Research evidence on strategies enabling integration of electronic health records in the health care systems of low‐ and middle‐income countries: A literature review

Kumar, Manish; Mostafa, Javed

doi:10.1002/hpm.2754

Cited by 24 publications

(25 citation statements)

References 13 publications

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“…Several countries introduced technical guidelines and changes in legislative policies for telepractice only during the COVID-19 pandemic 54 . But supportive mechanisms such as integrated electronic health records are still not widely available at a national level 55 .…”

Section: Discussionmentioning

confidence: 99%

Implementation components and factors that influence the provision of tele-audiology services for children and adults - a mixed-methods approach

Ramkumar

Shankar

2022

Preprint

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Background Tele-audiology has accelerated with the rapid advancement in information and communication technology. There is a significant knowledge gap concerning the use of implementation science and factors influencing tele-audiology as a routine or long-term, sustained effort. This mixed-methods study aimed to identify implementation factors that influence the provision of tele-audiology services. Method We carried out a mixed-methods study comprising a scoping review and semi-structured interviews (SSI). Articles describing tele-audiology were included based on a set of inclusion and exclusion criteria. Results Data was extracted from 32 studies that were mapped to 21 projects in tele-audiology. The broad areas of focus identified in tele-audiology included the provision of hearing screening, diagnostic evaluation, a combination of diagnostic audiological with otorhinolaryngological evaluation, hearing aid fitting and programming, cochlear implant fitting and mapping, aural re/habilitation services and comprehensive audiological services. Provision of diagnostic and therapeutic services were predominantly carried out using synchronous/ real-time telepractice methods. Asynchronous methods were used predominantly for audiometric screening, video-otoscopy and tympanometry. The most commonly used model was the ‘professional-facilitator-patient’ followed by the ‘professional-patient’ model. Barriers to long-term sustainability included insufficient initial financial investment, lack of reimbursement policies, limited internet (speed and bandwidth), and lack of organisational policies and uniform laws. Successful implementation was reported to be aided by having a stable source of funding, a devoted team of professionals and technicians with defined roles and duties, and with methodical planning. Conclusion The scoping review, as well as the interviewees, represented tele-audiology implementation efforts in a wide range of countries that include low-middle income and high-income nations. Successful implementation was reported to be aided by having a stable source of funding, a devoted team of professionals and technicians with defined roles and duties, and with methodical planning. Sustained implementation occurred when the need and usefulness of tele-audiology were accepted by public sector policy-makers. However, a more accurate understanding of sustainability can be obtained by the use of implementation science and frameworks to guide tele-audiology services.

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Section: Discussionmentioning

confidence: 99%

Implementation components and factors that influence the provision of tele-audiology services for children and adults - a mixed-methods approach

Ramkumar

Shankar

2022

Preprint

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“…Most other widely deployed mHealth applications primarily save data to their own servers and have challenges integrating with existing EHR systems. It will be several years before all LMICs have effective interoperability and health information exchange infrastructure [49,50]. In the meantime, a paradigm that advocates for comprehensive mobile extensions to existing EHR systems will help to reduce the widening digital divide that adversely impacts resource-limited settings.…”

Section: Discussionmentioning

confidence: 99%

mUzima Mobile Electronic Health Record (EHR) System: Development and Implementation at Scale

Were¹,

Savai²,

Mokaya³

et al. 2021

J Med Internet Res

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Background The predominant implementation paradigm of electronic health record (EHR) systems in low- and middle-income countries (LMICs) relies on standalone system installations at facilities. This implementation approach exacerbates the digital divide, with facilities in areas with inadequate electrical and network infrastructure often left behind. Mobile health (mHealth) technologies have been implemented to extend the reach of digital health, but these systems largely add to the problem of siloed patient data, with few seamlessly interoperating with the EHR systems that are now scaled nationally in many LMICs. Robust mHealth applications that effectively extend EHR systems are needed to improve access, improve quality of care, and ameliorate the digital divide. Objective We report on the development and scaled implementation of mUzima, an mHealth extension of the most broadly deployed EHR system in LMICs (OpenMRS). Methods The “Guidelines for reporting of health interventions using mobile phones: mobile (mHealth) evidence reporting assessment (mERA)” checklist was employed to report on the mUzima application. The World Health Organization (WHO) Principles for Digital Development framework was used as a secondary reference framework. Details of mUzima’s architecture, core features, functionalities, and its implementation status are provided to highlight elements that can be adapted in other systems. Results mUzima is an open-source, highly configurable Android application with robust features including offline management, deduplication, relationship management, security, cohort management, and error resolution, among many others. mUzima allows providers with lower-end Android smartphones (version 4.4 and above) who work remotely to access historical patient data, collect new data, view media, leverage decision support, conduct store-and-forward teleconsultation, and geolocate clients. The application is supported by an active community of developers and users, with feature priorities vetted by the community. mUzima has been implemented nationally in Kenya, is widely used in Rwanda, and is gaining scale in Uganda and Mozambique. It is disease-agnostic, with current use cases in HIV, cancer, chronic disease, and COVID-19 management, among other conditions. mUzima meets all WHO’s Principles of Digital Development, and its scaled implementation success has led to its recognition as a digital global public good and its listing in the WHO Digital Health Atlas. Conclusions Greater emphasis should be placed on mHealth applications that robustly extend reach of EHR systems within resource-limited settings, as opposed to siloed mHealth applications. This is particularly important given that health information exchange infrastructure is yet to mature in many LMICs. The mUzima application demonstrates how this can be done at scale, as evidenced by its adoption across multiple countries and for numerous care domains.

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“…EHR improvement helps to store and manage clinical data. Integration of EHRs into the health care systems of LMICs is still in the nascent stage [ 34 ]. In addition to releasing relative policies to ensure the implementation of EHRs in the health care system, the improvements should focus on workforce training, system quality and integrity.…”

Section: Recommended Solutionsmentioning

confidence: 99%

Artificial Intelligence-Based Pharmacovigilance in the Setting of Limited Resources

Liang

Sun

et al. 2022

Drug Saf

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With the rapid development of artificial intelligence (AI) technologies, and the large amount of pharmacovigilance-related data stored in an electronic manner, data-driven automatic methods need to be urgently applied to all aspects of pharmacovigilance to assist healthcare professionals. However, the quantity and quality of data directly affect the performance of AI, and there are particular challenges to implementing AI in limited-resource settings. Analyzing challenges and solutions for AI-based pharmacovigilance in resource-limited settings can improve pharmacovigilance frameworks and capabilities in these settings. In this review, we summarize the challenges into four categories: establishing a database for an AI-based pharmacovigilance system, lack of human resources, weak AI technology and insufficient government support. This study also discusses possible solutions and future perspectives on AI-based pharmacovigilance in resource-limited settings.

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Research evidence on strategies enabling integration of electronic health records in the health care systems of low‐ and middle‐income countries: A literature review

Cited by 24 publications

References 13 publications

Implementation components and factors that influence the provision of tele-audiology services for children and adults - a mixed-methods approach

Implementation components and factors that influence the provision of tele-audiology services for children and adults - a mixed-methods approach

mUzima Mobile Electronic Health Record (EHR) System: Development and Implementation at Scale

Artificial Intelligence-Based Pharmacovigilance in the Setting of Limited Resources

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