Original Research

A framework for the integrated digital transformation of municipal healthcare services in South Africa: The case of Gauteng

Musawakhe H. Khumalo, Tankiso S. Moloi

Received: 14 Nov. 2025; Accepted: 02 Mar. 2026; Published: 30 May 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: This study develops a framework for the integrated digital transformation of municipal healthcare services in Gauteng, South Africa, focusing on municipal clinic systems.

Objectives: To identify the factors impeding digital transformation, understand key stakeholder perspectives on a systems approach to digital change, and propose a framework for integrated digital municipal clinics. Additionally, this study examines the relationship between implementing digital transformation and quality of care, as well as how digital solutions connect various components within the municipal clinic system.

Method: A positivist research paradigm was applied, using quantitative surveys to gather data from 210 healthcare staff in Gauteng municipal clinics. Data were collected using closed-ended Likert-scale questionnaires designed to measure barriers to digital transformation, stakeholder consensus, key constructs for framework development and perceptions of service quality. Quantitative data were analysed using SPSS and MS Excel, employing descriptive statistics, correlation analysis and stepwise multiple regression to examine relationships between digital transformation, stakeholder roles, barriers and service quality outcomes.

Results: Findings reveal significant barriers, including infrastructural limitations, funding constraints, skill gaps and low digital service user acceptance. Despite these challenges, there is strong support for digital transformation, with the potential to enhance service integration, communication and overall care quality.

Conclusion: This framework aims to improve healthcare quality, access and operational efficiency in Gauteng’s municipal clinics, ultimately leading to better health outcomes for local communities.

Contribution: This study proposes a comprehensive framework that emphasises adaptable systems, continuous training and stakeholder collaboration to address these barriers and ensure successful implementation.

Keywords: digital health; healthcare transformation; municipal healthcare; healthcare AI; health information systems; stakeholder engagement; telemedicine; healthcare digitalisation.

Introduction

Background and context

The Fourth Industrial Revolution (4IR) marks a transformative era characterised by technological advancements in information technology (IT), control and automation across various sectors, including healthcare. This wave of digitalisation is significantly reshaping healthcare delivery, enhancing interactions between caregivers, patients, stakeholders and governments. Globally, municipal clinical services are embracing digitalisation at an unprecedented pace, leveraging 4IR technologies to reimagine healthcare management, optimise health monitoring and enhance patient care.

As evidenced by countries such as Estonia, Denmark and Canada, digital transformation within healthcare has resulted in improved access to care, operational efficiencies and the integration of digital tools across healthcare systems (Øvretveit 2019). In Africa, nations like Rwanda and Namibia have begun harnessing 4IR technologies in healthcare, deploying drones for medical supplies in rural regions and launching telemedicine during the COVID-19 pandemic (Mbunge et al. 2022; Schneider 2021). In South Africa, applications of artificial intelligence (AI) are emerging, aiding in disease diagnosis, treatment recommendations and decision-support systems (Mbunge et al. 2022). However, the pace of digitalisation in South Africa’s healthcare sector – especially in regions like Gauteng – lags significantly behind that of other sectors like banking.

In South Africa, the digital divide is a significant obstacle to healthcare digitalisation. This divide encompasses discrepancies in internet access and information and communication technologies (ICT) availability and is often pronounced between urban and rural areas. Rural regions frequently struggle with inadequate digital infrastructure, limited Internet access and low digital literacy, contributing to substandard healthcare, lower educational attainment and socio-economic disadvantages (Aruleba & Jere, 2022; Kuika Watat & Jonathan 2020). The digital divide impedes access to essential services, isolates rural communities from critical information and further exacerbates healthcare inequities. For instance, by 2018, only 1.7% of rural households in South Africa had Internet access, and in provinces like Northwest and Limpopo, even fewer households had similar access (Aruleba & Jere 2022).

Although South Africa is recognised for its high rate of ICT adoption, rural areas face considerable digital disparities. In these regions, ICT usage often remains basic, limited to voice calls, social media and SMS. Recognising these challenges, various initiatives have been launched to improve ICT infrastructure and integrate technology-enabled services in areas such as agriculture and education.

Given these challenges, this study centres on the digitalisation of municipal healthcare services within Gauteng, South Africa’s most populous province, with an estimated population of 14.3 million in 2023 (Kunene & Mapulanga 2023). Gauteng is a hub of affordable education, industrial development and research, making it an ideal setting to explore the potential impacts of digitalisation on healthcare quality. This study will investigate the challenges inhibiting healthcare digitalisation in Gauteng and assess the potential of integrated digital transformation to enhance service delivery and healthcare outcomes in the province.

