New advances in medical science and technology have decreased the global burden of disease. However, low-income countries lack the necessary resources to provide for the healthcare needs of all their people. E-health systems have the potential to help low-income countries tap into the richer healthcare resources of more affluent countries, by providing cost-effective tools that can link them to global data management banks, clinical decision support organizations, and care-at-a-distance programs. However, to be effective, these resources must be used with care. The first step in prioritizing healthcare resources is to estimate the burden of disease. High-income countries have reliable systems to assess the causes of death in the population; however, low-income countries do not have such systems in place, and mortality rates from a specific disease have to be extrapolated from incomplete data. Several studies have approached the problem of estimating the burden of disease by using a variety of methods to determine which diseases are responsible for the most deaths, which countries are carrying the highest burden of disease and death, and which populations are at the highest risk of death. These data help the allocation of resources where they can have the greatest impact on the delivery of healthcare. Although the concept of e-health is relatively new, there is already evidence of the benefits of e-health in the management of data in developing countries, as well as of the benefits of an increasing number and variety of other e-health applications. The aim of this study is to evaluate the general impact of e-health in developing countries and to determine which e-health applications may be of special import in Nigeria.
Key words: burden of disease, health patterns, ICT
Chapter 1: Research Methodology
The burden of illness is increasing worldwide, and developing and transitional countries continue to carry the heaviest burden of disease. Although therapeutics and treatments are available for many chronic diseases that increase the risk of mortality and impact quality of life, many of these countries lack access to proper healthcare. There are many factors that affect the ability of developing and transitional countries to meet the healthcare needs of their people, including political, administrative, socio-economic, environmental, and geographical barriers. To try to address some of these problems, policy makers have proposed a number of solutions, some of which are centered round newly available technologies.
Many healthcare policy makers, administrators and providers are turning their attention towards two new technological applications that show much promise in promoting universal delivery of quality healthcare: e-health and m-health. E-health uses information and communication technology to manage healthcare, while m-health uses mobile technology. The main attractions of these technologies are their accessibility, affordability, implement ability, and universal application. The World Health Organization (WHO), the United States of America, and the European Union, are strong promoters of e-health and m-health, and have developed programmes to help underfunded countries incorporate these technologies into their health care systems. A few countries have begun taking advantage of their offers, and the first results coming in are promising. However, the great majority of developing countries continue to struggle within their broken and terribly inefficient healthcare systems.
1.2 Scope of the research
The scope of this study is to evaluate e-health system applications and platforms that can facilitate the management of medical and patient data, offer clinical decision support, allow healthcare from a distance, and promote medical research in nations within the African Region.
1.3 Aim of the study
The primary purpose of this study is to evaluate some of the e-health applications that have already been proven, or may prove, of value in the delivery of healthcare in developing countries, and to identify the barriers that are preventing more widespread application of the technology. The secondary purpose of this study is to attempt to find solutions to any of the problems identified, with particular emphasis in Nigeria.
This study will identify e-health applications that have been used with success to address specific illnesses or diseases that place a high burden of illness and/or increase the risk of mortality in developing countries. This study will focus on countries within the African Region and on Nigeria in particular. This study will also analyze factors that have been preventing wider application of this technology. Finally, it will determine how these factors could be addressed to clear the way for the establishment of successful e-health programmes, with special focus on Nigeria.
1.5 Research questions
What e-health programmes have been successfully instituted in developed countries that could be adapted for implementation across the African Region, especially in Nigeria?
What e-health programmes have already been successfully instituted in other countries within the African Region that could be expanded for implementation in Nigeria?
What are the most significant factors that are preventing African nations from establishing national e-health programmes to meet the healthcare needs of their people?
What are the most significant factors that are preventing Nigeria from establishing national e-health programmes to meet the healthcare needs of its people?
Successful implementation of e-health systems relies on socio-technical, economic, and political factors. Government support will have the greatest impact on the continuity of implementation of e-health systems.
