Mapping inequities in digital health transformation within Ethiopia's primary health care system using PROGRESS-plus: Scoping review

Abstract

Objectives

Digital health technologies (DHTs) are recognized by the World Health Organization (WHO) as essential to achieving Universal Health Coverage, yet major equity gaps persist in low-resource settings such as Ethiopia. This scoping review applies the PROGRESS-Plus framework to examine how overlapping social identities (e.g., gender, residence, and income) shape inequities in access to, use of, and engagement with DHTs in Ethiopia's primary healthcare (PHC) system.

Methods

Following Arksey and O'Malley's framework enhanced by Levac et al. and reported using PRISMA-ScR 2020 guidelines. Searches were conducted in PubMed, Scopus, Web of Science, EMBASE, Google Scholar, and grey-literature sources for studies published between 2015 and 2025. Eligibility criteria were guided by the PCC framework, focusing on digital health interventions (DHIs) within Ethiopia's PHC system with explicit equity relevance. Data were extracted, charted, and synthesized using the PROGRESS-Plus framework, supported by thematic analysis, descriptive statistics, and integration with the WHO digital health intervention taxonomy and the NASSS implementation framework.

Results

Twenty-one studies met inclusion criteria. Digital health inequities consistently clustered around residence, education, socioeconomic status, gender, occupation, and marginalized-group status. Structural barriers, poor connectivity, limited devices, and inadequate digital health skills, disproportionately affected rural and pastoralist communities. Advanced digital health tools (AI, telemedicine, EMRs) were largely restricted to urban and better-resourced settings. Engagement was shaped by cultural and linguistic relevance, trust, peer support, and institutional readiness.

Conclusion

Digital transformation in Ethiopia's PHC system remains constrained by intersecting social determinants. Applying PROGRESS-Plus demonstrates that technological expansion alone cannot ensure equitable uptake. Equity-centered digital strategies, emphasizing infrastructure, contextualized design, capacity building, and inclusive governance, are essential for meaningful and sustainable digital health transformation adoption across all populations.

Keywords

Digital health equity Ethiopia primary healthcare PROGRESS-Plus socio-technical systems health disparities mHealth disability inclusion gender equity health policy implementation

Key messages

Despite Ethiopia's expanding digital health initiatives, little is known about how these interventions affect marginalized groups. This scoping review applies the PROGRESS-Plus equity framework to uncover how social determinants such as place, gender, occupation, and disability shape digital health access, use, and engagement within Ethiopia's PHC system.

Digital health adoption in Ethiopia is highly inequitable. The majority of interventions benefit urban, educated, and higher-cadre users. Rural residents, pastoralist communities, women, and persons with disabilities face consistent barriers, ranging from lack of connectivity to non-inclusive system design. SMS-based platforms had the highest uptake, while complex tools often excluded the most disadvantaged.

Technical expansion alone will not close digital health equity gaps. Policies must move beyond coverage metrics to actively design for inclusion. This includes investing in rural infrastructure, co-developing low-literacy tools, expanding digital health literacy programs, and embedding equity monitoring indicators within national strategies.

Ethiopia's digital health policies should integrate measurable equity indicators across all stages, design, implementation, and evaluation. Drawing on global lessons from countries like India, South Africa, and Rwanda, governance reforms must center on inclusive design, stakeholder engagement, and accountability mechanisms to avoid deepening health disparities.

Introduction

Ethiopia, digital health initiatives have accelerated through national strategies, electronic community health information systems (eCHIS), and platforms such as District Health Information Software 2 (DHIS2). These programs aim to mitigate critical health system challenges, including severe workforce shortages, estimated at 0.1 physicians per 1000 people.¹ Yet digital transformation efforts often overlook the social determinants that shape individuals’ access to and engagement with technology. Urban–rural disparities in connectivity and literacy, gendered norms in health-seeking behavior, and the exclusion of pastoralist and linguistically diverse groups continue to undermine inclusive digital health progress.^2,3

Ethiopia's digital health journey has evolved through distinct phases: fragmented donor-led pilots (2010–2015), strategic scale-up efforts (2015–2020), and COVID-19-accelerated expansion (2020–present). Despite these milestones, critical gaps remain. Only 18.2% of health facilities meet minimum information and communication technology (ICT) infrastructure standards, and nearly half of the health workforce lacks basic digital health competence.² Moreover, digital health system rarely accommodate local language, literacy levels, or cultural contexts, factors that reinforcing and hinder scalability. Over 80% of pilots projects remain unscaled due to governance fragmentation, urban-centered innovation, and insufficient alignment with equity goals.^4,5

Despite growing international emphasis on digital health equity, little is known about how national digital transformation processes in low- and middle-income countries (LMICs) integrate health equity frameworks. Most Ethiopian studies focus on technology adoption, system performance, or workforce capacity, but rarely assess whether DHIs equitably reach diverse social groups. There is a critical need for a systematic approach to evaluate how intersecting social determinants, such as residence, gender, education, and socioeconomic status, shape engagement with digital health technologies.

To address this gap, this review applies the PROGRESS-Plus framework, a comprehensive and widely recognized equity assessment tool. PROGRESS-Plus encompasses core social stratifiers; Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capita, along with additional context-specific factors (the “Plus”) to capture multiple, overlapping dimensions of disadvantage. The framework is particularly suited to digital health research because it integrates intersectionality, allowing analysis of how combined inequities influence digital health access, use, and engagement.

Accordingly, this scoping review aims to:

Identify and synthesize existing evidence on DHIs within Ethiopia's PHC system through the lens of equity;

Assess how PROGRESS-Plus dimensions are incorporated or overlooked in the design, implementation, and evaluation of digital health initiatives; and

Identify knowledge gaps, barriers, and enablers to equitable digital health transformation in the Ethiopian, with implications for other LMICs.

By applying PROGRESS-Plus, this review contributes to the global discourse on equity-centered digital transformation. It highlights that technological innovation alone cannot resolve systemic disparities unless digital health strategies are explicitly grounded in equity, contextual responsiveness, and inclusive governance.

Methodology

This scoping review followed the methodological framework proposed by Arksey and O’Malley,⁶ further refined by Levac, Colquhoun,⁷ and reported in accordance with the PRISMA-ScR 2020 checklist extension for scoping reviews.⁸

Stage 1: research question and eligibility criteria

The research question guiding this review was: “How effectively does the application of the PROGRESS-Plus framework within a scoping review methodology capture the intersecting dimensions of digital health inequity (access, use, engagement) across diverse populations in Ethiopia's PHC system”?