Problem statement

Despite significant governmental efforts to advance the digitalisation of healthcare services in South Africa, municipal clinics in Gauteng province continue to face challenges in meeting basic patient care needs. Although numerous studies have highlighted digital initiatives within the healthcare sector (Herselman, Botha & Loots 2016; Van der Hoogen, Koornhof & Mathee 2021), these often focus on broader national efforts rather than the specific obstacles within municipal healthcare settings. The lack of digital transformation in Gauteng’s municipal clinics has resulted in service backlogs, delayed patient care and a limited capacity for personalised healthcare delivery. This emphasises the urgent need for a tailored digital transformation framework to address these unique challenges.

The existing literature has extensively examined the quality of healthcare services in South Africa (Chigangaidze 2021; Mahomed & Asmall 2015); however, there is limited research on the digitalisation of municipal clinics, leaving a significant gap in understanding the barriers specific to this level of healthcare. Consequently, this study aims to address this gap by identifying the key factors hindering digital transformation in Gauteng’s municipal clinics, developing a strategic framework for digital alignment and evaluating how digitalisation could enhance healthcare quality. By focusing on the municipal level, this research contributes to filling a critical gap in the existing literature on healthcare digitalisation in South Africa.

Objectives of this study

The study aims:

• To determine factors impeding the digital transformation of municipal clinic services.
• To determine the key stakeholder consensus on the systems approach to digital transformation in municipal healthcare services.
• To identify and determine key constructs in proposing a framework for integrated digital municipal clinics.
• To examine the relationship between the level of digital transformation implementation and the quality of services in municipal clinics.
• To determine how digital transformation interlinks and connects various components of the municipal clinic system.

Significance of this study

This study holds substantial promise for advancing healthcare delivery, improving patient outcomes and enhancing operational efficiency in municipal healthcare services within Gauteng, South Africa. By focusing on the digital transformation of municipal clinics, it addresses a critical gap in healthcare accessibility and service quality for underserved communities. Implementing a cohesive, integrated digital framework can lead to more timely access to healthcare services, enabling personalised treatment options that can improve patient satisfaction and health outcomes.

Furthermore, this study’s findings can streamline healthcare operations by reducing service delays, optimising resource allocation and minimising administrative bottlenecks, thereby enhancing overall efficiency. Insights gained from this research can inform policymakers and healthcare administrators regarding the best practices and strategic approaches necessary for successful digital transformation. This, in turn, supports South Africa’s ongoing efforts to bridge the digital divide in healthcare and reduce disparities in access to quality services across urban and rural regions. By contributing to a scalable and sustainable model for digital healthcare, this study may help shape future policy and guide the broader digitalisation of public health services across the nation.

Literature review

Digital transformation in healthcare

The shift towards digital transformation in healthcare is marked by technologies such as AI, Internet of Things (IoT), telemedicine and Electronic Health Records (EHRs), which are being increasingly adopted to enhance patient care, data management and operational efficiency. Globally, nations are advancing towards digital solutions to address evolving healthcare challenges, with regions like North America and Europe leading in digital maturity (Øvretveit 2019; World Health Organization [WHO] 2020). Studies highlight how countries such as Canada and Estonia have implemented robust digital health policies that improve access to and quality of care (Øvretveit 2019; WHO 2022).

In recent years, AI-enabled diagnostics, wearable health tech and cloud-based data storage have become prominent in improving health outcomes and expanding accessibility to healthcare services (Mbunge et al. 2022). However, the adaptability of these innovations varies significantly across regions, with challenges tied to infrastructure, policy alignment and the digital divide being particularly evident in low- and middle-income countries (LMICs) (Choi, Choi & Marti 2025; Mbunge et al. 2022).

Current state of municipal healthcare in South Africa

South Africa’s healthcare sector has made strides towards digital adoption, but municipal care faces significant limitations, particularly in rural and underserved urban areas (Herselman et al. 2016). Municipal clinics, especially in Gauteng, struggle to provide quality healthcare because of a lack of digital infrastructure, funding and skilled personnel (Van der Hoogen et al. 2021). The current literature indicates that only a small percentage of South African rural households have Internet access, with urban areas also facing disparities in digital service availability (Aruleba & Jere 2022).

However, opportunities do exist, as recent governmental efforts are pushing for an e-health policy framework aimed at improving healthcare accessibility and digital literacy (South African Department of Health 2022). Despite these initiatives, municipal clinics still face systemic issues, such as inadequate ICT resources and policy inconsistency, which contribute to slow progress in achieving digital transformation in healthcare services.