This study will rely on surveys to attempt to measure localized e-Health activity in selected areas around Nigeria. One problem will be the identification of healthcare experts within those regions, and to then induce them to complete the survey. Another problem is that survey responses will by design be bases on self-reporting by the expert responder, particularly where open-ended questions are concerned. It will also be difficult, if not impossible, to verify the accuracy of their responses.
Moreover, there are wide variations in the definition of terminology and while the survey will be presented with detailed instructions, there is no guarantee that the respondents will rely on these instruction to complete the survey.
2. Global Burden of Disease
Science is an evidence-based endeavor, and health science is no different. The healthcare system must have reliable and consistent data on the burden of diseases to allocate its resources and develop health policies to eradicate these diseases. However, a system has yet to be developed that can deal with all the fragmentary data that is still coming out of many areas of the world, unreliable data which unfortunately comes from those areas in the world with the greatest need of consistent data. Information technology has the potential of playing an important role in filling the missing gaps of information. New technological developments have made it possible for even those with minimal training to gather and consolidate data, where in the past it was a task reserved for the highly skilled.
2.2Global Burden of Disease Analysis
Burden of disease analyses are central to health policy in several ways. Analyses of the demographics of disease help in the long-term assessment of performance within a country or region, or between countries and regions, and allow the tracking and judging of progress. Assessment of the burden of disease brings together a multi-disciplinary team of specialists, including epidemiologists and policy makers, whodebate values and priorities and determine national health policy. Knowing where the burden of disease is highest allows countries to prioritize and target specific diseases in need of intervention, like HIV/AIDS or malaria across the African Region, or poliomyelitis in Nigeria (Akom, 2008).
Burden of disease analyses can also guide the training of healthcare specialists for the delivery of healthcare interventions where the need is highest. Medical personnel are a limited resource and like any valuable resource they should not be wasted; effective use of human resources is especially crucial in countries with the lowest doctor/nurse-patient rations, like Niger and Sierra Leone, and many other countries in the African Region (Akom, 2008). In countries such as these, information-driven allocation of resources can generate the greatest good. Unfortunately, data is not always available and the majority of the information that is available is either not consistent, or not very reliable.
Murray and Lopez (1997) evaluated the 1990 mortality rates in eight regions of the world, and found there were no data available for 15 million out of the 50 million people who die each year worldwide. Nevertheless, there were methods that could be used to estimate the cause of death. This is possible if one examines the epidemiological patterns and characteristics of a particular community. For example, Murray and Lopez collected data from a variety of sources to estimate cause of death patterns for 107 different causes of death. The various sources were then collated and compared to compile a pattern and derive a holistic picture of mortality.The findings of their study showed that 98% of the deaths of children below the age of 15 occurred in the developing world. The probability of death in this age group was highest in sub-Saharan Africa, with a mortality rate of 22.0%, compared to a low rate of 1.1% in developed countries. Global deaths in 1990 were mainly due to non-communicable diseases (28.1/50 million deaths), followed by communicable and nutritional disorders (17.2/50 million deaths). Pediatric deaths were attributed to perinatal disorders (2.4/50 million deaths), diarrhea (2.9/50 million deaths), and measles (1.1 million/50 million deaths). Thus, half the leading causes of deaths were diseases that affect mainly children. This is particularly poignant because these diseases are largely preventable when access to healthcare is available and preventive methods followed. Injuries account for 10% of deaths around the world, but wide variations in the cause of these deaths preclude the assessment and management of data.
In 2006, Lopez et al. conducted a systematic analysis to evaluate the mortality, morbidity, and prevalence of 136 diseases and injuries for seven geographic areas of the world for 1990-2001, as well as 19 risk factors associated with these diseases.The results showed that out of 56 million people who died in 2001, 10.6 million were children, and 99% of them were from developing or transitional countries. Over 50% of the children deaths were caused by acute respiratory infections, diarrhea, malaria, HIV/AIDS, or measles. As high as these figures appear, the figures are 20% lower than the figures for 1990, except for the region in Sub-Saharan Africa, where the burden of disease increased due to the rampant HIV/AIDS epidemic. Half the disease rate was from non-communicable diseases and the leading factor was malnutrition. In addition, risk factors do not act in isolation but in concert with each other, thus 45% of global deaths are due to a combination of at least two risk factors. Overall, the burden of disease has improved around the world, although the numbers remain intolerably high.
