Although the definition for Smart Cities is not concrete (Balkaran 2019), Smart Cities may be described as cities that improve service delivery through the effective use of technology and employ smart methods to solve urban challenges (Kim 2022; Lai et al. 2020; Smart Cities World 2024) particularly brought about by rapid urbanisation (Kim 2022). Urban challenges such as increased congestion, pollution and insufficient infrastructure demand technology-driven solutions (Kim 2022). Lai et al. (2020) supports the definition of a smart city by highlighting the importance of data for improving not only service delivery, but also to stimulate economic development within the city. Dubai is an example of a smart city which aims to improve its air quality, preserve water resources (especially due to its arid location) and employ clean and renewable energy sources. Dubai’s plan would also promote the health of its current and future residents (AL-Dabbagh 2022). Although 99 cities have been identified as smart cities (Smart Cities World 2024), the distribution of smart cities by geographic location and the country’s economic status favours developed countries and countries outside of Africa and Asia. The distribution of current smart cities is summarised in Table 1 with further details in Supplementary Material (Moonsamy & Singh 2026).

Achieving smart city status is a mammoth task requiring several domains to be accounted for (Lai et al. 2020). Although smart cities are generally not built from scratch, Lai et al. (2020) present six domains which should be considered by smart city designers to upgrade cities to smart cities. These domains are: (1) Energy and Environment – Smart environment, (2) Economy – Smart economy, (3) Safety and security – Smart governance, (4) Health and living – Smart living, (5) Mobility – Smart mobility and (6) Education and government – Smart people. Further details are presented in Supplementary Material (Moonsamy & Singh 2026). This research approaches the concept of a smart city from a healthcare perspective, specifically for Johannesburg, South Africa. The following sections therefore present the Joburg 2040 plan and then focus on the opportunities for achieving smartness within the public healthcare system.

Johannesburg (also referred to as ‘Joburg’) is considered one of the wealthiest cities in Africa. It is home to the greatest number of US Dollar millionaires in Africa (14 600) (Africa News 2024) with an estimated population of over six million people (World Population Review 2024). The need for providing efficient services to a growing city and maintaining economic growth therefore contributed towards the conceptualising of the National Development Plan 2030 which is a detailed plan to promote living standards for all South Africans, especially those who are currently living under impoverished conditions (National Planning Commission 2014). The Joburg 2040 plan contributes towards the National Development Plan 2030 by focusing on the growth strategy specifically for Johannesburg. The Joburg 2040 vision states,

Despite the unequal distribution of smart cities globally (Table 1), South Africa plans to upgrade Johannesburg to a smart city through the use of technology and intelligent systems. Additionally, the Joburg 2040 plan shares components of the 17 United Nations Sustainable Development Goals (SDGs) which include efficient healthcare services – SDG 3 (United Nations 2024), New Urban Agenda which emphasises sustainable city designs (United Nations 2016), Agenda2063’s aspirations for a prosperous African continent (African Union 2023), the National Development Plan for uplifting South Africa (National Planning Commission 2014) and Transformation, Modernisation and Reindustrialisation (TMIR) which aims to transform and reindustrialise the Gauteng province (Gauteng Growth and Development Agency 2022).

Johannesburg aims to rebrand itself as a Smart City based on the Joburg 2040 plan (Bwalya 2019; City of Johannesburg 2019). Part of this implementation is to increase internet connectivity within the city. Although Smart Cities aim to introduce the concept of smart health, Johannesburg however must significantly step up efforts to create the infrastructure needed to support socioeconomic connectedness (Bwalya 2019) which includes connectedness within the healthcare system. Enhanced connectedness between healthcare systems and increased internet connectivity can, in turn, support the Information principle of the Batho Pele Principles by promoting access to information regarding available services (Moonsamy & Singh 2024c). Although several authors have argued the case for uplifting Johannesburg to a Smart City, Balkaran (2019) argues that a smart city in South Africa is a misplaced priority as the citizens would prefer an end to poverty – SDG 1. Balkaran (2019), however, also notes that citizens living in urban areas face challenges which include accessing healthcare services, which is a focus of this study. Additionally, Musakwa and Mokoena (2017) argue that although Smart Cities can have benefits, South Africans prefer efforts to be placed towards better economic prospects and an end to poverty – SDG 1 and SDG 2. A study by Mashau, Kroeze and Howard (2022), which aimed to assess smart city readiness from a municipality (small and rural), level identified 18 key factors related to smart city readiness of municipalities in South Africa. The factors that are of direct relevance to this research are internet connectivity, technology, infrastructure, data and public sector. Bandauko and Arku (2023) stress local or contextual relevance when implementing smart city concepts to limit further inequalities to citizens. Also noted by Bandauko and Arku (2023) is that although digital technologies and Information and Communications Technology (ICT) are critical to smart cities, ICT alone do not make smart cities; the social element must also be considered. Oke et al. (2020) argues that the smart living domain in South Africa is influenced by improving the delivery of healthcare services and also notes that video surveillance of citizens improves security within the city and thus supports individual healthcare. It is reasonable to assume that surveillance technologies require interconnectedness within the city.

