E-health in low to middle income countries

Clifford, Gari D.

doi:10.1080/03091902.2016.1256081

Cited by 24 publications

(27 citation statements)

References 21 publications

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“…Additionally, the challenges for implementing m‐health solutions in low resource communities are attributed mainly to the cost of access to mobile devices as well as the cost of an internet connection (Clifford, ; Dobson & Jackson, ). Other barriers to the adoption and use of these health care tools are limited funding and poor infrastructure by government organisations (Akhlaq, McKinstry, Muhammad, & Sheikh, ).…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…Low levels of education and literacy are prominent barriers linked to the adoption and effective use of technologies for self‐management of health in low resource countries (Clifford, ). Van Heerden et al () state that education and training programmes are a necessity as older users are unfamiliar with operating mobile devices and applications, a major barrier directly affecting the uptake and scaling of m‐health applications.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

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Challenges for the adoption of ICT for diabetes self‐management in South Africa

Petersen

Brown

Pather

et al. 2019

E J Info Sys Dev Countries

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The increasing disease burden in developing countries inhibits the provision of quality care to citizens. However, the increased availability of information communication and technology (ICT) tools makes this a viable option for inclusion in primary health care. Even so, barriers are impeding the successful adoption and usage of ICT tools in health care contexts. This research focuses on one such context to identify the challenges and barriers for the adoption of ICT tools for diabetes self‐management in the Western Cape province of South Africa. The extended technology acceptance model (TAM) and four factors (educational, technological, economic, and sociocultural factors) were identified as a basis for investigation. Evidence was gathered from a sample of 131 diabetic patients using semistructured interviews. These factors, together with TAM constructs, explore how patients interact with ICT and their attitudes towards the use of ICT for diabetes self‐management. The results indicate that all four factors form barriers to ICT adoption for diabetes self‐management. These findings provide a basis to inform how future interventions at the primary health care level may be developed to overcome the identified barriers in efforts to integrate ICT tools into diabetic patients' daily self‐management routines.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Section: Theoretical Frameworkmentioning

confidence: 99%

Challenges for the adoption of ICT for diabetes self‐management in South Africa

Petersen

Brown

Pather

et al. 2019

E J Info Sys Dev Countries

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“…This study is, to our knowledge, the first report of supportive mHealth technology for low-literate TBAs with little previous exposure to technology in a challenging rural healthcare delivery context, as well as the first report of referral rates by TBAs in indigenous populations, and it adds to the evidence of community-based intervention packages for improving maternal and perinatal outcomes [25, 26] and of mHealth interventions integrated within existing healthcare systems as potential solutions for addressing maternal health in LMICs [13, 27–29]. For example, in a study conducted in rural Pakistan by Jokhio et al [30], training TBAs to recognize maternal and perinatal complications, alongside efforts made to better integrate them into the formal health system, resulted in increased referral rates to facility-care for emergency obstetrical care.…”

Section: Discussionmentioning

confidence: 99%

mHealth intervention to improve the continuum of maternal and perinatal care in rural Guatemala: a pragmatic, randomized controlled feasibility trial

et al. 2018

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Background/objectiveGuatemala’s indigenous Maya population has one of the highest perinatal and maternal mortality rates in Latin America. In this population most births are delivered at home by traditional birth attendants (TBAs), who have limited support and linkages to public hospitals. The goal of this study was to characterize the detection of maternal and perinatal complications and rates of facility-level referral by TBAs, and to evaluate the impact of a mHealth decision support system on these rates.MethodsA pragmatic one-year feasibility trial of an mHealth decisions support system was conducted in rural Maya communities in collaboration with TBAs. TBAs were individually randomized in an unblinded fashion to either early-access or later-access to the mHealth system. TBAs in the early-access arm used the mHealth system throughout the study. TBAs in the later-access arm provided usual care until crossing over uni-directionally to the mHealth system at the study midpoint. The primary study outcome was the monthly rate of referral to facility-level care, adjusted for birth volume.ResultsForty-four TBAs were randomized, 23 to the early-access arm and 21 to the later-access arm. Outcomes were analyzed for 799 pregnancies (early-access 425, later-access 374). Monthly referral rates to facility-level care were significantly higher among the early-access arm (median 33 referrals per 100 births, IQR 22–58) compared to the later-access arm (median 20 per 100, IQR 0–30) (p = 0.03). At the study midpoint, the later-access arm began using the mHealth platform and its referral rates increased (median 34 referrals per 100 births, IQR 5–50) with no significant difference from the early-access arm (p = 0.58). Rates of complications were similar in both arms, except for hypertensive disorders of pregnancy, which were significantly higher among TBAs in the early-access arm (RR 3.3, 95% CI 1.10–9.86).ConclusionsReferral rates were higher when TBAs had access to the mHealth platform. The introduction of mHealth supportive technologies for TBAs is feasible and can improve detection of complications and timely referral to facility-care within challenging healthcare delivery contexts.Trial registrationClinicaltrials.gov NCT02348840.

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“…Authentic communication (10) Prioritizing scientific evidence 7Aligned goals and expectations 7Aligned goals and expectations (13) Complementary roles (13) Complementary roles (17) Barriers Prioritizing scientific evidence (9) Misaligned goals and expectations (15) Prioritizing business outcomes (8) Prioritizing business outcomes (13) Timeline (10) Timeline (12) expectations, conflicting scientific or business priorities and conflicting timelines as primary barriers. Overall, stakeholders from both academia and industry agreed that cross-sectoral collaborations are essential for the successful implementation of digital health initiatives.…”

Section: Facilitatorsmentioning

confidence: 99%

Academia–industry digital health collaborations: A cross-cultural analysis of barriers and facilitators

et al. 2019

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Background: Development and uptake of digital health technologies benefit from cross-sectoral efforts from academia and industry. Our study aims to identify the barriers and facilitators associated with academia-industry collaborations in digital health in middle-and high-income countries. Methods: Trained personnel conducted semi-structured interviews with 23 stakeholders who were active in industry, academia or both. Stakeholders were based in middle-income countries (including China) and high-income countries (including the United States) as defined by the World Bank. Interviews were conducted in the stakeholder's language of choice (Chinese, n ¼ 12; English, n ¼ 11). Qualitative interview questions elicited perspectives on stakeholders' experience with academia-industry collaboration, challenges faced, and factors that facilitated the process. Interviews were audiotaped, transcribed verbatim, thematically coded by bilingual coders and analyzed using inductive content analysis. Results: Stakeholders in both academia and industry identified complementary roles, authentic communication between partners, and clearly outlined goals or expectations prior to the collaboration as primary facilitators for success. Misaligned goals or expectations, differences in timelines for productivity and difficulties balancing expectations for business outcomes versus generation of scientific evidence were identified as primary barriers. Stakeholders in highincome countries reported inauthentic communication as a significant barrier to collaboration, whereas those in middle-income countries did not. Conclusion: Outlining and communicating openly about goals and expectations for timeline and priorities as well as establishing complementary roles will facilitate fruitful academia-industry collaborations in the future. Best practices for communication styles may be dependent on the cultural setting, and thus should be adopted accordingly.

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E-health in low to middle income countries

Cited by 24 publications

References 21 publications

Challenges for the adoption of ICT for diabetes self‐management in South Africa

Challenges for the adoption of ICT for diabetes self‐management in South Africa

mHealth intervention to improve the continuum of maternal and perinatal care in rural Guatemala: a pragmatic, randomized controlled feasibility trial

Academia–industry digital health collaborations: A cross-cultural analysis of barriers and facilitators

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