Eligibility criteria were defined using the PCC (Population–Concept–Context) framework. Population included Ethiopia's PHC system; health posts, health centers, primary hospitals, healthcare workers (e.g., Health Extension Workers (HEWs), nurses, PHC managers), and community users.⁹

Concept focused on digital health transformation initiatives such as eHealth, mHealth, electronic health records, DHIS2, and telemedicine, with explicit emphasis on equity dimensions related to access, use, or engagement.

Context was limited to Ethiopia across all administrative regions, including peer-reviewed and grey literature published between 2015 and 2025 in English.

Studies were excluded if they:

Focused exclusively on hospital-level or tertiary care without a primary-care link or

Lacked an identifiable equity component (Table 1).

Table 1.

Eligibility criteria.

Criteria	Included	Excluded
Population	Ethiopia's PHC system: health posts, health centers, primary hospitals; HEWs, nurses, PHC staff; community users	Populations not related to Ethiopia's PHC system
Concept	Digital health transformation; equity gaps in access, use, or engagement with DHTs	Studies not addressing digital health equity or transformation
Context	Ethiopia (all administrative regions)	Studies conducted outside Ethiopia
Type of Evidence	Peer-reviewed articles, grey literature, policies, program evaluations, institutional reports	Editorials, opinion pieces, non-research documents
Dates	January 2015 – May 2025	Publications before 2015 or after May 2025
Language	English	Non-English (unless translated)

Key concepts and definitions

To ensure conceptual clarity and consistent application of terminology, this review adopts the following definitions aligned with WHO, World Bank, UNICEF, and PROGRESS-Plus equity guidance.

Digital health inequity

Digital health inequity refers to systematic, avoidable, and socially unjust differences in access to, use of, and engagement with DHTs across population groups. Inequities arise from structural, sociocultural, economic, and institutional determinants that disproportionately disadvantage certain communities (e.g., rural residents, women, low-literacy populations, marginalized groups).

Digital health inequality

Digital health inequality refers to observable differences in digital participation or outcomes (e.g., smartphone availability, Electronic Medical Record (EMR) coverage), without implying social unfairness.

Digital transformation

Digital transformation denotes the system-wide integration of digital technologies, data systems, human capacity, governance, financing, and institutional readiness to improve health system performance. It extends beyond tool deployment to include digital leadership, interoperability, workforce digital skills, equity safeguards, and organizational change processes.

Digital health interventions:

Refer to specific digital tools or platforms (eCHIS, telemedicine, AI diagnostics, DHIS2, SMS-based systems). This review classifies DHIs in accordance with the WHO Digital Health Intervention Taxonomy, grouped by primary user category: 1) clients, 2) health providers, 3) health system managers, and 4) data services.

Access

Availability of devices, electricity, connectivity, and language-appropriate interfaces.

Use

Ability to navigate and apply digital tools effectively, shaped by digital literacy, training, workload, and professional roles.

Engagement

Sustained, meaningful integration of digital tools into routine workflows or health-seeking behaviours, influenced by trust, cultural congruence, and institutional readiness.

Enablers and barriers

Enablers are contextual or technical factors that facilitate equitable access, use, or engagement with digital health tools, while barriers impede these processes. This review differentiates enablers/barriers across:

Structural determinants

Infrastructure, governance, financing, policy alignment

Sociocultural determinants

Literacy, gender norms, language, social trust

Institutional factors

Workload, supervision, digital leadership, IT support

Technology features

Usability, offline capability, interface design

Stage 2: search strategy and data sources

We conducted a comprehensive literature review of digital health equity in Ethiopia, including studies published between 2015 and 2025, corresponding to the national health strategy periods (HSTP III). Searches were performed in PubMed, Scopus, Web of Science, EMBASE, and Google Scholar using a combination of controlled vocabulary (e.g., MeSH terms) and free-text keywords related to digital health, equity, primary healthcare, and Ethiopia, with Boolean operators (AND, OR) applied. Filters were set for English language and relevant publication types, including peer-reviewed and grey literature.

A total of 1458 records were identified from electronic databases (n = 1243) and grey literature sources (n = 215). After removing duplicates, 1154 records were screened, and 1006 were excluded based on title and abstract review. Subsequently, 148 full-text articles were assessed, 127 were excluded due to lack of focus on the PHC focus (n = 35), absence of digital health components (n = 28), methodological limitations (n = 22), insufficient information (n = 18), duplication (n = 10), non-English text (n = 8), or being outside the time range (n = 6). Finally, a total of 21 studies met the inclusion criteria (Figure 1).

Figure 1.

PRISMA diagram on digital transformation in the PHC system, Ethiopia, 2025.

Search terms combined keywords and controlled vocabulary (e.g., MeSH) related to digital health (“digital health,” “eHealth,” “mHealth,” “telemedicine,” “health information system”), context (“Ethiopia,” “primary healthcare,” “health system”), and equity (“PROGRESS-Plus,” “health equity,” “inequality,” “access,” “use,” “engagement”). Boolean operators and database-specific filters were used to refine searches and ensure relevance to Ethiopia's PHC context). Boolean operators and database-specific filters were applied to refine results, remove duplicates, and ensure relevance to the Ethiopian PHC context.¹⁰

Electronic databases and search strings

We used controlled vocabulary (MeSH), Boolean operators and truncation adapted to each database. The search focused on DHIs in Ethiopia's PHC context (Table 2).

Table 2.

Electronic databases and search strings.

Database	Exact Search String	Records Retrieved
PubMed/MEDLINE	(“digital health” OR mHealth OR eHealth OR telemedicine OR “electronic health record” OR DHIS2 OR “health information system”) AND (Ethiopia) AND (“primary health care” OR “PHC” OR “community health” OR “health extension”)	243
Scopus	TITLE-ABS-KEY (“digital health” OR mHealth OR eHealth OR telemedicine OR “health information system” OR DHIS2 OR EMR) AND TITLE-ABS-KEY (Ethiopia) AND TITLE-ABS-KEY (“primary health care” OR “community health”)	301
Web of Science	TS = (“digital health” OR mHealth OR eHealth OR telemedicine OR “health information system” OR DHIS2) AND TS = (Ethiopia) AND TS = (“primary health care” OR “community health”)	187
Embase	'digital health'/exp OR ‘mHealth'/exp OR ‘eHealth'/exp OR telemedicine OR ‘electronic health record’ AND Ethiopia AND (‘primary health care’ OR ‘community health’)	217
CINAHL (EBSCO)	(“digital health” OR mHealth OR eHealth OR telemedicine OR “health information system” OR DHIS2) AND Ethiopia AND (“primary health care” OR “health extension”)	125
African Index Medicus (AIM)	digital health AND Ethiopia	93
Cochrane Library	(“digital health” OR mHealth OR eHealth OR telemedicine) AND Ethiopia	77
Total peer-reviewed records retrieved		1243

Grey literature retrieval

Grey-literature searches targeted national strategy documents, program evaluations, donor reports, institutional assessments, and university theses. Sources included WHO, World Bank, FMOH, global health NGOs, and academic repositories (Table 3).