Frameworks for digital transformation

Existing frameworks for healthcare digitalisation, such as the Health Information and Management Systems Society (HIMSS) framework and various digital maturity models, offer comprehensive guides to measuring and implementing digital transformation (HIMSS 2021; Henneman et al. 2023). The HIMSS outlines benchmark levels of digital maturity for organisations, providing a roadmap outlining foundational digitisation to advanced data analytics and AI implementation.

Digital maturity models and frameworks have also emerged to assist healthcare systems across the globe in measuring their progress in adopting technology and creating digital health policies (Henneman et al. 2023). However, the applicability of these frameworks in South Africa remains limited because of the country’s unique socio-economic conditions and the digital divide affecting rural and urban healthcare delivery (Henneman et al. 2023; WHO 2022;).

Research gaps and the need for an integrated approach

Current digital strategies often fall short of addressing the unique needs of municipal healthcare services in South Africa. Studies point to gaps in the current approaches, such as the inadequate integration of digital solutions within the existing healthcare framework, insufficient training for healthcare providers and the high costs associated with technology adoption (Choi et al., 2025; Mbunge et al. 2022). There is a critical need for an integrated framework that bridges the gap between municipal healthcare demands and available digital resources, particularly in underserved regions.

An integrated approach would not only improve the efficiency of healthcare services but also foster equitable access across urban and rural settings, contributing to improved health outcomes. Bridging these gaps requires developing policies that incorporate both public and private sector collaboration, as well as fostering investments in digital infrastructure to support long-term sustainability (South African Department of Health 2022).

Theoretical framework

Digital transformation in municipal healthcare services draws on several theoretical models that address the complexities of technology adoption, organisational readiness, environmental factors and stakeholder interactions. This framework integrates principles from Moore’s law, Lee’s theory, General Systems theory, Complex Systems theory, the Technology-Organisation-Environment (TOE) framework, stakeholder theory and the technology acceptance model (TAM) to provide a comprehensive foundation for digitally transforming municipal healthcare in South Africa.

Moore’s law

Introduced by Gordon Moore in 1965, Moore’s law posits that the number of transistors on a microchip doubles approximately every 2 years, resulting in exponential improvements in processing power and reductions in cost. Applied to digital healthcare transformation, Moore’s law underscores the potential for rapid advances in computational capabilities that enable increasingly sophisticated healthcare solutions from data analytics to AI-driven diagnostics (Andrews, Bawden & Robinson 2021). This principle suggests that digital transformation efforts must be adaptable to ongoing advancements, anticipating faster and more affordable technological options over time; this is especially important for scalable solutions in resource-constrained environments like municipal healthcare.

Lee’s theory

Lee’s theory posits that technological change in organisations is often marked by adaptation processes within systems, emphasising both the inevitable disruptions and opportunities that new technologies bring (Lee 2008). For municipal healthcare, this means understanding and managing the adjustment process that occurs as digital tools are integrated. Lee’s theory thus supports the need for ongoing training and support for healthcare professionals, enhancing adaptability to technology-driven changes and addressing challenges such as learning curves and workflow restructuring.

General systems theory

General Systems theory (GST) provides a framework for understanding healthcare organisations as interconnected systems, each part influencing and interacting with others. This theory encourages a holistic approach, suggesting that for digital transformation to succeed in municipal healthcare, it must be integrated with existing clinical, administrative and patient-support systems (Von Bertalanffy 1968). By considering these interdependencies, digital transformation efforts can be better aligned with organisational goals, enabling a seamless flow of information, reducing redundancies and fostering coherence across different functional areas.

Complex systems theory

Complex Systems theory builds on GST by recognising that healthcare organisations are dynamic systems with complex interactions between human, technological and structural elements. This theory posits that unexpected challenges, emergent behaviours and adaptation are intrinsic to complex systems (Bar-Yam 2003). In the context of digital transformation, this suggests that any introduced changes must account for unintended effects, requiring flexibility and continuous feedback loops. Complex Systems theory thus supports iterative testing, user feedback and adaptability in the digital transformation framework for municipal healthcare.

Technology–Organisation–Environment framework

The TOE framework provides a structured approach to assessing the factors affecting technology adoption in organisations (Tornatzky & Fleischer 1990). For digital transformation in municipal healthcare, the TOE framework considers the following:

• Technological factors, such as the availability of digital infrastructure and the relative advantages of new technologies.
• Organisational factors, including the healthcare institution’s readiness for change, resource availability and leadership support.
• Environmental factors, such as regulatory requirements, community needs and technological trends. The TOE framework thus offers a comprehensive assessment tool for evaluating the feasibility of digital initiatives in municipal healthcare settings, ensuring that they are well supported, strategic and aligned with environmental demands.