Other studies continued to expand on the work of Murray and Lopez (1996). Mathers and Loncar (2006) conducted a study to project global mortality and burden of disease from 2002 to 2030 and found that Murray and Lopez had underestimated the impact of HIV/AIDS around the world. Mathers and Loncar projected future health trends using three scenarios; namely, baseline, optimistic, and pessimistic projections against data from previous studies. The advent of information technology (IT) technology has made data more readily available, although there are areas where the collection of reliable data remains elusive. In their study, Mathers and Loncar projected a shift in the burden of death from the younger to the older generation and from communicable to non-communicable diseases, as is now seen in industrialized nations. The risk of death for children less than 5 years of age is expected to fall by 50%. At the same time the study also projected a global rise in deaths due to HIV/AIDS, from 2.8 million in 2002 to 6.5 million in 2030. HIV/AIDS is projected to account for the largest number of deaths in developing and transitional countries by the year 2015, even under the most conservative baseline scenario. Of note, the fourth largest cause of death was projected to be due to road accidents. Figure 1(adapted from Mathers and Loncar 2006, e442) shows the estimated deaths in 2002 and the projected deaths in 2030.The vertical bars bisecting the points 2030 represent the range of deaths projections under the optimistic (7.5 million, age 45-59; 9.2 million, age 60-69) and pessimistic (11.5 million, age 5-59; 12 million, age 60-69) scenarios.
Fig. 1: Estimated 2002 deaths extrapolated to the year 2030
The authors acknowledged the limitations of their study and pointed out the transitional patterns of epidemiological characteristic of developing countries. Nevertheless, their projections seem more realistic than those in previous studies, as they took into account the aging of the global population, and used different scenarios by manipulating the same variables under various conditions.A more recent study by Mathers, Boerma, and Ma Fat (2009) also found that one-half of global children deaths are from the same four preventable and treatable communicable diseases described in earlier studies i.e., diarrhoeal diseases, prematurity and low birth weight, neonatal infections, and malaria. Their study also found that around 60% of global deaths occur from non-communicable diseases, again despite rising deaths due to HIV/AIDS.In addition, the study found major differences in the ranking of diseases between high, mid- and low-income countries. The main causes of pediatric deaths in low-income countries were infectious and parasitic diseases, specially malaria, and perinatal conditions. The top three causes of death for adults in low-income countries were lower respiratory infections, HIV/AIDS, and ischaemic heart disease (Table 1 adapted from Mather, Boerma, and Ma Fat 2009, p.20).
Table 1. The Ten Top Causes of Death in Low-Income Countries in 2004
Deaths in millions
% of deaths
Lower respiratory infections
Prematurity and low birth weight
COPD, chronic obstructive pulmonary disease; IHD, ischaemic heart disease; TB, tuberculosis.
*Countries grouped by gross national income per capita—low income ($825 or less)
Mather, Boerma, and Ma Fat 2009
In contrast, in high-/mid-income countries, 90% of deaths were due to non-communicable diseases or injuries (Tables 2a and 2b, adapted from Mather, Boerma, and Ma Fat 2009, p.20). The top three causes of disease in high-/mid-income countries were ischaemic heart disease, stroke and other cerebrovascular diseases, and lower respiratory infections. In the paediatric population, diarrhoeal diseases were the predominant cause of death. Tables 2a and 2b summaries the ten top causes of death in the world for all populations in mid and high-income countries respectively. The total number of deaths for all causes combined according to income was 26.3, 24.3, and 8.1 million deaths, for low-, middle-, and high-income countries, respectively.
Table 2a:The Ten Top Causes of Death in Middle-Income Countries in 2004.