Table 3.

Grey literature retrieval.

Source	Search Method	Records Retrieved
Ethiopian Federal Ministry of Health (FMoH)	Manual site search and document repository (site:moh.gov.et “digital health”)	21
Ethiopian Public Health Institute (EPHI)	Manual site search and direct PDF access	19
Digital Health Innovation and Learning Centre (DHILC)	Internal publication archive	16
WHO IRIS Repository	(“digital health” AND Ethiopia)	26
World Bank documents and reports	(“eHealth” OR “digital health”) AND Ethiopia	21
USAID Development Experience Clearinghouse	digital health AND Ethiopia	24
UNICEF/UNFPA Ethiopia	Country-level strategy and evaluation reports	17
Addis Ababa University Repository	digital health in theses/dissertations	21
Jimma/Gondar University Repositories	Manual repository searches	18
Google advanced search	site:.et “digital health” Ethiopia	32
Total grey literature records retrieved		215

All records were imported into EndNote, and duplicates were removed. Two reviewers (IM and RD) independently screened titles, abstracts, and full texts. Disagreements were resolved through discussion and consensus.

Stage 3: screening and selection process

This scoping review adhered to the enhanced Arksey and O'Malley methodological framework (refined by subsequent literature) and employed the PRISMA-ScR checklist to ensure transparency and reporting consistency.^11,12

A PRISMA-ScR flow diagram (Figure 1), summarises the search and selection process. A total of 1458 records were identified through database and grey literature searches. After the duplicate removal (n = 304), 1154 records remained. The title and abstract screening excluded 1006 records based on predefined inclusion criteria. The full-text review was conducted for 148 articles, of which 21 were eligible for final synthesis.

The study selection process is illustrated in Table 4, which outlines the number of records identified, screened, assessed for eligibility, and included in the review, along with reasons for exclusion at each stage.

Table 4.

Search strategy.

ID	Studies	Study Design	Year	Sample	Technology Type	Target population	Setting	PROGRESS-Plus Domains Addressed	Key Findings
ID	Studies	Study Design	Year	Sample	Technology Type	Target population	Setting	PROGRESS-Plus Domains Addressed	Access	Use	Engagement
S01	(Medhanyie et al., 2015)	Cluster trial (qual/quant)	2015	Tigray HEWs	Basic phones, SMS-based mHealth forms	HEWs	Rural Tigray	Place, Language, Occupation, Gender, Education	SMS content in Tigrinya improved linguistic accessibility; geographic remoteness and lack of electricity reduced system functionality and phone charging ability	Low ICT literacy and limited exposure to digital tools constrained capturing and sending form data	Strong HEW acceptance due to prior familiarity with basic phones; women HEWs showed high commitment to message transmission
S02	(Bogale et al., 2023)	Cross-sectional	2023	HEWs from 6 regions	eCHIS smartphone	HEWs	Amhara, Oromia, SNNP, Tigray	Place, Occupation, SES, Education	Poor connectivity, lack of backup power, and rural remoteness limited system availability and real-time data transfer	Gaps in digital literacy and absence of refresher training reduced effective eCHIS navigation	Community trust in HEWs increased use of the platform despite technical challenges; high motivation to provide data
S03	(Steege et al., 2018a; Steege et al., 2018b)	Qualitative ethnographic	2018	Sidama HEWs	Basic phones, SMS	HEWs	Sidama Zone	Place, Language, Gender, Occupation, SES, Social capital	Access constrained by low network stability and reliance on basic devices; linguistic familiarity enabled SMS comprehension	Gendered domestic burdens limited time available for SMS reporting; additional workload reduced use	Strong community bonding allowed HEWs to sustain reporting and messaging despite limited infrastructure
S04	(Gebremariam, Zelenko, Hadush, Mulugeta, & Gallegos, 2020)	Randomized SMS trial	2020	Mothers of infants	SMS maternal health messaging	Young mothers	Remote districts	Rural residence, Age	SMS successfully reached mothers in remote areas otherwise cut off from health education	Limited literacy hindered reading and interpreting messages; older caregivers relied on family to interpret SMS	Mothers receiving SMS displayed enthusiasm for the information; culturally acceptable and trusted
S05	(Starr et al., 2020)	Feasibility study	2020	Surgical patients	Phone follow-up	Post-op patients	Urban hospitals	Disability (post-surgery)	Phone follow-up provided accessible post-surgery support for patients unable to attend facility visits	Low digital literacy hindered timely reporting of symptoms; some unable to use phones beyond calls	Engagement moderate and dependent on patient ownership of a functioning phone
S06	(Brant et al., 2021)	Diagnostic evaluation	2021	Cataract patients & surgeons	AI diagnostic tool	Adults with visual impairment	Eye centers	Disability, Age	AI tools extended diagnostic access to underserved patients	Technology use limited to specialists; patients had no direct interaction	Minimal patient engagement; technology primarily enhanced provider diagnostic capacity
S07	(Baykemagn, Nigatu, Fikadie, & Tilahun, 2024)	Cross-sectional	2024	Rural primary health workers	mHealth guidelines app	PHC workers	Rural Ethiopia	Place, Occupation, SES, Education	Severe shortages of data, smartphones, stable electricity hindered access to the guideline tool	Poor availability of smartphones meant reliance on shared devices; low digital literacy worsened usability	Engagement remained low without structured training and mentorship
S08	(Tolera, Oljira, Dingeta, Abera, & Roba, 2022)	Cross-sectional	2022	Facility staff	EMR	Health workers	Dire Dawa	Occupation, Education, SES	EMR available only in portion of facilities; older workers had lower access	Use varied by cadre, training, experience, and exposure to ICT environments	Peer support and collaboration enhanced sustained engagement with the EMR
S09	(Gebeyew et al., 2025)	Cross-sectional	2025	HMIS staff and clinicians	Digital Data Hub	Nurses, HMIS workers	East Gojjam	Occupation, Education, Age	System design errors led to 42% rejection rate, limiting access to complete data	Use driven by trust in the platform and user perception of its stability	Engagement strongly tied to perceived usefulness, reliability, and accuracy of the system
S10	(A. Arega & Sharma, 2023; T. Arega, Mulatu, Alemayehu, Mussa, & Dheresa, 2022)	Comparative	2024	IT academics	HIS platforms	IT and research professionals	Ethiopia & India	Education, SES, Social capital	Academic institutions had stable internet access; India had stronger infrastructure than Ethiopia	India demonstrated higher and more consistent use due to stronger training culture	Researchers showed high engagement, motivated by academic productivity and data needs
S11	(Hailemariam et al., 2023a; Hailemariam et al., 2023b)	Qualitative	2024	HEWs & administrators	eCHIS	HEWs	Wogera District	Place, Religion, Social capital, SES	Unreliable power and weak networks restricted fair access to eCHIS	Use influenced by ICT familiarity; HEWs with higher schooling performed better	Engagement improved due to involvement of religious and community leaders
S12	(Bramo, Desta, & Syedda, 2022)	Ethnographic	2022	PLHC providers	ICT-HIS	PHC providers	Southern Ethiopia	Culture, Occupation, SES, Social capital	Infrastructure deficits (computers, network) constrained access	Use shaped by on-the-job training, workload, and competing tasks	Cultural norms affected provider willingness to use HIS; facility networks encouraged adoption
S13	(M. Tegegne & Wubante, 2022)	Systematic review	2022	Health workforce	ICT (general)	National providers	Nationwide	Education, Occupation, SES	ICT access uneven across regions due to limited infrastructure	Staff ICT skills determined ability to use HIS and mHealth systems	Engagement low in institutions lacking supportive digital culture
S14	(Wondimu, Abawari, & Kebede, 2025)	Cross-sectional	2025	PHC workers	mHealth ANC tools	Pregnant women	Bench-Sheko	Place, Marginalized groups, Education	Rural pregnant women faced barriers including lack of phones and network	System use dependent on worker training and community readiness	Engagement restricted by infrastructural and network constraints
S15	(Assaye, Kassa, Belachew, Tizie, & Worku, 2023)	Cross-sectional	2023	Physicians	Web platforms, apps	Physicians	Nationwide	Education, Age, Occupation	High access due to professional smartphone/computer ownership	Physicians displayed strong digital competence	High engagement through professional online networks and evidence-seeking culture
S16	(M. D. Tegegne et al., 2023)	Cross-sectional	2023	Health professionals	DHIS2, ICT tools	Providers	Gondar	Education, Age, SES	Digital divide observed—older and lower SES staff had reduced access	Higher education levels associated with more effective DHIS2 use	Peer collaboration influenced consistent system engagement
S17	(Sagaro, Battineni, & Amenta, 2020)	National study	2020	Health workers & programmers	Telemedicine	Providers & ICT teams	National	Place, SES, Occupation	Telemedicine access highly limited by ICT infrastructure and cost	Use hindered by low ICT skills and affordability issues	Engagement low due to institutional resistance
S18	(Sahelie et al., 2025)	Mixed-method	2025	Somali pastoralists	Mobile clinics & mHealth	Pastoralist communities	Somali Region	Place, Ethnicity, Language, Gender, Education, SES	Mobile clinics dramatically improved access for nomadic communities	Low literacy hindered use of SMS or app-based systems	CHW and clan networks improved trust and engagement
S19	(Zerfu et al., 2025)	Multi-region evaluation	2025	PHCU staff	DHIS2 (online/offline)	PHC providers	Oromia, Amhara, SNNP, Tigray	Place, Ethnicity, Education, SES	Offline mode improved access in low-network areas	Use depended on training quality and administrative support	Peer-to-peer networks strengthened continued engagement
S20	(Manyazewal, Woldeamanuel, Blumberg, Fekadu, & Marconi, 2021)	Systematic review	2021	National health system	Mixed digital tools	Providers & communities	Nationwide	Place, Ethnicity, SES, Disability, Marginalized groups	Rural–urban divide remained a major barrier to equitable digital access	Low smartphone penetration and low digital literacy restricted use	Engagement shaped by trust in health workers and digital competence
S21	(Getachew, Woldeamanuel, & Manyazewal, 2022)	Cross-sectional	2022	TB/HIV providers	Digital TB/HIV tools	Clinicians	Addis Ababa & regions	Occupation, Education, Marginalized groups	Strong access in urban facilities, weaker in peripheral areas	Higher education improved correct use of tools	Engagement closely linked to performance expectations and accountability culture

