Type of facility 5 0.001827 0.000365 11.47 <.0001 ***
Population served per capita 1 5.06E-06 5.06E-06 0.16 0.6909
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The coefficients for the model are presented in the table below.
Table 6: Coefficients for a Model with Interaction Effects of Telehealth and Access (location)
Standardized Parameter Coefficient SE tValue pValue Coefficient
Intercept -0.000448 0 0.000943 -0.48 0.6352
Location - Rural 0.00083 0.16497 0.000902 0.92 0.3592 Location - Semi-/Peri- urban -0.000275 -0.04184 0.00118 -0.23 0.8164 *** Telehealth - No 0.003486 0.88843 0.001009 3.46 0.0007 Telehealth(N *** o)*Location( Rural) -0.004083 -1.15084 0.001036 -3.94 0.0001 Telehealth(N o)*Location(P eri-Urban) -0.002536 -0.33707 0.001448 -1.75 0.0822 Facility Type - Health Centre II 0.00004542 0.01362 0.000636 0.07 0.9432 Facility Type - Health Centre III 0.000736 0.20958 0.000633 1.16 0.2475 Facility Type - Health Centre IV 0.000378 0.05247 0.000718 0.53 0.5994 *** Facility Type - Hospital 0.005325 0.52396 0.000871 6.11 <.0001
Facility Type - Other -0.001954 -0.03702 0.003335 -0.59 0.5589 Population served per capita 0.000127 0.02761 0.00032 0.4 0.6909
As presented in the table above, when we adjusted for population served per capita, location of facility and type of facility, the introduction of telehealth services improved
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maternal death rates by 0.003486 (0.35% ± 0.10%). However, this effect varied with
facility location (t=-3.94, p=.0001). The observed interaction effects are presented in the graph below (Figure 11). As presented in the graph, when comparing rural and semi-peri- urban facilities, the introduction of telehealth services in semi-peri-urban facilities is associated with lower maternal death rates (0.04%) while introduction of the same in rural facilities is associated with higher death rates (0.13%).
Average predicted maternal death rate by location and telehealth service 0.40% 0.38%
0.35% 0.32% 0.30% 0.25% 0.20% 0.18% 0.15% 0.13% 0.10% 0.04% 0.05% 0.04%
Predicted Maternal Dearh Rate 0.00% No Telehealth Yes -Telehealth No Telehealth Yes -Telehealth No Telehealth Yes -Telehealth Rural Semi-/Peri-urban Urban
Figure 11: Maternal Death Rates by Telehealth Service and Location
These results support the view that when adjusting for population served, location of
facility, and type of facility, the introduction of telehealth services will lower maternal
death rates, but the impact will only be positive among facilities located in semi/peri-
urban areas or urban areas. Health facilities with lower levels of access barriers (low
population size per health facility) in semi-peri-urban and urban areas are associated with
lower mortality rates. We reject the null hypothesis in favor of the alternative hypothesis
(p < 0.05; see table 5). Accordingly, this study accepts the alternative hypothesis (H2A)
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and concludes that telehealth moderates access barriers (location) which positively
impacts maternal health.
4.6 Discussion of Results
After the results were analyzed, deductions where drawn in accordance with the
research questions. This study established that the introduction of telehealth services
helped to moderate health care costs which then lowered maternal death rates. The
analysis of the predicted death rates from this model revealed opportunities to introduce telehealth solutions. Figure 12 below shows predicted death rate by facility type and location. Within the chart, the circle size represents the number of facilities in a given category. The bigger the size of the circle, the bigger the sample size.
As presented in the chart (Figure 12), we observed that introduction of telehealth would be more impactful in rural (area 2) and semi-rural hospitals (area 3); and in health centers located in urban areas (area 1). The darker circles represent facilities with telehealth mobile clinics (telehealth services), and the lighter-shaded circles indicate lack of telehealth services at those facilities. In each of the regions denoted by the numbers 1,
2, and 3, the darker-shaded circles are above the lighter shaded circles indicating that the predicted death rate was lower in facilities with telehealth mobile services (lighter-shaded circles), hence the opportunity to introduce telehealth services (within that specific red- partitioned area) to help moderate maternal death rates at those facilities that do not have telehealth (darker-shaded circles). Further below, Figure 12.1 (a figure analogous to
Figure 12) shows the differences in predicted death rate between facilities that have telehealth services (lighter circles in Figure 12) and those that have no telehealth services
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(darker circles in Figure 12). Similarly, the opportunity to introduce telehealth appears in the areas represented by the numbers 1, 2 and 3 in Figure 12.1 below.
