A Systematic Review of Digital Health’s Relevance to Population-Level Health, Service, and Equity Indicators in the Eastern Mediterranean Region

Joukar, M.; Shahali, Sh.; Rahimi, R.

doi:10.58209/hehp.14.2.401

A Systematic Review of Digital Health’s Relevance to Population-Level Health, Service, and Equity Indicators in the Eastern Mediterranean Region

Document Type : Systematic Review

Authors

M. Joukar ¹

Sh. Shahali ¹

R. Rahimi ²

¹ Department of Reproductive Health and Midwifery, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran

² Department of Medical Informatics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran

10.58209/hehp.14.2.401

Abstract

Aims: This systematic review synthesized evidence on the impact of digital health on health outcomes, services, equity, and demographic indicators in the Eastern Mediterranean Region.
Information & Methods: Following PRISMA 2020 guidelines, we conducted a systematic search of PubMed, Scopus, Web of Science, and IEEE Xplore for English-language studies published from January 2010 to June 12, 2026. Eligible studies evaluated digital health technologies in World Health Organization Eastern Mediterranean Region countries and reported health, health-service, health-equity, demographic, or implementation-related outcomes. We screened references and conducted targeted searches of resources from World Health Organization and the World Health Organization Regional Office for the Eastern Mediterranean. Because of heterogeneity in study designs, technologies, populations, and outcomes, we synthesized the findings narratively.
Findings: Of the 7,894 records identified, 11 studies met the inclusion criteria. Evidence was organized into five themes: digital health for maternal and reproductive prediction and decision support; maternal, neonatal, and health-service outcomes; health inequalities; policy, social, cultural, and infrastructural determinants; and population-level demographic indicators. Digital health showed potential to improve clinical decision-making, healthcare access, and service delivery. However, equity outcomes depended on factors such as digital literacy, socioeconomic status, infrastructure availability, and contextual adaptation. Implementation success was influenced by governance, interoperability, workforce capacity, sustainable investment, and user engagement. No study directly assessed macro-level demographic outcomes, such as life expectancy or population aging.
Conclusion: Digital health and artificial intelligence in the Eastern Mediterranean Region have the potential to improve access to healthcare services, quality of care, and health-system performance.

Keywords

Digital Health

Health Equity

Systematic review

Subjects

Health Care

1- Mandil A, Rashidian A, Nour M, Fouad H, Hajjeh R. Enhancing capacity and use of digital health in the eastern Mediterranean region: An urgent priority for action. East Mediterr Health J. 2021;27(11):1031-3.

2- Al Shorbaji N. E-health in the Eastern Mediterranean Region: a decade of challenges and achievements. East Mediterr Health J. 2008;14(Supp.):157-173.

3- Basakha M, Mohaqeqi KSH, Pashazadeh H. Acceptance of information and communication technology by the elderly people living in Tehran. SALMAND Iran J Ageing. 2019;13(5):550-63. [Persian]

4- WHO. Recommendations on digital interventions for health system strengthening. Geneva: World Health Organization; 2019.

5- Ghahramani S, Hadipour M, Peymani P, Ghahramani S, Lankarani KB. Health-related quality of life variation by socioeconomic status: Evidence from an Iranian population-based study. J Educ Health Promot. 2023;12:287.

6- Wilson S, Tolley C, Mc Ardle R, Lawson L, Beswick E, Hassan N, et al. Recommendations to advance digital health equity: A systematic review of qualitative studies. NPJ Digit Med. 2024;7(1):173.

7- Johnson SA. “Maternal devices”, social media and the self-management of pregnancy, mothering and child health. Societies. 2014;4(2):330-50.

8- Kia ZR, Khajavian N, Rahmani R, Askari F. The Effect of Educational Intervention with Mobile Health Technology on COVID-19 Induced Stress among Pregnant Women: A Randomized Controlled Trial. J Midwifery Reprod Health. 2023;11(3):3782.

9- Asadi F, Jahangiri MS, Rahimi F. A comparative study of the national infertility registry system and the proposed model for Iran. Crescent J Med Biol Sci. 2019;6(3):318–324.

10- Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.

11- McArthur A, Cooper A, Edwards D, Klugarova J, Yan H, Barber BV, et al. Textual evidence systematic reviews series paper 1: Introduction to the revised JBI methodology and overview of recent changes. JBI Evid Synth. 2025;23(3):423-8.

12- Hong QN, Fàbregues S, Bartlett G, Boardman F, Cargo M, Dagenais P, et al. The mixed methods appraisal tool (MMAT) version 2018 for information professionals and researchers. Educ Inf. 2018;34(4):285-91.