Stage 4: data extraction and charting

Data were extracted using a standardized charting form capturing: (i) Author, year, and study design; (ii) population characteristics and setting; (iii) types of DHIs and exposures; (iv) study features and methodological approach; (v) reported equity-related findings; and (vi) identified barriers, enablers, and recommendations. Extraction was conducted by one reviewer and independently verified by another. Accuracy was ensured by cross-checking parallel extraction outputs.

Findings were thematically analyzed and mapped onto the PROGRESS-Plus framework to examine how (DHTs) intersect with social-stratification domains. Variables of interest were summarized in structured tables.¹³

Stage 5: collating, summarizing, and reporting results

Quantitative data (counts, frequencies related to barriers, regions, and technologies) were processed and analyzed using Microsoft Excel and STATA. Qualitative findings (free text from articles) underwent reflexive thematic analysis using Braun & Clarke's 6-phase approach.¹⁴ A hybrid (inductive–deductive) codebook was developed based on predefined equity domains and emerging concepts.

Quantitative and qualitative findings were integrated using joint displays to show convergence and divergence across datasets. Emerging themes were further interpreted using the NASSS framework (non-adoption, abandonment, scale-up, spread, sustainability) to understand implementation dynamics.¹⁵

All findings were systematically organized using the PROGRESS-Plus equity framework, which includes:

Core domains: Place, race/ethnicity/culture/language (including religion), Occupation, Gender/sex, Education, Socioeconomic status, Social capital

“Plus” factors: Age, Disability/complex needs, Sexual orientation, Marginalized populations (e.g., mobile groups, homeless), Technology type.^16,17

An intersectional approach was applied. A domain was considered to demonstrate a consistent digital health inequity if ≥75% of studies referencing it reported similar disadvantage. Evidence matrices and heat maps were used to visually synthesize patterns across themes, regions, and technologies.¹⁸

Conceptual framework

The methodological analysis integrated three frameworks sequentially:

PROGRESS-Plus – used as the primary analytical lens to systematically map inequities across core and “Plus” social stratifiers.

NASSS Framework – applied secondarily to interpret implementation barriers and system-level complexity influencing digital health adoption.

WHO Digital Health Intervention Taxonomy – used to classify DHTs by primary user group (clients, providers, health system managers, and data services) to support international comparability.

Together, these frameworks provide a structured, transparent, and equity-focused foundation for synthesizing findings and interpreting digital health transformation in Ethiopia's PHC system (Figure 2).

Figure 2.

PROGRESS plus framework.

