Cited by 101Mobile Health and mHealth ApplicationsTelemedicine and Telehealth ImplementationICT in Developing Communities

The DOI matches its Crossref record; 39 of the 40 references it cites were found in a registry or an index; none of the 46 sources its claims cite is checked for support yet.

Assessing the feasibility of eHealth and mHealth: a systematic review and analysis of initiatives implemented in Kenya

Open access

Abstract

BACKGROUND: The growth of Information and Communication Technology in Kenya has facilitated implementation of a large number of eHealth projects in a bid to cost-effectively address health and health system challenges. This systematic review aims to provide a situational analysis of eHealth initiatives being implemented in Kenya, including an assessment of the areas of focus and geographic distribution of the health projects. The search strategy involved peer and non-peer reviewed sources of relevant information relating to projects under implementation in Kenya. The projects were examined based on strategic area of implementation, health purpose and focus, geographic location, evaluation status and thematic area. RESULTS: A total of 114 citations comprising 69 eHealth projects fulfilled the inclusion criteria. The eHealth projects included 47 mHealth projects, 9 health information system projects, 8 eLearning projects and 5 telemedicine projects. In terms of projects geographical distribution, 24 were executed in Nairobi whilst 15 were designed to have a national coverage but only 3 were scaled up. In terms of health focus, 19 projects were mainly on primary care, 17 on HIV/AIDS and 11 on maternal and child health (MNCH). Only 8 projects were rigorously evaluated under randomized control trials. CONCLUSION: This review discovered that there is a myriad of eHealth projects being implemented in Kenya, mainly in the mHealth strategic area and focusing mostly on primary care and HIV/AIDs. Based on our analysis, most of the projects were rarely evaluated. In addition, few projects are implemented in marginalised areas and least urbanized counties with more health care needs, notwithstanding the fact that adoption of information and communication technology should aim to improve health equity (i.e. improve access to health care particularly in remote parts of the country in order to reduce geographical inequities) and contribute to overall health systems strengthening.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This systematic review inventories 69 eHealth projects implemented in Kenya, finding that most were mHealth initiatives concentrated in urban counties and rarely rigorously evaluated. It concludes that eHealth activity is poorly aligned with marginalized areas and Ministry of Health priorities, limiting scale-up and equity impact.

Key findings

  • Of 69 eHealth projects, 47 (69%) were mHealth, 9 (13%) health information systems, 8 (11%) eLearning, and 5 (7%) telemedicine.
  • Geographic distribution was skewed: Nairobi had 24 mapped projects, while least urbanized counties such as Turkana, Wajir, and Garissa had 1, 1, and 2 projects respectively; Samburu, Marsabit, and Mandera had none. Of 14 marginalized counties, 10 had at least one project, with Kilifi highest at 5 and Kwale at 4.
  • Health focus was mainly primary care (19; 28%), HIV/AIDS (17; 25%), and maternal and child health (11; 16%).
  • Evaluation was limited: only 28 of 69 projects (41%) reported any evaluation, and only 8 (12%) were randomized controlled trials; 41 projects (59%) had no reported evaluation.

Methods

  • Systematic review of peer-reviewed and non-peer-reviewed sources, including PubMed, Embase, Web of Science, Econlit, SocIndex, Cochrane, Google Scholar, organizational websites, blogs, personal communication with implementers, and hand searches; no time period was specified.
  • The search identified 5,506 citations plus 40 hand-searched publications; after removing 354 duplicates and excluding records, 114 citations reporting 69 eHealth projects met inclusion criteria.
  • Projects were categorized by strategic area, thematic area, health focus, geographic location, and evaluation status; geo-coded maps were layered by urbanization and marginalisation using Commission on Revenue Allocation classifications.

Limitations

  • Stated by the paper: some projects may have lacked documentation or externally shared reports because they were profit-driven, aid-funded, or proprietary, and some projects may have been implemented after data collection concluded, so the inventory may not be exhaustive.
  • Evident from the text: reliance on non-peer-reviewed sources, organizational websites, blogs, and personal communication may introduce selection or reporting bias.
  • Evident from the text: because 41 of 69 projects (59%) had no reported evaluation, the review cannot assess effectiveness or cost-effectiveness for most included projects.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1186/s13104-017-2416-0

Cites

39 of 39 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Fig. 1 Search results. Source: authors’ synthesis
Fig. 1 Search results. Source: authors’ synthesisCC BY · PubMed Central
Fig. 2 Distribution of eHealth projects in Kenya by urbanization. Map A consisting of all the eHealth projects under implementation in 47 counties in Kenya. Map shows geographical locations of all eHealth initiatives categorised by strategic area of implementation and national projects. Map background is divided according to percentage of urbanization (see colour bars) and the number of counties in square brackets. Map B (Inset) Nairobi County (capital city) and neighbouring counties. Source: authors’ synthesis. No data permission was required
Fig. 2 Distribution of eHealth projects in Kenya by urbanization. Map A consisting of all the eHealth projects under implementation in 47 counties in Kenya. Map shows geographical locations of all eHealth initiatives categorised by strategic area of implementation and national projects. Map background is divided according to percentage of urbanization (see colour bars) and the number of counties in square brackets. Map B (Inset) Nairobi County (capital city) and neighbouring counties. Source: authors’ synthesis. No data permission was requiredCC BY · PubMed Central
Fig. 3 Distribution of eHealth projects in Kenya by marginalisation. Map A demonstrates eHealth projects in Kenya based on counties and categorised by strategic area of implementation and national projects. Map background is coloured according to county marginalisation as defined by CRA (see colour bars). Map B (Inset) highlights Kisumu, Vihiga, Kakamega, Siaya and neighbouring counties. Source: authors’ synthesis. No data permission was required
Fig. 3 Distribution of eHealth projects in Kenya by marginalisation. Map A demonstrates eHealth projects in Kenya based on counties and categorised by strategic area of implementation and national projects. Map background is coloured according to county marginalisation as defined by CRA (see colour bars). Map B (Inset) highlights Kisumu, Vihiga, Kakamega, Siaya and neighbouring counties. Source: authors’ synthesis. No data permission was requiredCC BY · PubMed Central