13- CASP. CASP quantitative studies checklist [Internet]. Oxford: Critical Appraisal Skills Programme; 2018 [cited Oct 19, 2026]. Available from: https://casp-uk.net/casp-tools-checklists/

14- Wells GA, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of non-randomized studies in meta-analyses. Proceedings of the Symposium on Systematic Reviews: Beyond the Basics-Improving Quality and Impact. Oxford: St. Catherine’s College; 2000.

15- Wolff RF, Moons KG, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: A tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med. 2019;170(1):51-8.

16- Tyndall J. AACODS checklist. Adelaide: Flinders University, 2010.

17- Binghamton University Libraries. Grey literature: Appraising grey literature 2023 [Internet]. New York: Binghamton University; 2025 [cited Oct 19, 2026]. Available from: https://libraryguides.binghamton.edu/c.php?g=1369090&p=10116151

18- Popay J, Roberts H, Sowden A, Petticrew M, Arai L, Rodgers M, et al. Guidance on the conduct of narrative synthesis in systematic reviews. Lancaster: Lancaster University; 2006.

19- Sadr H, Zahiri Z, Nazari M, Bahadori MH, Ashoobi MT, Hoseini A. Optimizing clinical decisions in reproductive medicine with a hybrid AI predictive model. Big Data Comput Vis. 2025;5(4):287-306.

20- Farzandipour M, Jeddi FR, Gilasi HR, Shirzadi D. Clinical and para clinical information needs of infertility electronic health records in Iran: A Delphi study. Acta Inform Med. 2017;25(3):163-8.

21- Saleh S, El Arnaout N, Sabra N, El Dakdouki A, El Iskandarani K, Chamseddine Z, et al. Evaluating the impact of engaging healthcare providers in an AI-based gamified mHealth intervention for improving maternal health outcomes among disadvantaged pregnant women in Lebanon. Front Digit Health. 2025;7:1574946.

22- AlArab N, Nabulsi D, El Arnaout N, Dimassi H, Harb R, Lahoud J, et al. Reproductive health of Syrian refugee women in Lebanon: A descriptive analysis of the Sijilli electronic health records database. BMC Womens Health. 2023;23(1):81.

23- WHO. Digital health in the Eastern Mediterranean Region: A snapshot. Cairo: WHO Regional Office for the Eastern Mediterranean; 2024.

24- Moulaei K, Sheikhtaheri A, Ghafaripour Z, Bahaadinbeigy K. The development and usability assessment of an mhealth application to encourage self-care in pregnant women against COVID-19. J Healthc Eng. 2021;2021:9968451.

25- Pouriayevali B, Ehteshami A, Kohan S, Isfahani SS. Mothers’ views on mobile health in self‑care for pregnancy: A step towards mobile application development. J Educ Health Promot. 2023;12(1):308.

26- Venkateswaran M, Ghanem B, Abbas E, Khader KA, Ward IA, Awwad T, et al. A digital health registry with clinical decision support for improving quality of antenatal care in Palestine (eRegQual): A pragmatic, cluster-randomised, controlled, superiority trial. Lancet Digit Health. 2022;4(2):e126-36.

27- Mominkhan DM, Aldahmashi F, Almudeer AH, Alhmod AS, Alharbi MF, Alzubaidi LM, et al. Implementing telemedicine intervention in neonatal intensive care units: Augmented teleconsultation and real-time monitoring experience. Telemed Rep. 2025;6(1):50-7.

28- WHO. Global strategy on digital health 2020-2025. Geneva: World Health Organization; 2021.

29- WHO. Digital health action plan for the Eastern Mediterranean Region, 2024-2028. Cairo: WHO Regional Office for the Eastern Mediterranean; 2025.

30- WHO. The World Health Assembly endorses the extension of the Global Strategy on Digital Health to 2027 and approves the next phase for 2028-2033 [Internet]. Geneva: World Health Organization; 2025 [cited Oct 19, 2026]. Available from: https://www.who.int/news/item/23-05-2025-world-health-assembly-endorses-extension-of-the-global-digital-health-strategy-to-2027

31- Alzakari SA, Aldrees A, Umer M, Cascone L, Innab N, Ashraf I. Artificial intelligence-driven predictive framework for early detection of still birth. SLAS Technol. 2024;29(6):100203.

32- Innab N, Alsubai S, Alabdulqader EA, Alarfaj AA, Umer M, Trelova S, et al. Automated approach for fetal and maternal health management using light gradient boosting model with SHAP explainable AI. Front Public Health. 2024;12:1462693.

33- Husain L, Kitchens K, Raja S, Memon M. Bridging implementation gaps in digital health: A translational research imperative for equitable healthcare innovation. Clin Transl Sci. 2025;18(10):e70375.

34- WHO. Global patient safety report 2024. Geneva: World Health Organization; 2024.

35- Nittas V, Chavez SJ, Daniore P. Current practice and expert perspectives on cultural adaptations of digital health interventions: Qualitative study. JMIR Mhealth Uhealth. 2025;13:e59965.