Quality appraisal

Although formal quality assessment is optional in scoping reviews, methodological rigor was assessed to contextualize evidence strength. Tools included: The Newcastle-Ottawa Scale, a validated tool for assessing the quality of non-randomized studies.¹⁹ We also used ROVIS tool for checking the quality of systematic reviews. The Mixed Methods Appraisal Tool (MMAT) was used to appraise qualitative, quantitative, and mixed-methods studies within a systematic review.²⁰ The included studies’ methodological validity and the quality of their conclusions were scrutinized. Studies were rated as high (≥80%), moderate (60–79%), or low (<60%) quality. All included studies met at least moderate quality standards and were retained for synthesis.

The WHO has established a standardized framework for classifying DHIs based on their primary user groups: clients, healthcare providers, health system managers, and data services. This taxonomy facilitates a common global language for the planning, implementation, and evaluation of digital health solutions.

Results

Study characteristics

Twenty-one studies conducted between 2015 and 2025 met the inclusion criteria. These employed a range of quantitative, qualitative, mixed-methods, ethnographic, and scoping review designs. They examined diverse DHTs implemented across Ethiopia's primary care systems, including SMS-based platforms, smartphone applications, eCHIS, electronic medical records (EMRs), AI diagnostic tools, telemedicine services, digital health data hubs, and mobile health platforms.

Study settings spanned remote rural communities such as pastoralist regions in Somali and Bench-Sheko to urban hospitals in Addis Ababa and Dire Dawa, reflecting substantial geographic and infrastructural diversity.

Study designs and populations

The included studies employed a wide array of methodological approaches. Cross-sectional surveys were the most common (n = 12), primarily assessing digital health readiness, access, and use among health workers.^21,22 Qualitative and ethnographic studies (n = 4) explored sociocultural and contextual drivers of digital health adoption, including community trust, gender norms, and digital health literacy.^17,23

Randomized and cluster trials (n = 3) assessed the effectiveness of interventions such as SMS-based maternal health messaging²⁴ and mHealth reporting tools for HEWs for community-based reporting.²⁵ Two systematic reviews synthesized national-level evidence on digital health access, ICT readiness, and system-wide adoption.^26,27

Study participants spanned diverse groups, including HEWs, clinical staff, patients, mothers, pastoralist communities, IT professionals, and national health workforce cohorts. HEWs were the most frequently studied group, reflecting their central role in Ethiopia's community-based PHC model.

Digital health technologies assessed

The reviewed studies evaluated a broad spectrum of DHTs across varied settings. SMS-based mHealth interventions^24,25,28 were frequently used in rural areas with low smartphone penetration, supporting health communication, reminders, and maternal health follow-up.

Between 2020 and 2025, smartphone-based platforms such as eCHIS and clinical decision-support applications^29–31 became increasingly prominent, reflecting the expanding digital health adoption among health workers.

Facility-based digital health information systems, including EMRs, DHIS2, and digital health data repositories,^22,32,33 were commonly examined for their contributions to service delivery, data quality, and routine reporting.

Emerging innovations such as telemedicine and AI-based diagnostic tools^3,34 highlighted the growing potential of advanced digital health solutions. Mobile clinic–linked mHealth systems were uniquely used to reach nomadic and geographically isolated communities.¹⁶

PROGRESS-plus domains identified

All studies identified multiple PROGRESS-Plus domains that influenced access to, use of, or engagement with digital health technologies. Place of residence was the most frequently reported factor, with rural and remote populations facing persistent barriers such as poor network connectivity and unreliable electricity.^16,25,35

Education, especially digital health literacy and ICT competency, significantly influenced digital health adoption among both users and providers.^22,29,33

Occupation also shaped engagement: HEWs, nurses, physicians, and IT personnel demonstrated varying levels of competency and comfort with technologies, reflecting differences in training, workload, and professional responsibilities.

Socioeconomic status (SES) influenced device ownership, smartphone access, and the affordability of digital health services, limiting participation among lower-income groups.

Gender shaped access and engagement, particularly among female HEWs and women in rural households, who faced both workload-related and sociocultural constraints.^16,25,28

Finally, social capital and cultural norms played a significant role in shaping trust, community acceptance, and peer support for digital health tools.^23,31,36

Collectively, these findings illustrate the multifaceted nature of digital health inequities in Ethiopia and underscore the need for interventions that address both structural and sociocultural determinants (Table 4).

Access, use, and engagement patterns

The Access–Use–Engagement heatmap (Figure 3), with further details provided in, synthesizes digital health inequity patterns across PROGRESS-Plus domains. The results reveal consistent clustering of inequities across structural and sociocultural determinants.

Figure 3.

Digital health inequity by PROGRESS PLUS domain in Ethiopia, 2025.

Access to digital health technologies

Access inequities emerged as the most pervasive challenge, with notably high disparities associated with technology type (100%) and marginalized groups (83.3%). Substantial inequities were also observed across occupational categories (76.0%) and place of residence (70.6%), underscoring the persistent disadvantages faced by rural and remote communities. Education and socioeconomic status each exhibited digital health inequity levels of 66.7%, reflecting the compounded effects of digital health literacy gaps, resource constraints, and structural barriers on digital health participation.

Remote and pastoralist regions consistently reported barriers linked to unreliable connectivity, insufficient electricity, and limited device availability.^16,25,28,35 SMS-based systems reached wider populations but remained constrained by language and low literacy.²⁴ Higher-end digital health tools, including AI diagnostics, telemedicine, web-based platforms, were largely confined to urban and specialized facilities,^3,34,37 reinforcing structural inequalities shaped by place, SES, and occupational role.

Use of digital health technologies

Use patterns were shaped predominantly by users’ digital health literacy, the quality and consistency of training, professional roles, and workload conditions. As reflected in (Figure 3), inequities in the use of DHTs were highest for technology type (100%) and marginalized groups (83.3%). Education (72.2%) and occupation (72.0%) also contributed significantly to uneven utilization, highlighting disparities in ICT competence and role-related access to digital health tools. Age-related differences further influenced use patterns, with digital health inequity level of 66.7%, indicating that older users were less likely to adopt or effectively operate digital health systems.

Professionals with higher education or ICT competence, including physicians, nurses, IT personnel demonstrated greater proficiency using EMRs, eCHIS, DHIS2, and analytics tools.^29,38,39 Limited or inconsistent training, particularly among HEWs, constrained sustainable system use.^23,28,30 Tools requiring advanced ICT skills (AI, telemedicine) were used primarily in tertiary facilities,^3,34 reinforcing occupational disparities.