Again, Figure 12 and 12.1 articulate the same message.
Figure 12: Predicted death rate by facility type and location
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Figure 12.1: Difference in predicted death rate
The research study further observed that private clinics tended to have similar
maternal death rates (close to 0%) regardless of their location. The opportunity to
introduce telehealth services would be in hospitals (rural and semi-urban hospitals), as
well as urban health centers. However, these types of facilities are predominantly
externally managed (i.e., either by the government’s ministry of health or by a non-profit organization (NGO)), with externally managed hospitals recording a death rate of up to
4% among those without telehealth services, as presented below.
Figure 13: Management of Telehealth Candidate Facilities
This research study found that private clinics with telehealth services recorded lower
maternal death rates; this was an indication that tools from private clinics may be adopted
for telehealth models in candidate facilities. However, further examination of the private
clinic profiles revealed that only 45% of private clinics provide child delivery and
maternity services which explains the close to 0% maternal death rates. A look at the
profile of the clinics compared to the facilities qualifying as good candidates for
telehealth reveals that telehealth candidates are characterized by a high volume of
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patients. As presented in Table 7 below, the staff-to-patient ratio in private clinics in 1:35 and up to 1:50 in the candidate telehealth facilities.
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Table 7: Profile of Clinics and Telehealth Candidate Facilities
Private Clinic Telehealth Facility Characteristics (based on averages) (n=9) Candidates (n=29)
Amount spent on all personnel 50,462,444 784,713,732
# staff working at facility 12 95
Doctors (Medical Officers (MOs) and Specialists) 1 4
Clinical Officers (COs) 0 4
Nurses 4 39
Other medical personnel 2 13
Non-medical personnel 5 36
Inpatient beds 13 93
Number of outreach or home visits 34 216
Number of emergency department visits 0 319
Total inpatient visits 247 4875
Total outpatient visits 2950 77705
Pre-delivery, post-delivery and delivery beds 2 14
Total births 77 970
Total ANC visits 419 4760 Staff to ANC Patient Ratio 1:35 1:50
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Table 8: Profile of Rural and Urban Facilities
Rural Semi-/Peri- Facility Characteristics (based on averages) Facility urban Urban (n=76) (n=119) (n=39) 136,088,27 335,169,19 1,171,980,79 Amount spent on all personnel (UGX) 1 8 0
# staff working at facility 22 38 106
Doctors (Medical Officers (MOs) and Specialists) 1 2 8
Clinical Officers (COs) 1 2 6
Nurses 10 13 50
Other medical personnel 3 5 12
Non-medical personnel 7 16 30
Inpatient beds 24 33 103
Number of outreach or home visits 54 143 96
Number of emergency department visits 82 2 917
Total inpatient visits 1,304 2,128 7,743
Total outpatient visits 13,454 46,928 48,831
Pre-delivery, post-delivery and delivery beds 5 4 10
Total births 323 253 1,481
Total ANC visits 1,673 1,390 6,600
Staff to ANC Patient Ratio 1:75 1:36 1:62
Amount spent per ANC Patient 81,327 241,132 177,564
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Bringing new technology-enabled solutions, especially telehealth, to Uganda’s health
delivery system can help to address the challenges faced by this country’s health sector, particularly in terms of increasing access to maternal health care and reducing the cost of care. This research found that maternal death rates were affected by cost of care and that the introduction of telehealth services lowered maternal care costs. These findings align with existing literature, with respect to the role of telehealth services in reducing the cost
burden of health care, and improving health care access and quality.
However, as is the case with the rest of Africa, the majority of Uganda’s population
reside in rural areas characterized by a high disease burden, areas most in need of
telehealth services. The rural population in Uganda (as a percent of the total population)
was recorded as 84% in 2016 (World Bank Collection of Development Indicators, 2016).