Deaths in millions
% of deaths
Lower respiratory infections
Trachea, bronchus, lung cancers
Road trafic accidents
Hypertensive heart disease
COPD, chronic obstructive pulmonary disease; IHD, ischaemic heart disease; TB, tuberculosis.
*Countries grouped by gross national income per capita—middle income (> $825, < $10,066)
Mather, Boerma, and Ma Fat 2009
Table 2b:The Ten Top Causes of Death in High-Income Countries in 2004.
Deaths in millions
% of deaths
Trachea, bronchus, lung cancers
Lower respiratory infections
Alzheimer and other dementias
Colon and rectum cancers
COPD, chronic obstructive pulmonary disease; IHD, ischaemic heart disease; TB, tuberculosis.
*Countries grouped by gross national income per capita—high income (more than $10,066)
Mather, Boerma, and Ma Fat 2009
This difference in the patterns of diseases betweenhigh-mid-income and low-income countries reflects the differences in the demographics of mortality. The majority of deaths in low-income countries occur in the youngest population aged <15 years, whereas the majority of deaths in high-/mid-income occur in populations aged >15 years (Figs. 2-4).Figure 2 shows the death distribution by age in high-income countries. The majority of people (71%) in high-income countries lived beyond the age of 70.The predominant cause of death for this age group was chronic diseases, with cardiovascular and cerebrovascular diseases accounting for 15.6% and 8.7% of all deaths, respectively (WHO 2011). The only leading infectious cause of death was lower respiratory infections, causing 3.8% of all deaths (WHO 2011).
Fig.2:WHO 2011 death distribution by age and income.
Figure 3 (WHO 2011) show the death distribution by age in middle-income countries. Nearly half (45%) the people live beyond the age of 70; and, like high-income countries, chronic diseases were the predominant cause of death, with cardiovascular and cerebrovascular diseases accounting for 13.7% and 12.8% of all deaths, respectively (WHO 2011). However, unlike high-income countries, chronic obstructive pulmonary disease represented a significant cause of death, at 7.2%. Infectious diseases like tuberculosis and HIV/AIDS were also among the leading causes of death, at 2.4% and 2.7%, respectively. Diarrhoeal diseases accounted for 4.4% of all deaths, mainly in the pediatric population (WHO 2011).
Fig. 3: WHO 2011death distribution by age and income
The demographics are quite different for low-income countries (Fig.4); less than 20% of the population lived beyond the age of 70, and 40% died below the age of 15. Table 1 shows the top ten leading causes of death in low-income countries. Infectious diseases accounted for the majority of deaths, including pulmonary infections (11.3%), diarrhoeal diseases (8.2%), tuberculosis (4.3%), HIV/AIDS (7.8%), and malaria (5.2%), a similar pattern of diseases as that found by Murray and Lopez (1997) in their studyof the global burned of disease in 1990. The leading causes of deaths for mothers and infants are complications of pregnancy and childbirth, together accounting for close to 9% of deaths. Diarrhroeal diseases and malaria were also responsible for a significant number of pediatric deaths. These too corresponded to findings of earlier studies (Lopez et al., 2006; Murray and Lopez, 1997).
Fig. 4: WHO 2011death distribution by age and income
Table 3 summarizes the studies by Murray and Lopez (1997), Lopez et al. (2006), Mathers and Loncar (2006), and Mathers, Boerma, and Ma Fat (2009).
Table 3: Summary of Studies on Global Burden of Disease and Mortality
Region with greatest burden of death
Major causes of
Major causes of global death
Murray and Lopez (1997)
22.0% versus 1.1% in developed countries
Perinatal disroders, 2.4/50
Non-infectious diseases, 28.1/50; infectious diseases and nutritional disorders, 17.2/50
Lopez et al. (2006)
50% due to acute respiratory infections, diarrhea, malaria, HIV/AIDS, or measles
Malnutrition, leading factor;
Non-infectious diseases, 50%;
Mathers and Loncar
Diarrhoeal diseases, prematurity and low birth weight, neonatal infections, and malaria
Non-coomunicable, 59% 69%
Mathers, Boerma, and Ma Fat (2009)
Infectious diseases, 50%
However, the picture is even more complex because there still exist wide regional variations in disease patterns among the various countries within each of these three income categories, especially among low-income countries. Thus, in recognition of the inequity in health among the various regions of the world, and with the standardization of data collection and analysis in mind, WHO organized all countries into six designated WHO regions: WHO African Region, WHO Region of the Americas, WHO South-East Asia Region, WHO European Region, WHO Eastern Mediterranean Region, and WHO Western Paciic Region, roughly equivalent to the categories used in the Lopez et al. (2006) study. A comprehensive list of the countries within each region may be found in World Health Statistics 2011 footnotes pages 169–170.