Verification

Claims the paper makes

47 Own result · 19 Not checked yet · 16 Own interpretation · 9 No basis given · 6 Own method

Verify all 46 references — free account

Show all 59 claims

  • It may state two separate claims as one. 24
  • Probably not a substantial claim. 18
38 of 38
  • The paper relies on this without support.

    There is a dearth of evidence of eHealth initiatives being implemented in Kenya, specifically a lack of a registry of all projects under implementation and documentation of their characteristics.

    “However, there is dearth of evidence of initiatives being implemented in the country. Specifically, there is lack of a registry of all projects under implementation and documentation of their specific characteristics including contributions to strengthening the Kenyan health system.”
  • The paper relies on this without support.

    A large number of eHealth projects in Kenya were not reported in peer reviewed literature.

    “This however was not sufficient as there were large number of eHealth projects in Kenya that were not reported in peer reviewed literature.”
  • The paper relies on this without support.

    The cost of setting up mobile health systems is considerably low compared to other ICT systems.

    “The cost of setting up mobile health systems is considerably low compared to other ICT systems.”
  • The paper relies on this without support.

    Mobile Health driven initiatives provide easy accessibility to interventions effectively at any setting.

    “Mobile Health driven initiatives provide easy accessibility to interventions effectively at any setting.”
  • The paper relies on this without support.

    In the developing and building up phase, eHealth initiatives are majorly driven by the need to improve access and quality of health care.

    “In this phase, the eHealth initiatives are majorly driven by the need to improve access and quality of health care.”
  • The paper relies on this without support.

    The major pressing health priorities in marginalised regions are maternal and child health challenges and communicable diseases such as malaria, tuberculosis, and HIV/AIDS.

    “The major pressing health priorities in these regions are maternal and child health challenges and communicable diseases such malaria, tuberculosis, and HIV/AIDS.”
  • The paper relies on this without support.

    Health systems are interconnected.

    “Since health systems are interconnected, it is necessary that eHealth projects be able to integrate to the overall health system.”
  • The paper relies on this without support.

    Development agencies focus on their countries' development assistance strategic direction while international non-governmental organisations focus on the most popular diseases in an effort to attract funding.

    “This is because development agencies focuses on their countries’ development assistance strategic direction while international non-governmental organisations would focus on the most popular diseases in an effort to attract funding.”
8 of 8

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Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

6 of 6

Citations

Cites

Show all 40 references

Research works printed but not linked: 4

  1. Talbot D. Kenya’s mobile prescription: local programmers and homegrown business models are helping to realize the vast promise of using phones to improve health care and save lives. Technol Rev (Camb, Mass). 2012;115:52.
  2. Kenya National Bureau of Statistics. Economic survey 2014. Nairobi: Kenya National Bureau of Statistics; 2014.
  3. Hoibak S, Schilperoord M. Android phones for mosquito net surveys. Forced Migr Rev. 2011;1(38):32.
  4. Constitution K. Government Printer. Kenya: Nairobi; 2010.

Cited by

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Items 101–101 of 101

Metadata

Authors
Njoroge, M., Zurovac, D., Ogara, E. A. A., Chuma, J., & Kirigia, D.
Affiliations
  • Kenya Medical Research Institute (KE)
  • Boston University (US)
  • Ministry of Health (KE)
Corresponding author
Njoroge, Martin
Venue
BMC Research Notes
Published
2017-02-10
Volume
10
Issue
1
Pages
90-90
ISSN
1756-0500 (ISSN-L)
OpenAlex
W2586626150
Cited by
100
References
40
Citations by year
2026: 4 · 2025: 9 · 2024: 9 · 2023: 17 · 2022: 10 · 2021: 16 · 2020: 14 · 2019: 10 · 2018: 5 · 2017: 6
FWCI
1.68
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • BMC Research Notes (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • International Development Research Centre (CA) (grant number 106229-011)
  • Wellcome Trust (GB) (092654)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
  • Physical Sciences › Computer Science › Information Systems › ICT in Developing Communities
Keywords
e-health, mobile health, Kenya, health information systems, telemedicine, online learning, HIV/AIDS, maternal and child health, primary care, health equity, health system strengthening, project evaluation
MeSH terms
Acquired Immunodeficiency Syndrome, Community Health Services, Developing Countries, Humans, Kenya, Primary Health Care, Public Health, Randomized Controlled Trials as Topic, Telemedicine, Healthcare Disparities, Health Information Systems

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