This research found that the introduction of telehealth services in rural facilities did not
adequately moderate the high maternal death rates as when compared to semi-peri-urban
facilities. This variation in impact response is not surprising given the spending and
manpower gaps we observed among rural facilities. The staff to ANC (antenatal care)
patient ratio was 1:75 in rural facilities compared to 1:62 in urban facilities. Similarly,
spending per ANC patient in urban facilities was two times the amount spent per ANC
patient in rural facilities. These findings confirm the importance of developing holistic
telehealth solutions that could benefit traditionally underserved rural areas characterized by inadequate infrastructure and lack of adequate government support.
Strains in governance characterized by limited capacity and high financing costs
identified in the literature review herein may explain the evidence we found with regard
to the role of facility management in influencing maternal outcomes. This research
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observed that the opportunity to introduce telehealth would be in hospitals (rural and
semi-urban hospitals) as well as urban health centers. However, these types of facilities
were predominantly externally managed (i.e., either by the government’s ministry of
health or by a non-profit organization (NGO)). These findings suggest that autonomous
facilities were better positioned to develop and sustain telehealth solutions. More
investigation is needed to understand how the type of facility management promotes
telehealth solutions.
Table 8 above shows the stark disparity between rural and other health facilities. For
example, the amount spent per antennal care (ANC) patient in rural areas is lower than in
semi/peri-urban and urban areas. This research found that rural health facilities in general
are disproportionately under-facilitated when compared to semi peri-urban and urban areas. There is an opportunity to introduce more telehealth services in remote areas in
Uganda to help close the inequity gap. However, the introduction of more telehealth services in rural areas in and of itself is not enough to create sustainable positive health outcomes if rural areas continue to be under-facilitated. This research comprehends the opportunity to connect the national referral-specialty hospital (Mulago Hospital – which has more resources in Uganda) with remote rural health centers through internet technology by providing connectivity for mobile telehealth centers in villages so they can provide maternal health services. Telehealth services would save money that patients would have otherwise had to spend on travel and accommodation.
That said, this research recommends a telehealth model (see figure below) that focuses on screening patients at lower level facilities to assess whether patients are candidates for remote diagnosis and care using telehealth-enabled tools. Candidates at
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lower level health facilities who are not good telehealth-candidates would then be
referred to appropriate higher level health facilities with the ability to handle their health care needs (if care can’t be dispensed suitably via telehealth). This approach would allow for the optimal use of scarce resources by providing health care to patients where they live, thereby eliminating the need for patients in rural and remote areas to travel long distances to seek care at higher-level health facilities predominantly located in Uganda’s capital city, Kampala.
Figure 14: Telehealth Model Process Flow
There are hub and spoke sites in any telehealth service system. A health facilitator
(usually a health provider who is not a doctor) at the spoke site remotely connects the
patient to the doctor/specialist at the hub site using telehealth-enabled technology like
live-video conferencing. This research study recommends a telehealth model akin to the
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hub and spoke model (see Figure 15 below) to help connect doctors and/or specialists at
the Kampala-based Mulago National Referral Hospital (i.e., hub site) to remote locations
(spoke sites). The retention level of doctors and specialists in rural areas is very low due to the poor infrastructure of rural health centers, and the lack of appeal of rural areas in general. Without access to modern-day conveniences such as good schools, doctors feel they cannot sustain a good standard of living in villages. Doctors and other highly trained professionals shun rural areas because of personal career development concerns, as they perceive that rural areas would professionally insulate them from career growth and development.
The proposed hub and spoke telehealth model would take advantage of Uganda’s better facilitated Mulago National Referral Hospital to provide maternal services to rural dwellers via telehealth-enabled technology. In essence, the hub would be the national referral hospital (Mulago) in Kampala, where the doctor or specialist healthcare provider would be located at the time care is provided via a telecommunication system. The spoke would be a rural or remote area where the patient would be located at the time care is provided via a telecommunication system. A nurse or other qualified healthcare provider would be present at the spoke site to provide triage and other assessment services, and to facilitate delivery of health care to the patient. Telehealth spokes sites would include primarily lower-level health care centers (HC I, II, III & IV), kiosks and mobile vans.
The goal is to connect the lower-level, district-based health services (HC I to HC IV) to the higher-level national referral hospital. This research noted that HC I to HC IV are the primary contact of rural and remote area-based dwellers with health care providers. In general, the hub and spoke model implies a number of sites where the “hub” is the anchor
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site staffed with doctors and specialists and the “spokes” would then provide the connection to the specialty sites (see figure below). This would help to mitigate the uneven distribution of health care workers skewed against rural areas (Uganda Health
System Assessment, 2011).