Figures 5 and 6 represent the WHO 2011 global infant and adult death estimates, respectively,according toeach of the sixWHO designated regions, with the high-income countries from each region separated off as a seventh group, the High Income Region.In accordance with other studies (Lopez et al., 2006; Mathers, Boerma, & Ma Fat, 2009;Mathers&Loncar 2006; Murray & Lopez, 1997), the African Region carried by far the greatest burden of disease;where the mortality rate exceeded that of all other regions by a factor of 2-5, in both the paediatric and adult populations.
Fig. 5: WHO 2011 Global Death Statistics for Children 0-4 Years
Fig. 6: WHO 2011 Global Death Statistics for Adults 15-59 Years
Figure 7 represents the WHO 2004 estimated child mortality rates by cause and region; 99% of deaths occurred in low-income and middle-income countries.Prenatal conditions and diarroeal diseases account for 42% and 54% of all deaths in children under the age of 5 in most regions except the Africa Region (25%), where post-natal mortality rates due to malaria (16%) drove the numbers down (WHO 2004). The highest burden of death for children under five years was borne by the African Region, amounting to 4.7 million out of 10.4 million deaths (45%). The second highest death rate occured in the Eastern Mediterranean, at 3.1 million (30%), which means that the death rate in the African Region is more than double that of all but one of the other six WHO regions. Diarrhoeal diseases and respiratory infections were the two leading infectious diseases.
Fig. 7: WHO 2004 child mortality rates by cause and region
The ranking of mortality rates according to region differs for the adult population, where low and middle-income countries of the European Region have the second highest rate of mortality (Fig. 8). In addition, the difference in adult mortality rates between countries in the High Income Region and those in the six other regions is less pronounced than for child mortality, due in part to the presence of a large adult population in the High Income Region; except for the African Region, where AIDS/HIV drove the adult mortality rates up, toten times thatof the High Income Region.
Fig. 8: WHO 2004 adult mortality rates by cause and region
There were also wide variations within each of the WHO regions, although the widest variationswere found amongst countries in the African Region. Figure 9shows a breakdown of child mortality rates in the African Region according to country. A cluster of countries in West Africa between the Tropic of Cancer and the Equator, including Nigeria, Niger, Chad, Sierra Leone, and Liberia,hadsome of the highest levels on infant mortality in the world, with more than 150 deaths per 1000 live births (Fig. 9). This area lies within a challenging environment and is a hot pocket of parasitic and infectious diseases, like malaria, cholera, and meningitis, as well as a host of other diarrhoeal diseases, and HIV/AIDS (OECD 2008).
Fig9: Infant mortality in Africa; WHO, World Health Statistics 2007 Highlights and Table.
The usual gender differences in the pattern of diseases were also found, although HIV/AIDS claimed by far the most lives for either sex. The second most common cause of deaths for both sexes was other infections and parasitic diseases. The main difference between the sexes was in the third cause of death, where males tended to lose their lives to injuries, and females died due to maternal and nutritional conditions (Fig. 10).
Fig. 10: WHO 2004 adult mortality rates in the African Region, by sex and major cause of death group
2. 3 Problems of gathering primary data
As critical as the acquisition of these data is, there remains considerable controversy regarding the methods of collection and analysis, as well as the sources of data, especially in African countries. An important factor to consider is that too often, the cause of death remains unknown. It is hoped that new developments in IT technologies may prove useful in facilitating the collection and evaluation of data in areas that have largely remained out of reach to researchers trying to collect demographic and epidemiological data.
