Contents of the pack and other information What DIFICLIR contains

In Kenya, the population is currently estimated at 44.61 million, which is more than four times larger than that of Rwanda (World Population Review, 2014). Unlike the Rwandan long legacy of political instability, Kenya has enjoyed a fairly peaceful political climate in its post-colonial history. As a developing country, nevertheless, Kenya is also dealing with a high unemployment rate, poverty and infrastructural underdevelopment. The rural population was last estimated at 76.02% in 2011 (Trade Economics, 2014) while the unemployment rate increased from 12.70% in 2006 to 40% in 2011 (Kenya Natural Bureau of Statistics, 2013;

Trade Economics, 2014).

Access to healthcare services remains a challenge for the majority of the poor, and its development is a priority factor for the state. Kenya continues to face health threats characterised by ravaging HIV/AIDS pandemics, spread of infectious diseases and malaria, high levels of infant mortality and maternal mortality, low levels of life expectancy and deteriorating (Gatero, 2011). HIV/Aids, in particular, represents one of the greatest public health challenge of redress, with over 1.6 million Kenyans reported to be living with HIV in 2011 (UNAIDS, 2011). In the same light, a high mother-to-child HIV/AIDS transmission and high maternal as well as infant mortality rates remain a major healthcare challenge in Kenya (UNAIDS, 2011). In line with the 1^st key consideration by Cresswell et al. (2013) in Figure 3, which is to clarify the problem(s) which a system is designed to solve, the Kenyan Ministry of Health (MoH) identified the problem of lack of access to healthcare services and the need to address this problem. Hence, the Kenyan Government set out to create easier access to healthcare services for her citizens through the implementation of e-Health IS tools.

2.5.2.1 Implementation of e-Health IS in Kenya

After identifying the problem in the Kenya public healthcare sector, the 2^nd key consideration in Figure 3 presents a need to build consensus among the different stakeholders. In this process, the government and the private sector collaborated to develop regulatory strategies to build a progressive system in the country (Makori, MiphMusoke & Gilbert, 2013). These strategies include the following policy frameworks: the Kenya ICT policy (2006), Kenya Communications Act (2009), strategic plan for health information systems (HIS) (2009-2014), and National standards and guidelines for creating electronic medical records (EMR) in 2010.

Consequently, these regulatory developments were synchronized with the national e-health policies, the national ICT policies, and in full consultation with healthcare workers and the users, in an attempt to develop a sustainable client-centred health system that is accessible to all Kenyans (Juma, Nahason, Apollo, Gregory & Patrick, 2012). The attempt by the

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government and private health sector to include stakeholders in the implementation of e-Health IS suggests a consensus was reached to address and build the healthcare sector.

After a consensus was reached, the 3^rd key consideration, according to Figure 3, was set in motion by the Kenyan MoH, which was to consider system options while also, adhering to the 4^th key consideration – choosing a system that meets clinical needs which is affordable.

To this effect, the Kenyan MoH started the nationwide deployment of an electronic system, the Open Medical Record System (OpenMRS) in 2006 (Mamlin et al., 2006), to combat HIV/AIDS and mother-to-child transmission (Seebregts, Mamlin, Biondich, Frasier, Wolfe, Jazayeri, Allen, Mirander, Baker, Musinguzi , Kayiwa, Fourie, Lesh, Kanter, Yiannoutsos &

Bailey, 2009). Of note is the computer-generated reminder feature on the OpenMRS, which helped healthcare practitioners to improve adherence to clinical guidelines to perform CD4⁶ blood tests and other clinical activities – which are essential to monitoring the health and treatment of patients with HIV and AIDS (Were et al., 2011).

