Challenges of e-Health IS Implementation and Use in SA

While logical pathways have been laid down to cautiously plan and direct implementation processes, the 6^th key consideration in Figure 3 – providing the appropriate infrastructure is arguably the most important factor underpinning the success of e-Health IS implementation.

The implementations of e-Health IS fall short in data aggregation and reporting components, with negative implications on the data quality in the healthcare sector (Snyders, 2013).

Explanations are that not all hospitals and clinics have computers and web-based versions of DHIS available in all the provinces (ibid). As a result of inadequate computer units, data had to be imported manually from various levels to produce a less than accurate national report (Garrib et al., 2008; Snyders, 2013). For example, an assessment of the health information systems of South Africa reported that surveillance reports generated at the national level are not timely, neither are they complete; this therefore raised concerns about the quality of routinely collected data in the South African healthcare system (Statistics South Africa, 2009). To further buttress this growing concern, it was discovered in the routine health data for PMTCT (prevention of mother to child HIV transmission) submitted to the DHIS in 3 districts of Kwazulu-Natal that 50% of data elements were incomplete, and 87%

were not accurate (Snyders, 2013).

To further buttress the importance of infrastructure in e-Health IS implementation, challenges included a lack of basic amenities such as electricity, and the internet, which makes e-Health

11 Booking refers to the first and the most antenatal visit of a pregnancy (Horner et al., 2013).

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IS solutions difficult to access (Blaya et al., 2010; Coleman et al., 2011). As a result, ICT infrastructure in both urban and rural hospitals are not integrated to work together across hospitals to allow healthcare professionals to gain the optimum benefits of e-Health IS applications (Coleman et al., 2011).

Consequently, the heterogeneity of implemented e-Health IS have inhibited inter-operability between and has caused a drop in system efficiencies due to conflicting operational standards (Adebesin et al., 2013). For example, the PHCIS users in clinics can only read data but cannot make any form of alterations in the CLINICOM system, meaning that they cannot update data in the central system (ibid). As a result, sharing of data between CLINICOM and PHCIS systems is limited as users of these systems are not able to freely share data between their systems (Mchunu, 2013). Such inadequacies of connectivity inhibit access, communication and ultimately, the success rate of HIT implementations in the SA public healthcare facilities (Mostert-Phipps, Pottas & Korpela, 2013).

According to Cresswell et al. (2013) in Figure 3, the 7^th key consideration to achieve a successful systems implementation is to comprehensively train staff to enhance user skills.

The problem of inadequate staffing and a lack of technical skills amongst healthcare practitioners has been a growing challenge in SA’s public health institutions (Mbananga et al., 2002; Mchunu, 2013). The system usage complexity seems to be based on the computer literacy of some users even though there are a few who are comfortable in using the systems. For example, lack of computer skills to use the PCIS caused nurses to discharge patients on the paper-system, thereby caused a backlog in updating information to the PCIS hence, the systems are grossly under-utilized (Mbananga et al., 2002). The resulting outcome was failure to continue using the PCIS tools but rather, resolved to the predominant use of paper-based systems which is perceived to be more comfortable by healthcare practitioners. Consequently, this increased the workload of the already overburdened low number of staff who struggle with redressing the pressing health challenges and burden of diseases (BoD) (Cline & Luiz, 2013).

Likewise, security measures as regards patient information remain inadequate in e-Health systems implementations. Complaints are that there is no protocol or guidance on how to safeguard patient confidentiality in the use of these systems (Cline & Luiz, 2013). For example, once a staff logs on to certain systems, the user has complete access to a patient’s information irrespective of his/her specialization in the hospital (ibid). Loopholes in access control measures on the CLINICOM system have also been cited as perilous security threats (Mchunu, 2013). For example, observations by Mchunu (2013) indicated that users share their login accounts while some still retain their credentials and privileges based on their previous positions because their access profiles were not amended. This interferes with

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the accuracy of the system logs trails, hence a false reflection of who accessed the system and for what purpose.

Furthermore, since clinical support systems such as the BACIS have been costly to implement at the initial stage, one would expect a higher rate of utilization in healthcare centres that have acquired them if a return on investment is to be attained (Horner et al., 2013). Unfortunately, the BACIS is reported to be grossly under-utilized in implementing institutions. For example, instead of using the system to support clinical functions and also for administrative purposes, it is being used only for administrative in a number of institutions (Coleman et al., 2011; Cline & Luiz, 2013).

In terms of systems usability, the functionality of systems such as CLINICOM has also proven inadequate, mostly due to computer network congestion, slowness of the system and technical failures. This has seen the decrease in reliability, with negative implications on the system by the users (Mchunu, 2013; Mostert-Phipps et al., 2013). As a result, healthcare professionals such as doctors and nurses do not use the systems for clinical duties (Coleman et al., 2011). Instead, healthcare professionals feel they are left with no option but the use of paper-based systems to complete their clinical activities (Cline & Luiz, 2013). The same deficiencies also inhibit the functionality of the PACS, with frequent system downtime that limit access to, and use of, the system. For example, system downtime often disrupts interactions and issues of urgency between clinicians and radiologists, such that it even delays the laboratories from where the results are being processes (Black et al., 2011).

At first glance, it seemed as if both high and low-medium income countries made decisive and evident steps to achieve a successful implementation of e-Health information systems according to Cresswell et al. (2013) in Figure 3. Whilst the use of e-Health IS were intended to simplify processes to improve the efficiencies of service delivery in the public healthcare sectors, the complexities associated with systems implementation were major drawbacks causing otherwise. Report of evidences show that some of them have, unfortunately, impeded workflow of healthcare practitioners in an already overburdened public healthcare system (Mostert-Phipps et al., 2013). Arguably, this can be associated with a lack of cautious planning and adherence to mitigate imminent challenges that might result in low use and ultimately, systems implementation failure. Of major concern is the fact that despite the reported implementation and use challenges, there are only a few published scientific studies on the use of e-Health IS by healthcare professionals despite being listed as a part of the e-health strategy of the NDoH in South Africa (Horner et al., 2013).

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