As far back as 1976, Ayeni (1976) decried the lack of adequate health data in Africa, including patterns of disease, the extent to which medical facilities are used, the populations affected, and morbidity. These data would help health administrators understand the current health status of the population in the country, increase the ability to detect changes in this status, and allow for predictions of health trends. Unfortunately, data is incomplete, and when available, there is lack of uniformity in the way it is reported. Ayeni suggested that data collection should be delegated to skilled personnel trained for that specific purpose.
In 1988, Adekolu-John conducted a statistical study on the health status of the Kainji Lake Area of Nigeria and found that 42% of deaths occurred in children below 10 years of age. The leading causes of death were malaria, diarrhea, and measles. There were also epidemics that accounted for sporadic spikes in death rates. One curious statistic is that the number of births in the hospitals exceeded the number of registered births and there were no data recorded for hospital deaths of infants, let alone for deaths occurring at home. The reason for this omission is that there was little awareness of the need to register these data for national concern. Non-indigenous people who moved into the area did attempt to register the births of their children, but neglected to register their deaths.
In 2003, fifteen years after the Adekolu-John study, Agundu conducted a study on the type of health statistics and the way these statistics were being collected and found that there is no systematic approach to the collection of data, as well as a general lack of appreciation for the significance of statistical data. Data for the study was collected from 120 senior public health officials in Nigeria. The officials had little knowledge of statistics and their relevance to their work and the data was simply filed away for some unknown future use.
Thirty years later, Okonjo-Iweala&Osafo-Kwaako (2007) were still concerned about the lack of proper statistical data on the health patterns and morbidity in African countries. The authors suggest that the deplorable statistics on the health of African nations is due in part to the lack of statistical data to guide the allocation of necessary, and scant, resources. Setel et al (2007) referred to this phenomenon as “a scandal of invisibility,” stating that people don’t “count” unless they are counted, and discussed socio-political and economic, as well as cultural factors that impact the delivery of healthcare in developing and transitional countries.
2.4 Potential role of IT in gathering data
People living in developing countries, particularly those living in the sub-Saharan African region, face the heaviest burden of disease. It is a crisis that is deepened by poverty and the skewed allocation of resources. Bukachi and Pakenham-Walsh suggested that access to new information and communication technologies (ICTs) can help improve the delivery of healthcare in these areas. In fact, healthcare workers are already using information technology with remarkable success as a means of communication, collaboration, to access health data including clinical information and records, and for continuing health education. However, one problem the authors of this study encountered is the lack of uniformity in infrastructure, and that different cultural contexts require different models and approaches, especially when patients represent a major part of the equation. Bukachiand Pakenham-Walsh suggested that a combination of old and new technologies would benefit healthcare systems, healthcare providers and patients alike.
2.5 Factors affecting the establishment of a national e-health system
E-health is rapidly emerging as one of the most powerful IT applications in medicine. It has the potential to enhance the delivery and continuity of healthcare by making medical care accessible to those separated by time, space, and money to the health care system. E-health applications can be used to target and manage chronic conditions that would otherwise go untreated, such as diabetes or cardiopumonary diseases. Since the early 1990s, e-health programs launched in developing and transitional countries by international concerns such as the Bill and Melinda Gates Foundation WHO, ISfTeH and the International Medical Informatics Association have been used to provide a wide range of healthcare services to populations lacking medical care. However, despite the success of programs such as DREAM, OpenMRS, and ZEPRS, widespread adoption of IT medical applications to improve quality of care and health outcomes and support conventional health care delivery has yet to be realized in the majority of areas with accessibility problems.