Stakeholder theory

Stakeholder theory emphasises the importance of engaging all stakeholders affected by organisational changes, particularly in public service sectors like healthcare (Freeman 1984). In municipal healthcare digital transformation, stakeholders include healthcare providers, patients, administrative staff, government bodies and the communities served. Recognising and addressing the diverse needs and concerns of these stakeholders is crucial for digital initiative acceptance and success. This theory supports participative planning and decision-making processes, fostering trust and alignment across stakeholder groups.

Technology acceptance model

The TAM, developed by Davis (1989), explores the determinants of technology adoption, focusing on perceived usefulness and ease of use as key factors influencing user acceptance. In the municipal healthcare context, the TAM underscores the importance of designing user-friendly systems that clearly demonstrate value to healthcare workers. For instance, if a new system for patient data management is perceived as easy to use and beneficial for patient care, it is more likely to be adopted by healthcare providers. The TAM provides insights into how design and user training can mitigate resistance and foster positive attitudes towards new technologies.

Integrating the theoretical framework

Together, these theories provide a robust framework for developing a digital transformation model in municipal healthcare:

• Moore’s law drives technological forecasting, ensuring that solutions are scalable and future proof.
• Lee’s theory guides the process of organisational adaptation to technological change.
• General and Complex Systems Theories underscore the importance of a holistic, flexible approach that accounts for interdependencies and adaptive behaviours in healthcare organisations.
• The TOE framework ensures a strategic alignment of technological, organisational and environmental factors.
• Stakeholder theory emphasises the inclusion of diverse perspectives, enhancing stakeholder engagement and acceptance.
• The TAM offers insights into user acceptance, highlighting the need for intuitive, beneficial technologies.

This integrated framework provides a foundation for designing and implementing a digital transformation strategy that is adaptable, inclusive and aligned with both technological advancements and the needs of stakeholders in South African municipal healthcare. These theoretical lenses are employed as complementary rather than competing perspectives, each illuminating different facets of the digital transformation challenge. It is important to note that this study adopts these theories pragmatically: they serve as analytical scaffolding to guide the development of an integrated digital transformation framework tailored to Gauteng’s municipal clinics, rather than as hypotheses to be formally tested. The objective is practical application and actionable insight, not theoretical validation.

Conceptual framework

The conceptual frameworks, as displayed in Figure 1, seek to identify the different components of an interconnected municipal clinic system and how they can be optimised through digitalisation and the creation of a system of systems.

FIGURE 1: Conceptual framework.

This conceptual framework for the integrated digitalisation of municipal clinical services provides a structured approach to implementing and benefiting from digital transformation. The inputs establish the foundational resources, the process details the collaborative and adaptive actions necessary for change and the outputs highlight the tangible improvements in patient care, operational efficiency and staff engagement. This framework underscores the potential for digital transformation in significantly enhancing municipal healthcare services and delivering more effective, accessible and personalised care.

Methodology

The research methodology employed a conclusive research design integrating both descriptive and causal approaches to examine the association between digital transformation and municipal clinic services in Gauteng. Descriptive research design enabled the systematic quantification and measurement of factors related to digital transformation, while causal design addressed predictive relationships between variables. This combination facilitated statistical analysis of factors impacting the transformation process and associated barriers. A quantitative research approach was employed exclusively. This approach enabled the collection of numerical data on factors impacting digitalisation, allowing for statistical generalisation, hypothesis testing and predictive modelling of relationships between variables. The quantitative focus ensured objectivity, replicability and precision in measuring digital transformation phenomena. A positivist research paradigm was adopted as the philosophical foundation for this study. Positivism enabled objective analysis of influencing factors through observable, measurable phenomena. This paradigm aligns with the study’s aim to identify statistical relationships, test hypotheses and develop predictive models of digital transformation outcomes in municipal healthcare.

Primary data collection was employed to obtain first-hand numerical data on the current scenario of municipal clinical services. The population comprised healthcare staff working in Gauteng municipal clinics. Simple random sampling was employed to select 210 healthcare staff for survey participation, ensuring representativeness and enabling statistical generalisation at 96% confidence with 5% margin of error. The sample size of 210 was determined using power analysis to ensure adequate statistical power for correlation and regression analyses. Closed-ended Likert-scale questionnaires served as the sole data collection method. This instrument was selected for its ability to generate numerical data suitable for statistical analysis, enabling measurement of attitudes, perceptions and behavioural intentions across standardised dimensions. The questionnaire comprised five sections aligned with research objectives: barriers to digital transformation, stakeholder consensus, key constructs for framework development, digital transformation implementation levels and perceived service quality. All items used 5-point Likert scales ranging from 1 = strongly disagree to 5 = strongly agree to ensure interval-level measurement.