Another example is the improvement on AMPATH⁷ Medical Record System (AMRS) whose implementation was aimed to cover all MoH healthcare facilities (Tierney et al., 2010). A positive impact on limited cases of implementation is cited. For example, accurately documented patient information became more secure and easily communicated among healthcare practitioners, with positive spin-offs on the diagnoses and treatment processes of infected individuals across the country (Seebregts et al., 2009; Juma et al., 2012). The bottom line is that regardless of ICT to evidently improve the quality and safety of healthcare service delivery in Kenya, the implementation of e-Health IS was accompanied by a multitude of use challenges, as observed in high income countries and the case of Rwanda in section 2.5.1.2.

2.5.2.2 Challenges of e-Health IS Implementation and Use in Kenya

As observed in the Rwanda context, the complexities associated with achieving a successful implementation of e-Health IS also manifest in the Kenyan context. Firstly, there was no adherence to standards, coupled with discrepancies and integration between the e-Health IS and ICT policies (Were et al., 2011). For example, a healthcare professional such as a family health worker might need to share health information with specialists for decision-making or in referral cases. A lack of coherent e-Health IS being used by different practitioners hinders easier, faster and accurate information access and sharing (Makori, MiphMusoke & Gilbert, 2013). This causes a backlog in the decision making processes and professional isolation of healthcare staff in seeking expert opinions in the healthcare field.

6 CD4 are lymphocytes- a type of white blood cell (AIDSMEDS, 2014).

7AMPATH - Academic Model for Providing Access to Healthcare

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According to the 5^th key consideration by Cresswell et al. (2013) in Figure 3, it is essential to plan appropriately. As a result of cautious planning, resolutions should either go with an incremental transformation or once and for all across the hospital. The challenge with the modest implementation progress of the OpenMRS seems related to resource limitations (Karuri, Waiganjo & Manya, 2013). For example, foreign aid seems to be the only source of funding for all reported implementation cases. The implementers of OpenMRS in Kenya might be constrained to run a parallel system (paper-based and electronic systems) due to the availability of funds. Subsequently, a parallel system tends to duplicate processes and increase medical errors, which are threats to patients’ safety (Cresswell et al., 2013).

The technology lifecycle phases in Figure 3 present the 7^th key consideration – have a plan to train staff. A shortage of human resource capacity, both in the healthcare profession and inadequate ICT Skills, is also cited as a challenge in the implementation of e-Health IS in Kenya. For example, Healthcare providers are overworked and overwhelmed, and given man’s characteristic of not being perfect, these type of environments heighten probability of making errors – with life threatening consequences (Mamlin & Biondich, 2005). Moreover, there seems to be inadequate ICT skills personnel in the public healthcare sector, such information technology (IT) maintenance staff that would train health practitioners (Pavalam, Jawahar & Akorli, 2010). The implications of inadequate staff training during and post-implementation of e-Health IS poses security risks to electronic patient information from both internal and external threats. These are due to lack of access control, which is a major aspect of every system that handles sensitive data and records of the public masses.

It is clear in this passage that Kenya has a fair share of socio-economic underdevelopment, healthcare challenges and intended national priorities. Similar to the Rwandan case (and to that of the high income countries), the Kenyan government was receptive to the adoption of Health IS to improve access to healthcare services. A deliberate effort to implement e-Health IS includes: policy frameworks, partnerships between the government, the private sector and the international development agencies such as USAID.

Nevertheless, the adoption processes of e-Health IS are complex, as claimed by Cresswell et al. (2013), yet with socio-economic under-development challenges in African countries, it makes an already complex process even harder with respect to achieving a successful implementation as observed in Rwanda and Kenya. Notable challenges of implementation in this respect include a lack of appropriate infrastructural base upon which solid systems can be built, financial resources to support the development and procurements. Furthermore, lack of ICT skills and personnel resources to operate and maintain implemented systems, a lack of adherence to local standards and deficiency in quality assurance.

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To further assess and understand the contexts of developing countries on their efforts to achieve a successful e-Health IS implementation in African countries, it is only fair to consider Nigeria, which is the most populated black country in the African continent before exploring a conclusive in the section 2.5.3.