Engagement with digital health technologies

Engagement with digital health tools was shaped by levels of trust, cultural congruence, peer support, and overall institutional readiness. As illustrated in (Figure 3), the highest engagement inequities were observed among marginalized groups (100%), followed by education (83.3%) and race/ethnicity/language/culture (83.3%), reflecting the strong influence of sociocultural and linguistic factors on sustained participation. Occupational differences (76.0%) and age-related disparities (77.8%) further contributed to unequal engagement, indicating that professional role, generational familiarity with technology, and broader social positioning significantly affected users’ ability and willingness to remain actively involved with digital health systems.

HEWs showed strong engagement where digital health platforms aligned with daily workflows and had local legitimacy.^25,31 Pastoralist communities engaged effectively with mobile clinic–supported systems due to high trust in community-based providers.¹⁶ In facilities, peer support, mentorship, and managerial reinforcement enabled sustained EMR/DHIS2 use.^22,32,36 Engagement declined where digital health tools were poorly integrated into workflows, lacked cultural resonance, or faced institutional resistance.^3,23,30

Integrated interpretation across access–use–engagement

Synthesizing evidence across all studies, and integrating heatmap results, reveals that Ethiopia's digital health inequities are deeply socio-structural rather than purely technological. Place of residence, education, SES, occupation, and marginalized-group status consistently shape inequities across all three dimensions. Technology type and marginalized group status show the highest digital health inequity levels across Access, Use, and Engagement (83.3–100%), indicating systemic barriers to inclusive digital health participation.

Education and digital health literacy strongly predict both use and long-term engagement, while occupational hierarchies shape competence and confidence in navigating digital health systems. Sociocultural domains, including gender norms, linguistic diversity, social roles, and community trust, lay critical roles in determining meaningful engagement. These intersectional patterns underscore the need for equity-centered digital health strategies that prioritize rural digital health infrastructure, tailored capacity-building, localized content, culturally responsive implementation, and institutional readiness strengthening.

Summary of findings

Analysis of supported by the detailed PROGRESS-Plus evidence in, shows that digital health inequities in Ethiopia follow a highly consistent stratification pattern across access, use, and engagement. Place of residence remains the strongest determinant: rural and pastoralist communities continue to face long travel times, limited network connectivity, and low smartphone ownership, though offline DHIS2 deployments and mobile clinics have partially reduced these constraints. Linguistic, ethnic, and cultural factors significantly shape usability and acceptability; local-language SMS tools routinely outperform English-based or non-localized applications, which experience high rejection rates (Figure 4).

Figure 4.

PROGRESS-Plus equity analysis in Ethiopian digital health.

Occupational disparities are pronounced, as HEWs and frontline staff operate with device shortages, heavy dual-reporting workloads, limited mHealth or analytics training, and insufficient IT support, whereas specialists and IT personnel have greater exposure to advanced systems. Gendered patterns persist: female HEWs frequently rely on shared devices and shoulder higher digital health workloads, while women in communities demonstrate stronger engagement when supported by CHWs or culturally aligned interventions.

Education and socioeconomic status form a clear gradient of digital health readiness and proficiency, low-literacy groups depend on SMS-based tools, while higher-educated health workers are more capable of using EMRs, analytics, and web-based platforms; affordability of data and airtime further shapes use among poorer households. Social capital and institutional readiness consistently mediate sustained engagement, with peer networks, managerial facilitation, and leadership involvement emerging as key enablers, whereas mistrust, low incentives, and weak infrastructure undermine uptake of digital health hubs and telemedicine.

Across the PLUS dimensions, age shows a predictable gradient: younger workers adopt technologies more rapidly, while older HEWs require more time, report higher anxiety, and engage less consistently. Disability remains substantially underrepresented, with limited adaptation of tools to diverse needs and minimal evidence of disability-responsive design. Marginalized groups, including pastoralists, remote mothers, and low-literacy communities, experience intersecting barriers but demonstrate strong engagement when tools are culturally tailored and delivered through trusted intermediaries such as CHWs or HITs.

Finally, technology type itself functions as a major axis of inequity: basic-phone-compatible SMS and offline systems enable widespread access and engagement, whereas AI, EMRs, and app-based platforms remain confined to urban, well-resourced settings and specialist cadres, requiring stable infrastructure and sustained institutional support. Collectively, these findings illustrate how structural conditions, sociocultural context, and technology design interact to produce durable inequities across the Access–Use–Engagement continuum.

Discussion

This scoping review offers one of the most comprehensive examinations of digital health equity in Ethiopia's PHC system, applying the PROGRESS-Plus framework to interpret access, use, and engagement disparities across eleven social domains. The discussion synthesizes thematic findings, interprets systemic implications, and proposes future research and policy directions.

Access to digital health technologies

This scoping review demonstrates that inequities in access to DHTs in Ethiopia are deeply rooted in structural determinants, including geography, socioeconomic status, technology type, and infrastructural availability. Rural, pastoralist, and remote communities experience the greatest exclusion due to persistent limitations in network connectivity, electricity, smartphone ownership, and health facility readiness, patterns consistently reflected across PROGRESS-Plus domains such as place of residence, SES, occupation, and marginalized populations.^16,36,40 Offline-capable tools such as DHIS2 and eCHIS reduce technology barriers, yet their implementation remains uneven, and core infrastructure gaps continue to reinforce spatial inequities.

Comparative evidence highlights gaps in Ethiopia's policy frameworks. While the Digital Health Blueprint, the Information Revolution Roadmap, and the National Digital Health Strategy draft articulate aspirations for digital health equity, they lack concrete, measurable equity indicators for rural and underserved regions.^16,17,25 In contrast, Rwanda's National Digital Health Strategic Plan explicitly integrates rural connectivity indicators and youth-focused digital health initiatives, producing more equitable rollout outcomes.⁴¹

Global guidance, including the WHO–ITU Global Strategy on Digital Health and the African Union Digital Transformation Strategy (2020–2030), similarly emphasizes rural access, affordability, and inclusion as foundational equity dimensions.⁴² Ethiopia's slow progress in operationalizing such guidance has resulted in persistent urban–rural disparities, leaving advanced technologies, such as EMRs, telemedicine, AI diagnostics, and analytics platforms, largely confined to tertiary and urban facilities.

Sociocultural characteristics also influence access. Individuals with low literacy, limited formal education, and restricted economic means encounter substantial barriers to device ownership and SMS use. Women, especially female HEWs, report higher rates of device sharing and reduced access to personal mobile phones, further compounding gender-related disparities in digital health participation. Financial constraints, including airtime costs and data affordability, remain prominent access barriers, especially in Somali and SNNP regions,^33,43 echoing UNICEF and AU calls for pro-poor digital health inclusion strategies.^6,32

Use of digital health technologies

Even when access enablers are overcome, disparities persist in the use of digital health tools due to gaps in digital health literacy, training adequacy, workload distribution, and professional hierarchies. HEWs, who shoulder the greatest burden of primary health service delivery, face substantial challenges using complex platforms like eCHIS and DHIS2 due to inconsistent training, limited ICT exposure, and competing routine responsibilities.^23,26,33 Conversely, physicians, nurses, and IT personnel demonstrate higher confidence and proficiency in EMRs, HMIS, and data analytics tools, revealing a professional digital health skills gradient across the health workforce.