Two pilot studies were conducted to ensure instrument reliability and validity. The first pilot study with 30 respondents identified item difficulties and ambiguities, while the second pilot study with 50 respondents confirmed clarity and refined scale properties. Content validity was established through expert panel review, with items retained only if greater than 50% expert agreement was achieved. Reliability was assessed using Cronbach’s alpha in SPSS, with all scales achieving acceptable internal consistency. Quantitative data were analysed using SPSS version 26 and MS Excel. Analytical procedures included descriptive statistics to characterise sample demographics and variable distributions; correlation analysis using Pearson product-moment correlations to examine bivariate relationships between digital transformation, stakeholder roles, barriers and service quality; stepwise multiple regression analysis to determine the predictive power of independent variables on service quality and to quantify variance explained and inferential statistics with significance testing at p less than 0.05 level to ensure statistical confidence in findings.

Ethical considerations

Ethical clearance to conduct this study was obtained from the Johannesburg Business School Research Ethics Committee (JBSREC) (Ref. No. JBSREC2023142). All participants in the study provided the necessary consent, which was then properly documented. All ethical approvals for this study were obtained from the institutions concerned. The following approvals were granted: approval by the University of Johannesburg by the JBSREC in accordance with the university’s research ethics policies, approvals by The City of Tshwane Metropolitan Municipality in accordance with the municipal policies on research, approvals by the City of Ekurhuleni Metropolitan Municipality in accordance with the municipal policies on conducting research involving subjects of the municipality and approvals by the Gauteng Department of Health in accordance with departmental policies.

Results

This section reflects the analysis of results.

Profile of respondents

Respondents’ demographic profiles are essential for understanding the context of this study on digital transformation in municipal clinic services. The respondents included a majority of technical healthcare workers, such as clinicians, doctors and nurses (76.2%), while 7.6% worked in administrative roles, 9.5% held supervisory roles and 5.7% were in other diverse positions. In terms of age, 23.8% were between 20 years and 30 years, 37.1% were aged 31 years to 40 years, 24.8% were between 41 years and 50 years and 14.3% were over 50 years, offering a range of experiences.

Regarding education, 7.6% had completed certificate courses, 4.8% had Grade 12 as their highest qualification, 28.6% held nursing diplomas, 26.7% had bachelor’s degrees in nursing or related fields and 30.5% held diplomas or higher qualifications in other disciplines. The respondents also varied in healthcare experience: 24.8% had 0 year to 4 years, another 24.8% had 5 years to 9 years, 21.9% had 10 years to 14 years and 28.6% had over 15 years. In terms of experience specific to municipal clinic services, 64.8% had 0 year to 4 years, 9.5% had 5 years to 9 years, 11.4% had 10 years to 14 years and 14.3% had over 15 years. This diversity across roles, age, education and experience provides a broad perspective on digital transformation needs and expectations in the municipal healthcare sector.

Factors impeding digital transformation of municipal clinic services

This objective explores barriers impeding digital transformation in municipal clinic services, analysing respondents’ levels of agreement and supporting findings from the existing literature. The barriers identified are presented in Table 1 and subsequently discussed.

Available infrastructural and technological developments

Respondents showed moderate agreement regarding the impact of infrastructure and technology on digital transformation, with 43.8% agreeing and 21.9% strongly agreeing. The literature confirms the essential role of reliable technological infrastructure in digital health initiatives. For example, Chaves Cano et al. (2024) assert that infrastructure forms the backbone of digital health transformation, facilitating the integration of personal health records, biomedical research and care services. However, similar to this study’s findings, Cohen and Martin (2020) highlight gaps in technological readiness, suggesting that infrastructure deficits can delay progress.

Available funding

Financial constraints emerged as a significant barrier, with 33.3% of respondents strongly agreeing that funding issues hinder transformation efforts. This is consistent with Lennon et al. (2017), who identify funding as a primary obstacle in digital health adoption, which is further exacerbated by governance and infrastructure gaps. Effective digital transformation requires substantial investment in technology, staff training and system upgrades. The consensus around funding constraints in this study reinforces findings from the broader literature regarding the need for dedicated financial support to overcome these barriers.

State of technological skills among healthcare professionals and administration

Skill gaps within healthcare staff and administration were also recognised as barriers, with 35.2% agreeing and 22.9% strongly agreeing on this issue. This aligns with research by Van Velthoven, Powell & Powell (2018), who argue that healthcare organisations need skilled professionals to maintain a competitive advantage in a digital landscape. Without sufficient training, healthcare staff may find it challenging to adapt to new digital systems, slowing transformation efforts. The moderate agreement found in this study underscores the importance of ongoing training programmes to bridge skill gaps among healthcare professionals.

