About the Author(s)


Wesley Moonsamy Email symbol
Department of Informatics, Faculty of Engineering, Built Environment and Information Technology, University of Pretoria, Pretoria, South Africa

Shawren Singh symbol
Graduate Centre for Management, Faculty of Business and Management Sciences, Cape Peninsula University of Technology, Cape Town, South Africa

Citation


Moonsamy, W. & Singh, S., 2026, ‘Towards smart city planning from a healthcare perspective: A South Africa-based theoretical model’, South African Journal of Information Management 28(1), a2165. https://doi.org/10.4102/sajim.v28i1.2165

Original Research

Towards smart city planning from a healthcare perspective: A South Africa-based theoretical model

Wesley Moonsamy, Shawren Singh

Received: 10 Feb. 2026; Accepted: 23 Apr. 2026; Published: 30 June 2026

Copyright: © 2026. The Authors. Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Background: Rapid urbanisation in cities such as Johannesburg has caused severe congestion, pollution and issues related to accessing city services such as healthcare. The Joburg 2040 growth plan responds to these challenges through uplifting Johannesburg to a smart city by 2040.

Objectives: To determine how Johannesburg can achieve the Joburg 2040 growth plan objectives and to reach smart city status from a healthcare technology perspective.

Method: Thirty-one semi-structured interviews were conducted with public healthcare professionals in Gauteng, South Africa, to better understand digital health systems and processes related to emergency patient care and hospital occupancy.

Results: A qualitative interpretive analysis involving three cycles of coding led to the identification of 214 codes, 16 network relationships and six themes (connect disparate systems, combine data, communicate in real time, collaborate on patient care, cooperate on long-term objectives and contain security threats). The themes were incorporated into a theoretical model (theoretical model for achieving smartness in healthcare), associating the six themes and a Live Healthcare Console, a system which was conceptualised in previous research.

Conclusion: For Johannesburg to become a smart city from a healthcare perspective, system designers should start by connecting disparate healthcare systems which would then enable downstream processes.

Contribution: This research considers smartness from a healthcare perspective and contributes a theoretical model which can be used as a reference for implementing a smart healthcare system.

Keywords: Smart healthcare; rapid urbanisation; Joburg 2040; live healthcare console; connect disparate systems; combine data; real-time communication; collaboration on patient care.

Introduction

Smart cities are either built from scratch or existing cities can be upgraded to smart cities by enabling six possible smart domains (environment, economy, governance, living, mobility and people) (Lai et al. 2020). Although 99 smart cities have been identified globally (Smart Cities World 2024), there is an unequal distribution of smart cities as most are in developed countries. South Africa plans to uplift Johannesburg (Africa’s richest city [Africa News 2024]) to a smart city by 2040 through the Joburg 2040 growth plan.

Johannesburg struggles with typical issues associated with rapid urbanisation which include congestion and an increased demand for infrastructure and technology (Kim 2022). This can lead to residents struggling to access city services such as healthcare. Emergency patient transport in particular is one critical and constrained healthcare service that has struggled to meet demands (BusinessDay 2022; IOL 2022). Johannesburg therefore stands to benefit from smart city designs that use smart technology to optimise current healthcare processes. This research focuses on smart city designs from a (smart) healthcare perspective and follows a qualitative interpretive analysis approach. Thirty-one semi-structured interviews were conducted with healthcare workers from four out of the five healthcare districts in Gauteng, South Africa, occupying 15 job roles which can be classified as strategic, management and operational. The interviews were centred around the concept of a Live Healthcare Console (Moonsamy 2024) which is a conceptual system that can connect disparate digital healthcare systems to enable downstream processes. The analysis of the data led to the formulation of six themes (connect systems, combine information, communicate in real time, collaborate with team members, cooperate on strategic goals and contain security threats) which were associated to form the theoretical model. This research article commences with a literature review that considers five key areas: Smart cities (definitions and global viewpoint); Joburg 2040 (the plans to uplift Johannesburg to a smart city by 2040); The South African context (views expressed by other authors on the Joburg 2040 plan); Smart city, smart healthcare (achieving smartness in healthcare) and Theoretical models for smart healthcare (the use of theoretical models in expressing healthcare phenomena). The research method then describes how the data were collected and analysed. The results section explains how the six themes were derived, followed by the presentation of the theoretical model. The discussion section explains the theoretical model in relation to smart healthcare, followed by the conclusion.

Literature review

Smart cities

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).

TABLE 1: Distribution of smart cities.

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.