The six domains of a smart city highlight the concept of health and living which has also been described as smart living. For this research, however, we refer to this concept as Smart Healthcare. Smartness in healthcare exceeds the use of intelligent devices and delves into other forms of technology such as the Internet of Things (IoT), 5G networking and Artificial Intelligence (Moonsamy & Singh 2024b; Syeda, Syeda & Babbar 2022) which supplement this description by arguing that a smart healthcare system should contain elements of connectedness between systems and people, combining data from different sources, communication between healthcare professionals and patients and collaboration amongst healthcare stakeholders. Angelidou (2017) outlines several characteristics of a smart city which include the ability to increase the outreach of city services, the ability to adapt to new applications of technology and to contain elements of being futureproof. Due to positive patient outcomes as a result of healing at home, Canadian hospitals such as Grand River Hospital and St. Mary’s General Hospital have launched programmes that allow current patients who meet a specific set of criteria to be cared for in their own homes (Williams 2024). This concept could be seen as the healthcare system’s ability to adapt to changing needs and for the city to increase its reach of city services. In South Africa, facilities such as Cure Day Hospitals are able to perform minimally invasive surgeries on patients and are able to discharge the patient on the same day (Cure Day Hospitals 2024). By introducing these concepts to the overall healthcare system, the system itself could be seen as adaptable. Hospital beds could, in turn, be reclassified as physical (patient occupies a physical bed overnight) and virtual (patient is still active on the system but is recovering in their own home and therefore not occupying a physical bed in a facility). The Grow Gauteng Together (GGT2030) plan calls for the introduction of smart digital public systems which can improve services, including healthcare (Gauteng Provincial Government 2019). By 2026, Johannesburg is expected to implement smart healthcare measures to reduce the prevalence of communicable diseases such as HIV, and by 2030, the city is expected to implement a healthcare system that is smart and efficient (City of Johannesburg 2019). The National Development Plan 2030 aims to transform the healthcare system by connecting disparate healthcare systems, decentralising authorities and transferring responsibility to lower levels of administration (National Planning Commission 2014). These aims could therefore impact the public healthcare system at the three main levels: Strategic – Healthcare decision-makers; Tactical – Facility and district managers; Operational – Healthcare workers at facilities and Emergency Medical Services (EMS). We have previously responded to the architectural concerns related to South Africa’s healthcare systems which do not display adequate connectedness (Moonsamy & Singh 2024a) and have suggested the development of a Live Healthcare Console to allow disparate public healthcare systems in South Africa to connect and share information (Moonsamy & Singh 2024c). This research contributes instead towards a more theoretical understanding of the synergy between people and healthcare systems and how this can support the notion of smart healthcare. The next section presents the importance of theoretical models in expressing ideas relating to digital health systems.

Digital health research focuses on data and technology (which can be referred to as Information Systems) related to providing healthcare services (Moonsamy & Singh 2024b, 2024c). Models can be used in the design of complex information systems because they can remove complexities (Moonsamy & Singh 2024c; Olivier 2004) and can aid in the understanding of the overall design. Several researchers have presented theoretical models to aid in the understanding of healthcare phenomena. Fortuna et al. (2019) present an empirical-based theoretical model on digital health interventions related to people who are living with serious mental illnesses. The model can serve as a foundation for understanding the peer support factors that affect the use of digital health interventions by people living with severe mental illness. A hierarchical theoretical model for medication adherence was created by Unni and Bae (2022). The model illustrates five levels which could lead to medication adherence for long-term illnesses. A theoretical model presented by Vargas-Peláez et al. (2017) includes the relevant stakeholders, policies as well as practices which affect perceptions towards patients taking medicines as a health need. The grounded theoretical model of mHealth data protection presented by Pool, Akhlaghpour and Fatehi (2020) describes contextual factors, mechanisms and outcomes related to data protection within healthcare. Although several theoretical models have been presented by researchers, models related to smart cities within the context of the South African-based healthcare system have not been directly addressed. This research focuses on healthcare resource management, specifically hospital bed occupancy, as this is related to patient movement and emergency medical service decisions. Healthcare data as identified earlier can serve to promote the smartness of the healthcare system and therefore needed to be better understood. During this research, we used an empirical approach to construct a theoretical model to support the uplifting of Johannesburg to a smart city from a healthcare perspective.