There are many factors that hinder the adoption of e-health technology including socioeconomic and political issues. It is difficult to launch an e-health system without the financial and policy support of local government. Governments that are able to use e-health to lower the economic barrier to healthcare through the convergence of technology and medicine are more likely to push for the adoption of e-health services. In addition, for any meaningful improvement in national healthcare, e-health services should be designed to provide universal and unlimited access to medical care, preferably under government support and control supported by private concerns. However, there are a number of issues that must be addressed when developing an e-health delivery system. First, patient characteristics are critical to the implementation of IT medical services. The patients’ needs and preferences must be matched with e-health service applications. It is also important to consider the patient’s ability to interface with the IT application relevant to the disease being monitored. Equally important is to evaluate the success of a particular application in delivering a medical service and to prioritize need. E-health clinical outcomes must be analyzed against conventional off-line medical care. In addition, e-health should not be viewed as a replacement to traditional healthcare but as a means of expanding current medical care services to improve patient outcome, prevent health crises, and reduce the frequency of return visits to hospitals and clinics.
Other factors affecting the adoption of e-health services include consumer perception of IT, the characteristics of organizational systems, and communication between the various stakeholders. Education is also a major barrier in consumer adoption of e-health. It is also difficult to expand e-health services from small to large-scale implementation without the technological knowhow. Understanding stakeholder perceptions can help the development of a strategy to incorporate e-health into routine healthcare. The readiness of patients, healthcare providers and organization to adopt e-health services is not in question; although there might be differences in stakeholder perceptions of IT, including the various applications associated with e-health. Attitude has been shown to have a significant impact on the adoption of e-health in the private healthcare sector, including trust, perceived usefulness, and feeling comfortable with the use IT.
But perhaps the largest barrier to the establishment of an e-health program is cost. Although the rising cost of medical care should motivate government and private agencies to take advantage of the medical and financial benefits of e-health, the issue remains as to who will shoulder the financial burden of developing an e-health system.
There are a number of issues that need to be addressed by a country wishing to establish a national e-health care system. First, the country must establish a national e-health policy or strategy, as well as a specific national ICT procurement policies or strategies for the health sector as a framework for the implementation of medical applications. Next, the government must allocate public funding for e-health programmes according to national healthcare needs. Governments should also promote private funding and public-private partnerships to support e-health programs. However, e-health programs cannot be established without ongoing support in the form of ICT training, as such, tertiary institutions should be encouraged to offer ICT training for health care professionals. Thus, there are many factors involved in the implantation of an e-health program.
2.6 E-health and the delivery of healthcare: summary
The literature review on the effect of information technology on health outcomes shows that e-health applications can have a significant impact on the delivery of healthcare. Some e-health applications support clinical decisions and laboratory analysis while others are concerned with data archiving and communication among participants separated by geographic, time, social and cultural barriers. E-health applications are now being implemented worldwide to evaluate the epidemiology of diseases and for disease surveillance across populations. E-health in developed in developed countries is more likely to use applications that target chronic conditions, whereas e-health applications in developing and transitional countries are more likely used for acute access to expertise. Developing and transitional countries have been quick to launch a number of ambitions programs with immediate and long-term impact on the outcome of community and individual patient healthcare. E-health systems also promote the self-management of healthcare and improve the outcome of chronic diseases like diabetes and HIV/AIDS. However, more information is needed regarding the long-term impact of e-health on the prevention and control of disease.