Educational background is a critical determinant of use. Individuals with secondary or postsecondary education are far more likely to interpret digital health data, navigate complex interfaces, and integrate digital health insights into decision-making processes. This aligns with the World Bank Digital-in-Health report, which warns that digitalization can exacerbate digital health inequity unless literacy-targeted training investments are prioritized.⁴⁴ Ethiopia's Digital Education Strategy attempts to strengthen workforce digital health skills but lacks differentiated training pathways for low-literacy HEWs, limiting its equity impact.

Gender dynamics influence use as well. Female HEWs frequently confront heavier digital digital health workloads, safety concerns during home visits, and device-sharing norms that constrain meaningful use. However, when digital health tools are gender-responsive, culturally aligned, and supported by peer mentoring, their use improves significantly, reflecting WHO recommendations on gender-sensitive digital health design.^45,46 Comparative insights from Rwanda demonstrate the value of embedding gender-responsive and youth-focused digital health capacity-building within national strategies.⁴⁷

Socioeconomic constraints further hinder use. Lack of airtime, limited device charging options, and unstable connectivity reduce the frequency and reliability of digital health interactions. International experiences, such as digital health subsidy programs in South Africa and Brazil, illustrate how affordability measures can improve digital health use among marginalized populations.^48,49

Engagement with digital health technologies

Engagement, defined as sustained, consistent, and meaningful use of digital health tools, is shaped by institutional culture, sociocultural compatibility, trust, workflow integration, disability inclusion, and supportive supervision. The review shows that communities with low literacy, those in pastoralist areas, remote households, and individuals with disabilities experience structural exclusion from long-term engagement due to inaccessible interfaces, language barriers, and weak user support systems.^3,16,23,29

Cultural and linguistic adaptation significantly improves engagement. Local-language SMS reminders, culturally tailored maternal health tools, and CHW- or CBHIT-supported digital health services enhance trust and uptake, aligning with UNICEF's emphasis on gender-responsive and culturally relevant digital health designs.⁵⁰ However, Ethiopia's digital health strategies, including the eCHIS Implementation Guide and the Digital Health Regulatory Framework draft, lack clear operational directives on linguistic and cultural adaptation.⁵¹ Countries such as India and South Africa offer stronger models by embedding language inclusivity and marginalized-group support within national digital health standards.^52,53

Engagement is also contingent on institutional support. Facilities with strong leadership commitment, peer-learning environments, and dedicated supervision demonstrate higher rates of EMR and DHIS2 adherence. For HEWs, supportive digital health peer networks, community trust structures, and culturally resonant delivery models significantly influence long-term engagement patterns.^23,26

Disability inclusion is the most under-addressed engagement domain. Digital health platforms rarely incorporate universal design features, such as screen readers, voice navigation, or simplified interfaces, leaving individuals with disabilities systematically excluded. While policy documents acknowledge the need for disability inclusion, no operational standards or monitoring indicators exist, contrasting sharply with disability-inclusive digital health policies in South Africa and Brazil.^48,49,51

Integrated interpretation across access–use–engagement

Taken together, the findings reveal a cascading equity mechanism across the Access–Use–Engagement continuum. Structural determinants (infrastructure, SES, place of residence) restrict access; resource and skill gaps (education, occupation, workload, and training) constrain use; and sociocultural and institutional dynamics (language, trust, disability inclusion, leadership, workflow integration) shape sustained engagement. Technology type acts as an additional axis of inequity:

Basic-phone and offline tools (SMS, DHIS2 offline, eCHIS offline) broaden inclusion.

High-end, resource-intensive tools (AI diagnostics, app-based platforms, cloud EMRs) are accessible only in well-resourced, urban environments.

These patterns align with global frameworks; WHO, ITU, UNICEF, World Bank, and underscore Ethiopia's urgent need for equity-sensitive digital health governance, including:

Equity indicators embedded in national digital health strategies.

Differentiated digital health literacy pathways for diverse cadres (e.g., HEWs vs. clinicians).

Localized, multilingual, culturally adapted designs for marginalized communities.

Universal design and disability-inclusive standards across all digital health platforms.

Affordability and access interventions, including subsidized mobile data, shared digital health community access points, and offline-first designs.

Peer networks, community digital health champions, and participatory co-design to strengthen trust and engagement.

Despite the breadth of evidence, gaps remain. Intersectional inequities, such as gender interacting with SES or rurality are underexplored. Most studies focus on short-term adoption rather than long-term engagement or system sustainability. Disability remains the least examined PROGRESS-Plus dimension. Addressing these gaps is essential for designing equitable, inclusive, and sustainable digital health systems capable of reaching Ethiopia's most underserved populations.

Conclusion

This scoping review provides the first comprehensive synthesis of digital health inequities in Ethiopia's PHC system using the PROGRESS-Plus framework. Findings reveal persistent disparities in access, use, and engagement with digital health technologies, influenced by intersecting factors such as geography, gender, education, occupation, and socioeconomic status. Despite progressive national strategies, implementation gaps remain, particularly in addressing disability inclusion, cultural adaptation, and rural digital health access.

To ensure equitable digital transformation, Ethiopia should adopt equity-disaggregated monitoring systems, strengthen rural and gender-responsive digital health infrastructure, and promote inclusive, user-centered design. Future research should focus on longitudinal and participatory approaches to better understand evolving inequities and inform evidence-driven digital health policies aligned with Universal Health Coverage and the Sustainable Development Goals.

Unique contribution

This study provides a unique contribution by systematically mapping digital health inequities in Ethiopia's PHC system using the PROGRESS-Plus framework. It integrates evidence across access, use, and engagement domains, offering a comprehensive picture of how socio-demographic factors and technology types shape digital health adoption. By identifying consistent inequities related to residence, education, socioeconomic status, age, and technology type, and highlighting under-studied areas such as gender, disability, and social capital, the study advances knowledge and informs equity-sensitive digital health strategies.

Gap it fills

The study fills a critical gap by examining how contextual barriers, population characteristics, and technology interact in low-resource settings, a perspective rarely addressed in Ethiopia and comparable LMICs. Many existing studies lacked disaggregation across PROGRESS-Plus domains, underrepresented marginalized populations (e.g., rural residents, people with disabilities), and focused primarily on tools rather than systemic equity drivers. Cross-sectional designs limited long-term insights, and grey literature and community voices were often excluded, restricting generalizability.