Acceptance of digital healthcare services among care users

User acceptance of digital healthcare services emerged as another notable barrier, with 33.3% of respondents expressing agreement. Connolly et al. (2021) discuss the importance of user engagement for the success of digital health initiatives, especially at the community level where municipal services operate. A lack of user acceptance can undermine the adoption of digital health services, as users’ trust and willingness to engage with digital tools are essential for integration. This study reflects these challenges, indicating a need to foster user acceptance through targeted engagement strategies.

Technological knowledge and skills among care users

A significant barrier identified was the technological skill level among care users, with 41.9% of respondents agreeing that knowledge gaps hinder digital transformation. Benis et al. (2021) emphasise that user competence is critical for inclusive digital health systems under the One Digital Health framework. The findings in this study echo this viewpoint, suggesting that without adequate digital literacy, care users may struggle to adopt new health technologies. These results reinforce the importance of educational programmes that build user skills, ensuring digital transformation efforts are accessible and effective.

Overall, this study reveals that funding constraints, skill gaps among both professionals and users, and limited user acceptance constitute the main obstacles to digital transformation in municipal clinic services. The alignment here with the existing literature underlines the need for a comprehensive strategy addressing these barriers in order to foster effective digital transformation.

Key stakeholder consensus on the systems approach to digital transformation in municipal healthcare services

This objective assesses the consensus level among respondents regarding the involvement, understanding and importance of key stakeholders in the digital transformation of municipal healthcare services. It examines perspectives on the dependency and reliability of digital healthcare services among various stakeholders. The results are presented in Table 2.

Clarity regarding key stakeholders’ roles

Respondents expressed varying opinions about whether key stakeholders’ roles in digital transformation were clearly defined. With a mean score of 3.25 and a standard deviation (SD) of 1.029, findings indicate a moderate agreement level, where 42.9% agreed and 5.7% strongly agreed.

Understanding of key stakeholders’ roles

Opinions regarding stakeholders’ understanding of their roles were mixed, with a mean score of 3.16 and a s.d. of 0.984. Notably, 33.3% agreed and 5.7% strongly agreed that stakeholders understand their roles.

Dependency of healthcare providers on digital services

There was a moderate agreement (mean score of 3.20, SD of 1.138) regarding healthcare providers’ reliance on digital services, with 39.0% agreeing and 9.5% strongly agreeing.

Reliability of digital services for healthcare users

Respondents showed a moderate level of agreement regarding the reliability of digital healthcare services, with a mean score of 3.37 and a SD of 1.031, where 42.9% agreed and 9.5% strongly agreed.

Importance of healthcare professionals in digital services

The consensus on healthcare professionals’ importance in digital services was strong, with a mean score of 3.98 and a SD of 0.830. Over 49.5% agreed and 25.7% strongly agreed, regarding their essential role.

Involvement of care users in digital transformation

There was notable agreement regarding the involvement of care users as important stakeholders, with a mean score of 3.86 and a SD of 0.851. Here, 54.3% agreed and 18.1% strongly agreed.

Importance of various stakeholders

High levels of agreement were observed regarding the importance of IT providers, clinic administrators and government bodies in digital healthcare services, with a mean score of 4.16 and a SD of 0.878. This reflects a strong consensus regarding the significance of diverse stakeholders.

Platform for stakeholder contributions

Opinions varied on whether a platform for stakeholder contributions exists, with a moderate level of agreement (mean score of 3.56, SD of 0.973): 39.0% agreed and 13.3% strongly agreed.

In essence, these findings reveal varied agreement levels regarding key stakeholders’ involvement, understanding and importance in municipal healthcare digital transformation. A notable consensus emerged around healthcare professionals’ roles and user involvement although clarity on these roles and the availability of contribution platforms remains less definitive.

Key constructs in proposing a framework for integrated digital municipal clinics

This objective seeks to capture a consensus regarding critical elements in order to guide digital transformation initiatives within municipal healthcare settings. The mean scores for the key constructs identified are presented in Table 3.

Interconnectedness of digital healthcare systems

A high level of agreement (54.3%) was observed in this regard, with 11.4% strongly agreeing on the importance of interconnected systems, yielding a mean score of 3.72 (SD = 0.783). This suggests a strong consensus on the significance of system integration for achieving care service goals.

Adaptability of digital healthcare systems

Respondents acknowledged the need for adaptability, with 61.0% agreeing and 18.1% strongly agreeing, resulting in a mean score of 3.93 (SD = 0.756). This highlights the importance of flexibility to accommodate environmental changes.

Impact of technological skills deficit

Agreement was noted regarding the impact of limited technological skills, with 51.4% agreeing and 20.0% strongly agreeing, producing a mean score of 3.80 (SD = 0.941).