3. ICT Applications in the Healthcare Sector
Healthcare involves the collaboration of various medical organizations, institutions, and providers, all of whom manage their own data under different storage and retrieval systems, and though practical and efficient within the target system, there is a lack of uniformity in structure across other systems (Masudet al. 2012). Moreover, there are often variations in data compiled from the same resources. This lack of synergy between the various data storage systems, and the types of information stored, preclude the sharing of data among the various healthcare professionals, institutions, and organizations. E-health systems, on the other hand, allow the storage and retrieval of heterogeneous multimedia content data under a single global platform, facilitating interdisciplinary sharing of data. E-health technologies can be grouped into three main categories: (1) management of data, (2) clinical decision support, and (3) management of healthcare from a distance (Black et al. 2011). Successful implementation of any of these e-health technologies relies on the evaluation of a multitude of factors at each step of the execution process, in particular, socio-technical and economic factors. Government support is also important. In 2004, the United States President’s Information Technology Advisory Committee proposed a restructuring of the current healthcare information system to lower cost, reduce medical errors, and improve quality of care (Geissbühler 2012). The cornerstones of this proposal included electronic data storage and retrieval systems, clinical decision-support applications, computerized physician order entry, and inter-organizational data exchange. These technologies support e-health at each level of the hierarchy of the healthcare system: clinical, institutional, organizational, national, and global. Also in 2004, the CSIRO (Commonwealth Scientific and Industrial Research Organisation) and the Queensland Government together established the Australian e-Health Research Centre (AEHRC) for the purpose of establishing a national e-health system (Hansen et al. 2011). The aim of AEHRC is to improve delivery of healthcare, increase patient satisfaction, and reward healthcare workers. The main technological focus is on medical data, new clinical models, advanced medical imaging, and the development of medical skills. Queensland now has a tele-cardiac rehabilitation program, and advanced medical imagining technologies are being used throughout the Australian healthcare system.
3.2 Impact of e-Health in clinical systems
The use of e-health in the clinical setting is gaining widespread acceptance in developed countries, although there are wide variations in the scope and extent of their use. In the EU, Denmark, the Netherlands, Sweden, and the United Kingdom use e-health systems to store most of their clinical data, while in the United States, less than 20% of primary patient data are store electronically (Piette 2012). Cebulet al. (2011) compared the quality of care in 27, 207 patients with diabetes at 46 clinics in Cleveland, Ohio, and found that, regardless of the type of insurance held by the patient, practices that used electronic health records (EHRs) were able to deliver better quality of diabetes care than practices using standard paper records, suggesting that the use of EHRs can help provide higher quality of diabetes care. In New Zealand, the documentation of patients at risk of cardiovascular disease is poor, despite national recommendation guidelines for the management of CVD (Wells et al. 2008). The authors conducted a short study of e-health decision support in the clinical setting and found a four-fold increase in the recording of patient risk assessment data, suggesting e-health should be adopted in routine primary care practice to improve patient quality of care.
In addition to what is rapidly becoming conventional e-data storage and retrieval, Ibaida, Khalia, and Al-Shammary (2010) suggest that e-cardiology applications be combined with data hiding and watermarking techniques, to embed confidential patient information into the recorded ECG signals of the patient, since ECG data is large enough to host other information without compromising the primary data. The embedded information could then be retrieved separately. Furthermore, these data would be secure as it would be difficult for hackers to identify their exact location.
3.2.2 Developing countries
In Kenya, clinical laboratory order rates for CD4+ lymphocyte counts were significantly higher at clinics that relied on electronic data systems for automatic reminders, compared to control clinics (53% versus 38%) (Were et al. 2011). However, sporadic cuts in power supplies weakened the infrastructure and increased the risk of reliance on e-health delivery systems. Thus, unless provisions are implemented to address peripheral technical issues, there can be small hope for major advances in e-health in countries facing this type of technical challenge. For this very reason, Tawfik, Anya, and Nagar (2012) warn against the implementation of e-health across boundaries without first understating the differences in conceptual framework or the socio-technological challenges against which different clinicians must construct their medical decisions. The authors detail how the different work settings of primary care providers in the UK, the UAE, and Nigeria impact clinical decisions, thus any collaboration across borders should proceed with caution.
Scott, Ndumbe and Wooton (2005) conducted a study in Cameroon, where medical residents from Yaounde I University are sent out in the field to complete their training, often to remote and rural areas where medical resources are limited and far removed from their medical school environment. A significant number of residents (65%) relied on their mobile phones to contact a medical colleague for advice, and most wished they could have been able to reach a mentor before reaching a medical diagnosis, suggesting that e-health can be a cost-effective solution to help meet the healthcare needs of people at the fringes of the healthcare system. However, to be truly effective, an e-health system such as this should be developed in cooperation with all major stakeholders to maximize data access and continuity of care.