Limitations of the review

This review has a number of shortcomings even though it provides a thorough synthesis of digital health equity in Ethiopia. Disaggregation across the entire PROGRESS-Plus framework was lacking in many studies, and social capital, religion, and disability were frequently absent. With only 28% of studies offering sex-disaggregated data and only 5% mentioning disability, gender and disability were underrepresented.

The majority of studies ignored the viewpoints of marginalized groups in remote areas because they were urban-focused. Long-term insights were limited by the prevalence of cross-sectional designs. Seldom was community voices heard, particularly those of rural women or people with disabilities. Grey literature may have been left out due to biases in language and publication. Furthermore, the majority of studies focused on tools rather than systemic equity drivers, and very few looked at the policy-practice gap. The findings’ depth of equity and generalizability are limited by these gaps.

Future research directions

Future research should employ longitudinal, intersectional, and participatory designs to assess how DHIs influence equity over time. Mixed-methods approaches that integrate user experience, social determinants, and implementation science perspectives are needed to understand the mechanisms linking technology to equitable health outcomes.

Special attention should be given to under-studied domains such as disability inclusion, social capital, religion, and institutional trust. Comparative studies across LMICs could identify scalable equity models and best practices for localization. Additionally, experimental and realist evaluation designs can help test the effectiveness of equity-oriented digital health innovations, including gender-responsive, age-sensitive, and context-tailored tools. Strengthening partnerships between academic institutions, digital health innovators, and community organizations will be critical to advancing evidence-based, inclusive digital health transformation across Ethiopia's PHC system.

Policy recommendations

1. Strengthen Digital Health Foundations

Expand rural connectivity, electricity supply, and device distribution through coordinated public–private partnerships.

Implement interoperable, offline-first architectures suitable for remote environments.

Enforce national data governance and interoperability standards.

2. Build Human and Institutional Capacity

Deliver role-specific digital health literacy and ICT competency training with continuous refresher modules.

Integrate digital health into pre-service curricula for all health cadres.

Strengthen digital health leadership, IT support units, and organizational readiness.

3. Promote Equity-Driven, Contextualized Digital Health Design

Localize tools through translation, culturally aligned content, and low-literacy interfaces.

Employ participatory co-design involving HEWs, CHWs, pastoralists, and marginalized users.

Incorporate disability-inclusive features and universal design standards.

4. Ensure Sustainable Financing and Scalable Implementation

Transition from fragmented pilot funding to national pooled financing.

Integrate digital health into routine district health budgets.

Adopt transparent procurement frameworks ensuring long-term sustainability.

5. Monitor and Address Digital Health Inequities Systematically

Institutionalize PROGRESS-Plus–aligned digital health equity dashboards.

Require demographic and geographic disaggregation in all digital health reporting.

Develop district-level guidelines for identifying and addressing inequities.

Key implications for practice and policy

Priority Area	Implications
Rural Infrastructure	Connectivity, electricity, and device access are foundational to digital health equity.
Digital Health Literacy	Role-specific, continuous training is essential for HEWs and frontline workers.
Culturally Responsive Design	Local-language tools substantially increase usability and engagement.
Institutional Readiness	Leadership, workflow alignment, and IT support determine sustainability.
Equity Monitoring	PROGRESS-Plus disaggregation is critical for identifying disparities.
Technology Choice	Offline-first tools improve inclusion; advanced tools require equity safeguards.
Community Trust	Chws And Pastoralist Networks Enhance Engagement And System Legitimacy.

Supplemental Material

sj-docx-1-dhj-10.1177_20552076251408535 - Supplemental material for Mapping inequities in digital health transformation within Ethiopia's primary health care system using PROGRESS-plus: Scoping review

Supplemental material, sj-docx-1-dhj-10.1177_20552076251408535 for Mapping inequities in digital health transformation within Ethiopia's primary health care system using PROGRESS-plus: Scoping review by Ibsa Mussa and Rabelani Dagada in DIGITAL HEALTH

Footnotes

Acknowledgments

The authors would like to acknowledge the University of South Africa (UNISA) for providing the necessary resources and institutional support that enabled the preparation of this report and the compilation of the manuscript.

Abbreviations

AI: Artificial Intelligence; CHWs: Community Health Workers; DHTs: Digital Health Technologies; DHIS2: District Health Information Software 2; eCHIS: Electronic Community Health Information System; eHealth: Electronic Health; EHRs: Electronic Health Records; EMR: Electronic Medical Record; FMOH: Federal Ministry of Health (Ethiopia); EPHI: Ethiopian Public Health Institute; HEWs: Health Extension Workers; HITs: Health Information Technicians; ICT: Information and Communication Technology; ITU: International Telecommunication Union; HSTP: Health Sector Transformation Plan; LMICs: Low- and Middle-Income Countries; mHealth: Mobile Health; MOE: Ministry of Education; PHC: Primary Health Care; PHCUs: Primary Health Care Units; SES: Socioeconomic Status; SMS: Short Message Service; SNNP: Southern Nations, Nationalities, and Peoples Region; UI: User Interface; UHC: Universal Health Coverage; UNICEF: United Nations Children's Fund; WHO: World Health Organization

ORCID iD

Ibsa Mussa

Ethical approval

All sources were secondary, and ethical clearance was not required under UNISA Policy on Research Ethics (2024, Sec. 7.5).

Authors contributions

All authors contributed to the conception and design of the study, including the development of the main conceptual framework and proof outline. IM led the model design, developed the computational framework, and conducted the data analysis. IM and RD co-authored the initial draft of the manuscript. All authors reviewed the results, contributed to the interpretation of findings, and participated in revising the manuscript. IM supervised the overall study process. All authors read and approved the final version of the manuscript for publication.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Availability of data and materials

The original contributions presented in the study are included in the article/supplementary files, further inquiries can be directed to the corresponding author/s.

Reflexivity statement

The authors of this paper are based in Ethiopia and South Africa and bring interdisciplinary expertise in public health, digital transformation, and equity-focused health systems research. The lead author is a male public health specialist and early-career researcher based in Ethiopia with extensive experience in digital health policy and equity analysis. The co-author is a senior male scholar specializing in digital transformation and systems leadership in Southern Africa. While both authors identify as male and are based at African institutions, the research emphasizes inclusivity through its methodological focus on marginalized populations (e.g., rural women, persons with disabilities, and pastoralist communities). Future collaborations will seek to strengthen gender and geographic diversity in research teams to better reflect the populations studied.

Supplemental material

Supplemental material for this article is available online.

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