Joburg 2040

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,

Johannesburg – an economically vibrant and inclusive African city; strengthened through its diversity; a Smart City that provides high quality of life; a City that provides sustainable services for all its citizens; and a resilient society. (City of Johannesburg 2019)

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).

The South African context

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.

Smart city, smart healthcare

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.

Theoretical models for smart healthcare

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.

Research methods and design

Sample and sampling method

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.

Data collection strategy

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.

The research instrument

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.

Data analysis

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

TABLE 2: Summary of the data analysis steps.
Ethical considerations

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).

Results

Thirty-one stakeholders occupying 15 different roles (described in Supplementary Material [Moonsamy & Singh 2026]) within the public healthcare system were interviewed using a semi-structured approach. The 10 core questions (Moonsamy & Singh 2026) served to initiate the dialogue with the participants by serving as ‘icebreakers’. Interviews were conducted from Monday to Friday. The average interview length was 31 min, and the interpretive analysis resulted in the formation of 214 codes (determined during the first cycle of coding). During the second cycle of coding, associations between the codes were identified which resulted in 16 Networks (clusters of associated codes). The 16 networks were grouped in the third cycle of coding which in turn led to the identification of six themes. The composition of each theme has been presented in Supplementary Material (Moonsamy & Singh 2026). Pseudonyms have been used to protect the anonymity of the participants. No further information relating to the participants such as their gender, place of work, position, department or other have been presented to prevent reverse-engineering the identity of any participant. The comment is a concluding paragraph which summarises the setup and quotation (Weaver-Hightower 2015).

Connect

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.

‘No, the EMS does not run on our system.’ (Participant: A3)

‘No, no, I don’t think there’s a link at the moment.’ (Participant: A5)

‘Yeah, that’s the weakness of the divide. The weakness of the divide is that it doesn’t talk to the EMS.’ (Participant: A14)

‘I think there’s definitely the disconnect between EMS and the clinics in the hospitals in general, I feel that there should be a single system where it starts with the ambulance crews and the digital.’ (Participant: A19)

‘So EMS the dispatch system, everything like that is happening in one silo and then the hospital will have their own system [sic].’ (Participant: A19)

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.)

Combine

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.

‘They will send it on the dispatchers list.’ (Participant: A22)

‘So normally there is no alert that there’s no system [sic].’ (Participant: A4)

‘Currently, we’re not doing anything. There’s nothing. There’s no button that we are pressing to say, now we are on divert.’ (Participant: A5)

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.

‘We just put it as an occurrence as in like case notes [sic].’ (Participant: A21)

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.

Communicate

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.

‘I would want to really see the information on real-time… And you know, it’s always helpful to have that on real-time [sic].’(Participant: A15)

‘Definitely. I think especially from the dispatch perspective, if you could have a real-time view of hospital capacity, then I think you’re [sic], you know it can inform your dispatch decisions [sic]. You wouldn’t necessarily send a priority one patient to a hospital if the trauma unit is, let’s say full. And you know that the hospital will imminently announce that they are on divert for trauma cases. So you would rather advise the crew to move somewhere else.’ (Participant: A19)

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.

‘We have all the mode[s] of communicating with our crews. We have a tablet. We will communicate with them with WhatsApp. We have the phone, the recorded line when we send information that are vitals, that’s where we prefer using the phone because of now it’s on the recorded line. We have [a] two-way radios where we actually relay the message.’ (Participant: A21)

‘So there’s different WhatsApp groups.’ (Participant: A1)

‘Most of the information is transferred either telephonically (if the phone lines are working) or by WhatsApp based on the fact that the doctors have data.’ (Participant: A2)

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.

Collaborate

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.

‘Let’s say the patient is being transferred to us. I need let’s say it’s now being admitted to our step-down or whatever [sic].’ (Participant: A20)

‘For a femur fracture and there’s no space in the level one hospital because they don’t have capacity at all. They don’t have expertise. They don’t have resources to operate on such business. Such a patient belongs to a level two hospital where the patient needs to come immediately, even if the patient injury happened by the gate of that other hospital.’ (Participant: A28)

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.

Cooperate

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.

‘I think on the basis that they wanted to do it for the whole province, but that has not come to fruition.’ (Participant: A13)

‘But the cost of those issues are huge.’ (Participant: A2)

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.

‘And I think that some of the other provinces have implemented a digital system from the EMS perspective.’ (Participant: A19)

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.

Contain

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.

‘It’s hospital specific. So each hospital has its own bed management system that’s there [sic].’ (Participant: A6)

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.

‘Just that, you know, we are living in a like an era whereby anything is possible [sic], we have got a lot of cyber-attacks, those things [sic]. But then, according to security, somehow, I think we will like before [sic], like such thing happens [sic]. It’s like a security specialist can be involved [sic].’ (Participant: A5)

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).