Figure 15: Proposed Hub & Spoke Telehealth Model Approach
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Chapter 5. Conclusions, Research Contributions, and Suggestions for Future Research
5.1 Conclusions
In conclusion, the acceptance of telehealth as an alternative choice in the effort to expand coverage of health care services in remote and rural communities continues to rise. The review of the literature supported by the research findings of this study demonstrate the potential benefits of telehealth in helping to close the health care inequity gap. This praxis establishes and asserts that telehealth has the potential to increase health care access, reduce transportation barriers and costs, improve disease management, and support early intervention.
This research provided confirmation that increasing the use of telehealth can stimulate the optimal use of scarce resources within the health sector, which in turn could help reduce the cost of health care. In broad terms, this study strongly endorses the adoption of telehealth as a major service delivery component within Uganda’s health care delivery system.
Consequently, the proposals offered here can be applied to help increase the number of Ugandan women covered by trained health care providers before, during, and after delivery, thereby helping to reduce the maternal death rate. The opportunity to introduce telehealth would be in hospitals (rural and semi-urban hospitals) and urban health centers.
In addition, facility management is critical in implementing effective telehealth interventions in Uganda, since autonomous (internally-managed) facilities were observed to implement more successful telehealth models in this study. In conclusion, the promise of telehealth as a disruptive solution now exists if the necessary resources are invested to
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champion this technology as a key problem-solving tool within Uganda’s health care delivery system.
5.2 Research Contributions
We recommend Uganda’s health sector policy to include a framework for capturing the knowledge generated through the use of telehealth. The interactions between patients and health care workers through telecommunication technologies creates knowledge that could be harnessed to drive innovation. Knowledge management matters to Uganda’s health sector for several reasons, including the need to capture expertise of employees who leave, share expertise, transfer best practices and lessons learned. Knowledge management helps to reinvent knowledge. The American Productivity & Quality Center
(APQC) defines knowledge management as “a systematic effort to enable information and knowledge to grow, flow, and create value (O’Dell & Hubert, 2011). In order to implement an effective telehealth-knowledge management program, the planning function at the Ministry of Health in Uganda should develop knowledge maps to identify relevant knowledge that can be harvested from the use of telehealth: “A knowledge map acts as a snapshot in time to help your organization understand what knowledge it has and what it lacks” (O’Dell & Hubert, 2011). The primary goal of an effective knowledge map is to direct attention to the most important knowledge within a system, so as to allow for its capture, storage and use in driving efficiency and innovation. Effective healthcare systems are very dependent on knowledge and its flow—which makes it important to integrate health care services delivery and knowledge capture processes. The quality of care can improve when health care providers are empowered to share the knowledge gained through the course of delivering care.
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Research shows that the integration of knowledge management in healthcare
promotes evidence-based medicine (EBM) and enhances the quality of care. EBM is
defined as the practice of involving the “integration of clinical expertise, patient values
and the best research evidence into the decision making process for the care of the
patient. Clinical expertise refers to the clinician’s cumulated experience, education and
clinical skills” (Sackett, 2000). EBM practices allow clinicians to take into account new
evidence while being collected, as patients share their experiences and stories with their
health care providers regarding their health issues. Accordingly, the quality of care
improves when health care workers use best practices and information gained through
knowledge management capabilities within the telehealth technology system. The
creation of knowledge and discovery is afforded by the following three pillars of EBM
coming together: patient values and preferences, best evidence, and clinical expertise (see
chart below). EBM also improves transparency and accountability within the health care
sector as health care workers increasingly share knowledge and best practices. Therefore,
the integration of telehealth technologies and knowledge management capabilities
enhances EBM practices which then drive better health outcomes. However, it’s
important to know that the implementation of knowledge management tools within the
telehealth system also depends on ensuring buy-in from health care workers and other stakeholders at all levels. Knowledge management programs are most effective when such systems consider people first. For example, Communities of Practice (CoP) have proven to be one of the most effective knowledge management approaches (O’Dell &
Hubert, 2011). However, the success of CoP’s in enhancing knowledge management depends on whether the organizational culture is suited to support knowledge-sharing and
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learning. A community of practice (CoP) can be defined as “a group of people who have a particular activity in common, and as a consequence have some common knowledge, a sense of community identity, and some element of overlapping values” (Hislop, 2005, p.59). CoPs succeed when they gain a critical mass of participants who have come together as a community to interact in support of a common purpose. This means that all stakeholders involved in the delivery of health services via telehealth have to come together for a common purpose so as to create a vibrant CoP within the telehealth system.