Collecting data from multiple stakeholder groups can vary the data, resulting in a myriad of interpretations (Sholl et al. 2019). Accordingly, data were collected from stakeholders who could be grouped into three categories. Strategic stakeholders use digital health data for addressing long-term objectives related to the overall healthcare system. Tactical stakeholders are managers who use digital health data to coordinate tasks directly related to patient care. Operational staff either directly involved in patient care or who capture healthcare information or generate healthcare reports to be used by other stakeholders. The research was conducted in Gauteng which is the smallest province in South Africa but with the largest population (Stats SA 2021). Ethical clearance was sought from all five research districts in Gauteng; nevertheless, four of the districts granted approval in time for the data collection phase.

The data were collected using semi-structured interviews. Purposeful sampling which has been defined as the ‘intentional selection of information-rich individuals’ (Ng et al. 2023) was the primary data sampling method employed for this research. Additionally, snowball sampling was applied as a secondary data collection strategy as it was anticipated that purposeful sampling alone would not yield sufficient responses. Snowball sampling is an appropriate supplementary data collection strategy as it can be used to recruit other potential participants (Zickar & Keith 2023). It was observed during the data collection phase that managers would identify individuals in their teams who would be appropriate participants.

Semi-structured interviews were used in this research as they allow the interviewer to add follow-up questions related to the original question (Stahl & King 2020) which in turn can enrich the responses received. Semi-structured interviews are used in collecting data for digital health (eHealth) research (Wronikowska et al. 2021). The research instrument, presented in Supplementary Material (Moonsamy & Singh 2026), contains 10 primary questions which were positioned to allow for follow-up questions. The research instrument was first piloted with three test participants who provided their feedback which was then incorporated into the final instrument.

The details of the data analysis are presented in Table 2.

Ethical clearance to conduct this study was obtained from the College of Agriculture and Environmental Sciences Health Research Ethics Committee (REC) (Ref. No. REC-170616-051).

Smartness in healthcare calls for digital health and other related systems to be connected to each other in a way that supports the sharing of healthcare management information. The following excerpts from participants highlight the disjointed nature of healthcare systems in Gauteng.

The participants noted that the hospital systems are not connected to the EMS systems. In the case of the emergency department, which interacts with EMS daily, the disconnect between the systems cause the healthcare workers to share information telephonically or via text messages (WhatsApp). The Communicate theme delves deeper into the communication mechanisms in use. Additionally, participants highlighted that internet connectivity (through WIFI) within the hospitals is poor and that healthcare workers resort to the use of their private devices. (The security risks of this practice have been noted in the Contain theme.)

The Combine theme which refers to combining relevant information from disparate sources builds on the Connect theme as the systems cannot combine information if they are not connected to each other. One critical use case for combining healthcare information is related to the load-balancing of scarce resources. When an emergency department has reached a critical capacity, the managing medical officer (MMO) has the authority to divert incoming ambulances to the closest available facility. This requires the hospital and EMS teams to synchronise their patient care activities. The disconnect between these systems (highlighted in the Connect theme) contradicts the condition of combining information.

The divert information is manually communicated (such as via telephone call) and is not system-generated. The relevant stakeholders, therefore, do not receive real-time notifications of the ambulance divert. The lack of a system-generated reference number for an ambulance divert results in a lack of digital evidence as noted by Participant A21 who captures the divert in the case notes of a file.

The case notes as noted above are not linked to ambulance divert reporting. The effects of the Connect and Combine themes result in additional communication between stakeholders, using in some cases, unofficial mechanisms such as WhatsApp. This is discussed in the Communicate theme.

Smart healthcare calls for effective communication amongst systems and people. Importantly, communicating in real time and communicating real-time information was highlighted by the participants. In some cases, a lack of efficient communication mechanisms led to the use of personal devices and communication mechanisms such as WhatsApp.