Emphasis on outcomes in care service

The emphasis on outcome-focused care services received high agreement (55.2%), with a mean score of 3.83 (SD = 0.791), affirming the value placed on achieving desired outcomes in digital healthcare services.

Clarity in digital transformation involvement

Mixed responses were noted in this regard, with a mean score of 3.39 (SD = 1.044). Although 48.6% agreed on the clarity of roles in digital transformation, there was notable variation, suggesting room for further communication.

The data indicate substantial agreement on the need for system integration, adaptability, skill development and outcome focus although clarity regarding transformation roles could be improved. These constructs are critical for designing an integrated digital framework in municipal clinics and promoting alignment with digital transformation goals.

Relationship between digital transformation implementation levels and service quality in municipal clinics

To achieve this objective, correlation and stepwise regression analyses were conducted to determine the influence of digital transformation, stakeholder roles and barriers to effective digital transformation on service quality in municipal clinics.

Correlation analysis

The correlation results are presented in Table 4.

Digital transformation and quality of care: The strong positive correlation (r = 0.641, p < 0.05) suggests that higher levels of digital transformation are associated with improved quality of care.

Stakeholder role and quality of care: The strong positive correlation (r = 0.715, p < 0.05) highlights the critical role of stakeholder engagement in enhancing care quality.

Barriers and quality of care: The weak negative correlation (r = −0.120, p = 0.085) indicates that while barriers can impede care quality, their impact is not statistically significant.

Stakeholder roles and digital transformation: The significant correlation (r = 0.603, p < 0.05) suggests that effective stakeholder engagement enhances digital transformation.

Overall, the results highlight the synergistic importance of digital transformation and stakeholder engagement in improving municipal health service quality. Although barriers have a slight negative effect, they are not statistically significant, and the subsequent regression analysis further quantified these relationships.

Stepwise regression analysis

Stepwise regression analysis was performed to explore how digital transformation, stakeholder roles and barriers affect municipal healthcare quality. The model summary, ANOVA and coefficients are presented in Table 5, Table 6 and Table 7, respectively.

In Model 1, digital transformation and stakeholder roles explain 58.1% of the variance in healthcare quality (R² = 0.581). Adding barriers in Model 2 increases the explanatory power to 61.6% (R² = 0.616).

Both models are significant at p < 0.001, confirming the collective impact of the predictors on healthcare quality.

In Model 1, both digital transformation (B = 0.305, p < 0.001) and stakeholder roles (B = 0.677, p < 0.001) are significant predictors, with the latter having a stronger effect (β = 0.513). In Model 2, digital transformation (B = 0.277, p < 0.001) and stakeholder roles (B = 0.736, p < 0.001) remain significant, but the addition of barriers (B = −0.193, p < 0.001) introduces a negative influence on healthcare quality.

The regression analysis reinforces the importance of digital transformation and stakeholder involvement in enhancing municipal healthcare quality, with barriers presenting a challenge that reduces these positive effects.

Discussion

The findings of this study reveal three critical insights regarding digital transformation in municipal healthcare services. Firstly, the strong positive correlation between digital transformation and service quality (r = 0.641, p < 0.05) supports the TAM and the broader digital transformation literature, which posit that perceived usefulness and ease of use of digital systems directly enhance healthcare delivery outcomes (Davis 1989; Øvretveit 2019). The regression analysis confirms that digital transformation remains a significant predictor of service quality (B = 0.277, p < 0.001) even when controlling for other variables, suggesting that investments in interoperable systems, EHRs and telemedicine capabilities yield tangible improvements in patient care.

Secondly, the role of key stakeholders emerged as the strongest predictor of service quality (B = 0.736, p < 0.001, β = 0.557), accounting for the largest variance in outcomes. This finding aligns with Stakeholder theory (Freeman 1984) and the TOE framework, which emphasise that organisational readiness and leadership support are critical enablers of technology adoption. The high mean score (4.16) regarding the importance of IT providers, administrators and government bodies underscores that successful digital transformation requires coordinated engagement across multiple actor groups. This stakeholder consensus facilitates the alignment of technological, organisational and environmental factors necessary for sustainable change (Tornatzky & Fleischer 1990).

Thirdly, while barriers to digital transformation – including infrastructural limitations, funding constraints and skill gaps – were identified as significant obstacles in the findings, the regression analysis reveals that these barriers have a statistically significant but relatively modest negative impact on service quality (B = −0.193, p < 0.001). This suggests that although barriers matter, they do not dominate outcomes when stakeholder engagement and digital transformation initiatives are effectively implemented. The TOE framework supports this interpretation: while environmental and technological constraints present challenges, organisational factors and stakeholder commitment can mitigate their effects. Consequently, the study demonstrates that proactive stakeholder management and strategic digital investments can overcome structural impediments, reinforcing Lee’s theory (2008) regarding organisational adaptation to technological change.