Whereas we recommend that the Government of Uganda and its partners should invest heavily in building information technology infrastructure to standup knowledge management tools (such as CoP platforms) within the telehealth system, it’s also important to note that employees are the anchors of these knowledge management tools, as opposed to the information infrastructure platforms through which knowledge is managed and propagated. For this reason, we recommend the initiation of training programs to ensure the vibrancy of a positive knowledge management culture within
Uganda’s health care sector. That said, knowledge management also depends on a leadership attitude and perspective that understands what makes people want to learn, share, and contribute. Such a leadership approach in which people are priority ought to be akin to the concept of transformational leadership which calls for leaders to inspire those they lead to perform better than their expectations. As such, the implementation of an effective telehealth system also relies on the quality of leaders within Uganda’s health care sector. More precisely, transformational leadership occurs “when one or more persons engage with others in such a way that leaders and followers raise one another to higher levels of motivation and morality. That people can be lifted into their better selves
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is the secret of transforming leadership and the moral and practical theme of this work”
(Burns, 2016). So, the philosophy of leadership within the health care sector matters in nurturing knowledge management capabilities within the telehealth system as a source of synergy, productivity, and innovation.
Figure 16: Integration of Evidence Based Medicine (EBM) and Telehealth (Sackett, 2000)
In spite of the promise of telehealth as an innovative technologically-enabled solution that could greatly improve health outcomes in Uganda and other developing countries, its acceptance in Uganda has not taken off swiftly. The reasons could be many but we can infer from this research study that the lack of resources, absence of a streamlined framework over the telehealth sector, limited internet penetration, limited computer literacy, poor internet security, poor road transportation system, and other human, social and technology-related barriers are to blame. According to Uganda’s 2013 National e-
Health Policy report, “most e-Health applications and products have been run in silos and are not interoperable or compatible, preventing sharing of information and services”
(Kiberu, et.al , 2017). For this reason, we recommend that the government of Uganda 76
develop as well as codify a comprehensive telehealth framework to oversee the
implementation of telehealth projects across the entire country, making sure that the roles
and responsibilities of all stakeholders are clearly defined. As an example of barriers to
the adoption of telehealth, Kiberu et.al, (2017) cite the Uganda National e-Health Policy report (2013) which indicated that Uganda does not have well-developed national guidelines responsible for the protection of electronic health information. Data privacy concerns, especially when it comes health records, is a barrier to the adoption of telehealth. When people don’t believe their private information will be protected when they interface with technological applications, they are less inclined to use that technology. Whereas the issue of data privacy is a real problem that warrants attention in and of itself, computer illiteracy can also drive irrational fear of imminent breach of personal health information. A good-sized number of people in Uganda are predisposed to staying away from using telehealth services as a result of negative propaganda. The
general lack of knowledge in technology and telehealth security in particular ensures a
fertile ground for the spread of misinformation. As such, telehealth programs are most effective if they include public awareness campaigns and training programs to counter negative information. We recommend the development of a comprehensive legal and regulatory framework to enhance data security in Uganda.
Whereas Uganda’s level of internet penetration has increased with the
implementation of 4G broadband technology over the years, in their study on the state of
information technology and communication in Uganda health sector, Kiberu, et.al, (2017)
reported that internet penetration remains very low in rural areas. According to the
Uganda Government Annual Market Industry report (2018), internet penetration in
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Uganda was 45.4% in 2018. In this report, it was also stated that the proportion of
households with internet access in Africa was 18% compared to 43% in developing
countries, and 84.4% in developed countries. Even worse, the digital gender divide is
more disconcerting in Africa, with the percentage of women with access to the internet
25% lower than men (Uganda Government Annual Market Industry, 2018). The rapid
adoption of telehealth can only be realized with increased investment in information and
communication technologies. We recommend that the Government of Uganda expand the
coverage of high speed internet bandwidth across the whole country (but most especially
in rural areas), increase training in computer literacy, and continue to identify and invest
in opportunities that will help to digitally connect remote areas to urban areas. The
adoption of telehealth will be slow in taking off without a ubiquitous, effective, and
reasonably-priced broadband connectivity.