At least two participants highlighted that having access to real-time information would support them in their daily activities. However, as noted in the Connect and Combine theme, the lack of connectivity between systems causes healthcare workers to communicate with each other to obtain the information that they require. A lack of quality internet and WIFI access, however, leads healthcare workers to resort to the use of their own devices, data and the use of unofficial communication platforms.

The participants mentioned that WhatsApp is used effectively by several teams to communicate in real time using real-time information. They also noted that the use of WhatsApp is subject to them having enough data (paid for by themselves). They also noted that they share information with great care and sensitivity to patient privacy. The synergy between the various healthcare teams is proof of the collaborative nature of the healthcare system. The Collaborate theme is discussed next.

Hospital and EMS staff collaborate daily on cases where patients need to be transported from a scene to a hospital and from a clinic to a hospital. There are also cases where patients are transferred between step-up and step-down hospitals. When a patient shows signs of recovery, the patient can be transferred to a step-down facility to free up a bed in a higher-level facility. Conversely, patients requiring higher levels of care may be transferred to a step-up facility. The coordination of these types of patient transport and transfer processes is facilitated by the hospital staff (wards and emergency department) and EMS.

Healthcare professionals need to consult with teams in other facilities to determine whether they have the capacity to treat patients who require either step-up or step-down level treatment. Participant A28 refers to an example of a femur fracture. In such a case even if a lower-level facility is available, the patient may only be stabilised and must then be transferred to an appropriate level facility for treatment. This is also dependent on whether there is capacity at the higher-level facility. Collaboration is required on daily activities involving patient care, for longer-term objectives such as resource allocation, the relevant stakeholders must cooperate with each other to achieve these objectives. The Cooperate theme is discussed in the next section.

An MMO occupies a revolving role within a particular district and coordinates higher levels of resource management and decision-making including that of diverting ambulances. Real-time information is therefore vital for an MMO who needs to make key decisions which can affect multiple hospitals and EMS teams. Additionally, hospital Chief Executive Officers, district managers and technology professionals need to cooperate with each other on strategic decisions such as whether to initiate projects based on conducting feasibility assessments.

Participants A13 and A2 refer to the costs of digital health projects, which can be high and wasteful if they do not achieve desired outcomes. Participants noted that in other provinces such as the Western Cape, there have been advances in the healthcare systems which enable healthcare professionals to make decisions using real-time information.

Participant A19 refers to connectivity between EMS systems in the Western Cape province and other systems which enable decision-makers to balance resources based on up-to-date information. Connecting systems to systems, combining information and communicating between systems can, however, introduce opportunities for individuals to compromise the system and information. This concept has been highlighted in the Contain theme which is discussed next.

South Africa has been the target of cybercriminals in recent years (Kahn 2024; Reuters 2020). Some participants therefore highlighted the potential risks to connecting systems through a system such as a Live Healthcare Console. In addition to external threats, participants noted that access to information is based on access control policies which can limit information access. It was noted in the Connect theme that some healthcare workers resort to using their private devices due to the slow network access to the hospital. This poses additional risks as patient information may leave the boundaries of the public hospital network.

Participant A6 noted that access to information such as bed occupancy in another facility is not available even though SAP Health Information System (HIS) is a central system. This could be due to access control policies.

Participant A5 suggests that cybersecurity experts be added to the digital health team to guide the systems designers on how to safeguard systems and information. The six themes presented in this section were associated with each other and to the Live Healthcare Console based on the smart city principles to formulate a theoretical model (discussed in the next section).

The interviews were centred around the Live Healthcare Console, a conceptual system which contains elements of smartness such as connectedness through the use of IoT and 5G networking, combining of relevant information, communicating in real time with the right people at the right time and real-time collaboration amongst the key healthcare stakeholders. Since the purpose of this research was to understand how the Joburg 2040 vision could be reinforced from the smart healthcare perspective, the six themes presented above were related to each other and with the Live Healthcare Console which serves as a mechanism to support the themes. Additionally, patients who are at the heart of the healthcare system have also been included as the patients. The theoretical model is presented as Figure 1.

The Live Healthcare Console: (1) connects the disparate healthcare systems and (2) combines real-time data into a unified dataset. The data are then used by the Live Healthcare Console to support effective (3) communication in real time and with real-time information. Real-time information made available to the right people can serve to empower patients (general public or smart people) and enables (4) collaboration amongst the healthcare teams. A series of short-term collaborations then leads to long-term (5) cooperation to achieve strategic objectives. The Live Healthcare Console, being a system that houses real-time and critical information, could become a target for cybercriminals and should therefore (6) contain security threats by encrypting data and securing all endpoints.