Conclusion

This study identified several barriers to digital transformation in municipal clinics, with respondents citing infrastructural and technological limitations, funding constraints and skill gaps among staff as significant issues. Digital service acceptance by care users was also low, compounded by limited digital literacy and resistance to change. The data highlighted the need for adaptable, interconnected digital systems to improve service integration and continuity of care. Although some digital tools were used effectively, their inconsistent application and resource gaps limited the overall benefits. There was a moderate consensus on the importance of stakeholder collaboration, emphasising the need for clear roles and responsibilities, particularly in engaging care users to ensure the digital solutions meet their needs. Key constructs for a successful digital framework include adaptable systems, consistent training and a focus on positive care outcomes.

Despite significant challenges, digital transformation holds great promise for improving municipal clinic services. The effective integration of digital systems can enhance communication, data sharing and care quality, provided that infrastructure, funding and training needs are met. Stakeholder collaboration and clarity regarding roles are essential in ensuring that digital solutions are user focused and supportive of both providers and patients.

For municipal decision-makers in Gauteng and similar contexts, this framework offers an immediate imperative: treat digital transformation not as an IT procurement exercise but as a governance priority requiring cross-departmental coordination, sustained budgetary commitment and structured stakeholder forums beginning now. Municipal clinics must be repositioned as coordination hubs that integrate primary care, specialist referrals and community health services through interoperable digital systems, rather than isolated service points. Ultimately, digital maturity in this context is a question of institutional capacity and collaborative governance; without these foundations, technology investments alone will perpetuate the very inequities they seek to resolve.

Recommendations

To address these barriers, municipal clinics should prioritise infrastructure upgrades, sustained funding and ongoing training to boost staff and care user digital skills. Implementing adaptable, secure and interoperable digital systems will improve data sharing and streamline operations across departments. A comprehensive digital tool implementation strategy should address resource gaps and service integration issues. Clear stakeholder roles and active care user involvement are crucial in ensuring that solutions align with user needs. Developing a robust digital framework for municipal clinics should focus on interconnected systems, continuous training, security, interoperability and positive care outcomes to support a successful transformation.

Proposed framework

The framework for integrated digital municipal clinics provides a systematic approach to enhancing healthcare quality and access, as depicted in Figure 2. It addresses the technical, organisational and user-related challenges identified in the study to support effective digital transformation in municipal clinics.

FIGURE 2: Envisaged framework.

The proposed framework for integrated digital municipal clinics targets essential technological, organisational and user-related challenges. It emphasises a robust IT infrastructure for interoperability, secure data management and standardised protocols. Organisational processes are streamlined through governance structures, consistent funding and workflow integration. Continuous training programmes address digital literacy and change management strategies help staff adapt to digital tools. The framework promotes patient engagement, ensuring accessible and inclusive digital solutions for diverse users. Stakeholder collaboration across the healthcare, IT and government sectors fosters coordination, while interconnected systems like EHRs enable seamless data sharing. Continuous monitoring with key performance indicators (KPIs) and feedback loops supports improvements, focusing on quality of care and expanded service access. This comprehensive approach aims to enhance municipal clinics’ service quality and accessibility, driving better health outcomes for communities.

Acknowledgements

This article includes content that overlaps with research originally conducted as part of Musawakhe Khumalo’s doctoral thesis titled ‘A digital transformation framework for enhancing access and quality of municipal clinic services’, submitted to the Johannesburg Business School, University of Johannesburg in 2025. The thesis was supervised by Tankiso S. Moloi. Portions of the data, analysis and/or discussion have been revised, updated and adapted for journal publication. The original thesis is publicly available at: https://ujcontent.uj.ac.za/esploro/outputs/doctoral/A-digital-transformation-framework-for-enhancing/9955293307691. The author affirms that this submission complies with ethical standards for secondary publication, and appropriate acknowledgement has been made to the original work.

This article is further based on data from a larger study. A related article focusing on barriers to digital transformation in Gauteng’s municipal health clinics has been published in Journal of Local Government Research and Innovation, 6, #282. The present article addresses a distinct research question, focusing on a framework for the integrated digital transformation of municipal healthcare services in South Africa: The case of Gauteng.

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

Musawakhe H. Khumalo: Conceptualisation, Methodology, Writing – original draft, Writing – review & editing. Tankiso S. Moloi: Supervision. 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.

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

The datasets used and/or analysed during the current study are available from the corresponding author, Musawakhe H. Khumalo, upon reasonable request.

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.

References