5.3 Future Research Recommendation – Impact of Telehealth in Consideration of Variations in Health Care Utilization
This study points out several barriers to health care utilization in Uganda, including
the long average distance to healthcare facilities, low health care expenditure per capita,
and lack of health professionals and facilities, particularly in rural areas. The review of
literature indicates that the majority of maternal death cases in Uganda could have been
prevented if not for lack of appropriate resources. The 2012 ABCE study revealed
variations in the use of maternal health care between regions, place of residence, cultural
norms, and socioeconomic status. These variations are observed over a stretched continuum of health care utilization metrics and are attributable to both social and economic factors. For example, we noted in this study that the average total number of antenatal care (ANC) visits in Uganda is driven by a number of elements and
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circumstances, including factors related to the user (e.g. literacy, age, cultural norms, income) or supply side effects (e.g. distance to facility, availability of health services), or an interaction between the factors. In addition, some parts of Uganda are still besieged by political conflicts, including war and terror. While this study recommends telehealth as the antidote that can help solve the health care inequity problem in Uganda, it does not address the conditions and circumstances under which telehealth would be the most optimal solution, given the variations between regions, place of residence, socioeconomic circumstances, and cultural norms. In light of the variations discussed above, this study accentuates the need to explore and evaluate the conditions and circumstances prevailing in Uganda’s healthcare delivery system with regard to the causes of the variations in health care utilization between different groups and regions across the entire country.
5.4 Future Research Recommendation – Impact of Telehealth on Recruitment and Retention of Health Care Professionals in Rural Areas
Bagayoko, et.al. (2012) argue that telehealth can help to increase recruitment and retention of health professionals in remote areas by reducing the isolation felt by rural- based professionals using informational technology (IT) networking solutions. By allowing professionals in rural areas the ability to stay connected with their peers and keep their knowledge current, telehealth could present an opportunity for urban-based health care providers to consider serving in rural areas. Similarly telehealth could also help to retain rural-based health care professionals. That being said, urbanization is a multi-pronged issue resulting from population changes, climate and environmental changes, land use reassignment, and rural urban migration. Telehealth is just one of several independent factors affecting the rate of recruitment and retention of health care
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professional in rural areas. More generally, the rural brain drain phenomena is a function of increasing urbanization.
According to the Uganda Bureau of Statistics (UBOS, 2014), Uganda’s urban population has steadily increased from about 1.7 million in 1991 to nearly 7.4 million in
2014. According to the World Bank (2015), this development now means that 18% of
Uganda’s population live in urban areas as of 2014 with the rate of increase at 4.5% per year, even with fertility levels progressively decreasing in urban centers. Overall, the level of urbanization in Uganda has been attributed to the increase in the number of urban centers, the transformation of previously rural areas into urban centers, and the increasing shift of labor force concentration from subsistence agriculture to high-productivity work such as manufacturing and services (see Appendix H for trend data in the level of urbanization). Whereas urbanization could pass along opportunities to those who move to cities, it has also created a vacuum in rural areas, and exacerbated health care inequity as more productive people depart for the cities. In fact, almost all young people who were born in rural areas in Uganda end up migrating to urban areas after they have had the opportunity to earn a college education, or even high school education to a lesser extent.
Moving to cities has long been the norm for rural Ugandans with aspirations for vertical mobility. As discussed above, telehealth is one of several factors affecting the rate of recruitment and retention of health care professionals in rural areas. The potential upside from having a better understanding of the role of telehealth and information technology in general with respect to its effect on the level of rural urban migration of health care workers supports a strong recommendation for further study. This understanding can help
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in developing a national strategy to increase the number of doctors, nurses, and other healthcare professionals in remote and rural areas.