Theoretical model for smart healthcare in South Africa

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.

FIGURE 1: Theoretical model for achieving smartness in healthcare.

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.

Discussion

For Johannesburg (and similar cities) to achieve smart city status by 2040, all six domains need to be enabled; however, from a healthcare perspective, smartness could be achieved by first connecting the relevant healthcare systems. A crucial finding of this research highlights that EMS and hospital digital health systems do not connect to each other. Communication is conducted manually via telephone (landline) which has the shortcoming of unreliability. If EMS systems were connected to hospital management systems through an integration platform provided by the Live Healthcare Console, operational data could be shared in real time between the systems. Communication between EMS and hospitals would then be benefited by timestamps, audit trails, reporting and other functions which would support management functions (collaborate) and promote strategic objectives (cooperate). On the ground, this would mitigate the risk of an ambulance arriving with a patient at a hospital that is on ambulance divert. The research also recognised patients (the general public) as key stakeholders in smart healthcare (smart health and smart people), yet the public is excluded from public digital health designs. Healthcare data and related processes are contained within systems which do not share data nor inform the public. Smartness in healthcare requires smart data to be shared with smart systems, with smart people, and for smart decision-making. Decision-making within the South African context could mean whether a mother takes her child to a clinic or hospital, whether an ambulance driver transports a patient to a regional or academic hospital or whether an MMO digitally approves a request to place a hospital on ambulance divert. To achieve the Joburg 2040 goals, it is therefore important to connect systems in a way that supports the sharing of smart healthcare data.

Conclusion

Joburg 2040 is a growth plan to uplift Johannesburg to a smart city by 2040. There are six domains that city planners must consider when upgrading cities to smart cities (smart environment, smart economy, smart governance, smart living, smart mobility and smart people). The six domains aim to reduce the effects of rapid urbanisation and also aim to realise the benefits of smart city designs. Since this research is classified as digital health research, the focus was on the smart living domain which was referred to as smart healthcare. Interviews were conducted with key stakeholders from the public healthcare system in South Africa. Through a qualitative interpretive analysis, six themes (connect, combine, communicate, collaborate, cooperate and contain) were derived. A graphical theoretical model named ‘Theoretical model for achieving smartness in healthcare’ was then used to express the relationship between the six themes and a Live Healthcare Console which is a conceptual system that integrates digital health systems. The theoretical model demonstrates how the Live Healthcare Console could connect fragmented digital health systems, combine data into a unified dataset and communicate the data in real time with key stakeholders. This can keep the public informed of critical updates to the healthcare system. Additionally, real-time information can help healthcare teams to collaborate effectively on patient care. Long-term objectives, such as balancing scarce healthcare resources, can be achieved through cooperation between strategic-level managers through the use of real-time information. Since South African digital health systems have been the target of cybercriminals, the Live Healthcare Console should contain security threats before they compromise the system and data. Implementing a smart healthcare system exceeds the introduction of connected technology alone, the user acceptance of new systems and processes (change management) also needs to be investigated to gain a better overall understanding of smart healthcare. The concept of virtual beds was briefly introduced in this article; however, this concept requires further investigation to understand how flexibility in hospital bed occupancy could be incorporated into existing smart healthcare designs. Future research can also consider the effect of the theoretical model on other major cities in South Africa and similar cities in Africa.

Acknowledgements

This article includes content that overlaps with research originally conducted as part of Wesley Moonsamy’s doctoral thesis titled ‘Digital health: A live healthcare console for public health in Gauteng, South Africa.’ submitted to the University of South Africa in 2024. The thesis was supervised by Shawren Singh. Portions of the data, analysis, and discussion have been revised, updated, and adapted for publication as a journal article. The original thesis is publicly available at: https://uir.unisa.ac.za/handle/10500/31888. The author affirms that this article complies with ethical standards for secondary publication, and appropriate acknowledgement has been made of the original work.

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

CRediT authorship contribution

Wesley Moonsamy: Conceptualisation; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Software; and Writing – review & editing. Shawren Singh: Conceptualisation; Supervision; and Writing – review & editing. All authors reviewed the article, contributed to the discussion of results, approved the final version for submission and publication, and take responsibility for the integrity of its findings.

Funding information

The publishing fees for this research article were funded by the University of Pretoria via the Research Development Programme.

Data availability

The data that support the findings of this study are available on Figshare at https://doi.org/10.6084/m9.figshare.31989414. The raw data are not publicly available due to the sensitive nature of the healthcare system.

Disclaimer

The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.

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