5.5 Future recommendation: education, innovation and research.
Telehealth technology and capabilities can be used beyond providing health care services remotely. The potential for using telehealth technology applications as a channel to support education, research and data management is feasible. The role and impact of telehealth as a tool in training and educating health care workers and in promoting research and development was not fully investigated due to time constraints. As such, the application of telehealth in educating health care workers, and in fostering innovation research, is a topic deserving of research attention. This is especially important in a country like Uganda where investment in education and research in general remains very low. Uganda has only two major public universities that conduct internationally recognized research in health care. These universities, Makerere University and Mbarara
University, also house the only two leading medical schools in Uganda. However, they are inaccessible to most Ugandans, especially those in rural areas. The number of students admitted to study health care-related courses, including medicine and nursing at these universities, is not adequate given the lack of health care workers in Uganda.
Moreover, the students who get the opportunity to study at Makerere University and
Mbarara University are more likely to look for employment in urban areas after they graduate. Therefore, the need to identify innovative solutions (such as telehealth) to take health care-related educational services to rural areas is crucial to Uganda’s developing health care system. Telehealth can enable specialist health providers at telehealth hubs in urban areas, and unskilled health providers at remote locations, to have the opportunity to
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collaborate and learn from each other. Whereas the flow of knowledge can be two-ways in this scenario, health providers at remote locations stand to benefit more as they are given the advantage of learning from skilled and better facilitated specialists at superior health facilities.
This research established that most health facilities in Uganda lack basic equipment, tools, and technological capabilities. As such, the health care sector is largely labor intensive, especially in the rural areas and at lower level health facilities, such as health centers I, II and III. A large percentage of health care workers at these lower level facilities are volunteer Village Health Teams (VHTs). According to Mays et.al, (2017),
VHTs in Uganda have helped to increase access to health care, which has led to improvements in health outcomes. The impact of VHTs has been noticeable mostly in reducing under-five child morbidity and mortality, and also in the treatment of HIV,
Tuberculosis, and Malaria. Mays et.al, (2017) also found that the retention of VHTs would be greatly improved by fostering stronger partnerships and collaboration between
VHTs and other health workers. In this research study, we found that rural areas are mostly served by VHTs and other less-skilled paid health workers. Over the years, the scope of medical practice for rural health care workers who are not doctors has increased with the increasing shortage of doctors in Uganda. Some health facilities in Uganda without qualified doctors on their staff were actually providing maternal services (such as emergency obstetric care) that typically would require a trained doctor in a normal setting. Nevertheless, there are many other women in Uganda who still deliver at non- health care facilities, in their homes, or places of work under the care of unskilled traditional birth attendants (TBAs) and family members. As important as the VHTs and
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traditional birth attendants are for rural communities in Uganda, it’s conceivable to deduce that they are also very susceptible to instigating bad health outcomes, including maternal death due to their lack of sufficient training. Telehealth can be used to integrate
VHTs and TBAs in the maternal health services delivery system by remotely connecting them to specialist providers at better health care facilities, and by enabling training, supervision, and evaluation of VHTs and TBAs. Ultimately, telehealth can increase the retention of rural based health care workers—the importance of which cannot be overstated in the effort to promote better health outcomes in underserved rural areas. One
Ministry of Health report stated that “70% of doctors, 80% of pharmacists, and 40% of nurses and midwives are urban-based, serving only 12-16% of the population” (National
Health Policy, Ministry of Health, 2009). Telehealth can also provide the opportunity for partnerships and collaboration between diverse pools of health care workers in disparate settings that would otherwise not have been able to work together. Such collaboration and interaction can be nurtured to develop innovation through research and fortuitous discovery. Accordingly, the role of telehealth in promoting collaboration among health care workers, promoting research, catalyzing innovation and extending education to rural-based healthcare communities merits further research and discussion.
5.6 Future Recommendation: Telehealth and Quality of Care
Whereas this research study deduced that telehealth improves the quality of health care, no scientific tests were performed to confirm this affirmation. The evaluation of literature in this study provided theoretical substance and empirical evidence supporting the hypothesis that telehealth improves health care quality. The discussion and
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substantiation provided in this study of the benefits of telehealth in improving the quality
of care warrants further investigation. The World Health Organization (WHO) defines
quality of care as “the extent to which health care services provided to individuals and
patient populations improve desired health outcomes. In order to achieve this, health care
must be safe, effective, timely, efficient, equitable and people-centered” (WHO, 2016).
Based on this definition of the quality of care, future work on how telehealth systems can be used to promote the delivery of effective and safe health services to hard-to-reach populations merits scientific review. Conclusively, telehealth supports the timely delivery of health services by reducing the travel burden of patients who would have otherwise not been able to seek care due to lack of transportation.
This research provided evidence indicating that telehealth shows great promise in the work to close the quality of care gap that is attributed to consequences resulting from human failure. The lack of well-trained health care workers and overreliance on traditional nonscientific practices in remote and rural areas has been proven to negatively impact the quality of care. This has compromised patient safety for women and contributed to maternal death. According to the 2016-2020 Uganda Health Sector Quality
Improvement Framework and Strategic Plan (2016), a quality assessment study of 400 health centers IIIs and IIs conducted in 2013 indicated that 40% of diagnosis among children for malaria, tuberculosis, anemic malaria, acute diarrhea and pneumonia were inaccurate. The health centers in the study quoted above did not have any trained doctors on their staff. The 2016-2020 Uganda Health Sector Quality Improvement Framework and Strategic Plan (2016) also reported that 80% of maternal and neonatal conditions were not properly treated and managed. The poor quality of care at the facilities in the
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study cited above was attributed mainly to the technical unskillfulness of the health care workers, lack of evidence-based clinical practices, partial treatment care plans, and poor interpersonal skills. Research shows that telehealth has been proven to increase the quality of care and in promoting better health outcomes. According to the 2010 World
Report on Disability, the use of telehealth tools in delivering health care services leads to better clinical outcomes in general, especially in mental health, cardiac rehabilitation, orthotics, and cognitive rehabilitation (WHO, 2010). Accordingly, the role of telehealth in enhancing the quality of care, especially in rural-based health care facilities, deserves further research and discussion.
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Appendix B: Organization and Function of Uganda Health Care Services
Source: Uganda Hospital and Health Centre IV Census Survey 2014
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Appendix C: Roles at Various Levels of the Health System in Uganda
Source: Uganda Health System Assessment 2011
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Appendix D: Relative Fill Rates in 2010 and 2011 for Doctors, Clinical Officers, Nurses, and Midwives for five Facility Types
Source: MoH HRH Audit Report 2010; MoH HRH Audit Report 2011
95
Appendix E: Antenatal Care
Source: Demographic and Health Survey 2011
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Appendix F: Selected Health Financing Indicators for Uganda and Comparison to Average for Peer Countries
Source: Uganda Health System Assessment 2011
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Appendix G: SDG Goal 3 Goal 3: Ensure Healthy Lives and Promote Well-being For All at All Ages
3.1 By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live
births.
3.2 By 2030, end preventable deaths of newborns and children under 5 years of age, with
all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live
births and under-5 mortality to at least as low as 25 per 1,000 live births.
3.3 By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical
diseases and combat hepatitis, water-borne diseases and other communicable diseases.
3.4 By 2030, reduce by one third premature mortality from non-communicable diseases
through prevention and treatment and promote mental health and well-being.
3.5 Strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and harmful use of alcohol.
3.6 By 2020, halve the number of global deaths and injuries from road traffic accidents.
3.7 By 2030, ensure universal access to sexual and reproductive health-care services, including for family planning, information and education, and the integration of reproductive health into national strategies and programs.
3.8 Achieve universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for all.
3.9 By 2030, substantially reduce the number of deaths and illnesses from hazardous
chemicals and air, water and soil pollution and contamination.
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3.a Strengthen the implementation of the World Health Organization Framework
Convention on Tobacco Control in all countries, as appropriate.
3.b Support the research and development of vaccines and medicines for the communicable and non-communicable diseases that primarily affect developing countries, provide access to affordable essential medicines and vaccines, in accordance with the Doha Declaration on the TRIPS Agreement and Public Health, which affirms the right of developing countries to use to the full the provisions in the Agreement on Trade
Related Aspects of Intellectual Property Rights regarding flexibilities to protect public health, and, in particular, provide access to medicines for all.
3.c Substantially increase health financing and the recruitment, development, training and retention of the health workforce in developing countries, especially in least developed countries and small island developing States.
3.d Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risks.
Source: WHO, Sustainable Development Goals (SDGs)
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Appendix H: Number of Urban Centers by type and Urban Population, 1991– 2016
Source: Uganda Bureau of Statistics (UBOS), 2014
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