Evaluating Telemedicine for Chronic Disease Management in Low- and Middle-Income Countries During Corona Virus Disease 2019 (COVID-19)
1
Faculty of Health, Medicine and Social Care, Anglia Ruskin University, Cambridge CB1 1PT, UK
2
Faculty of Science and Engineering, Anglia Ruskin University, Chelmsford CM1 1SQ, UK
*
Author to whom correspondence should be addressed.
Hospitals 2025, 2(2), 9; https://doi.org/10.3390/hospitals2020009
Submission received: 12 February 2025
/
Revised: 25 March 2025
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Accepted: 8 April 2025
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Published: 23 April 2025
Abstract
Background: The rapid expansion of telemedicine globally, especially during the COVID-19 pandemic, has been critical for maintaining the continuity of chronic care, including in low- and middle-income countries (LMICs). In the context of maintaining health services during major hazards, telemedicine offers a potential solution for reducing the impact of associated disruptions and maintaining the functionality of hospitals. This study aims to evaluate the application of telemedicine for chronic diseases in LMICs during COVID-19, with a focus on its role in enhancing health system resilience during disastrous events. Methods: A systematised review was conducted by searching PubMed, Scopus, Global Health, and Google Scholar for primary literature published between January 2020 and July 2023. English-language articles on chronic disease management were targeted; they were freely accessible and excluded abstracts, conference papers, posters, and grey literature. A multilevel evaluation framework was applied, covering access, cost, patient and health worker experiences, and the effectiveness of telemedicine interventions. Results: After screening one thousand six hundred seventy-eight records, twenty-three studies and two additional snowball-sourced papers from ten countries were included. Findings revealed that while telemedicine enhanced access to care, patient experiences, and effectiveness, cost analysis remains an understudied area. Discrepancies in perspectives were noted between patients and health workers, particularly regarding access and effectiveness. Nevertheless, the majority of studies agree on telemedicine’s positive impact on the accessibility and resilience of health systems during major emergencies, which reduces costs and improves the overall patient experience. However, concerns such as outdated regulations and policies and poor internet connectivity pose a challenge that needs to be addressed. Conclusions: This review highlights the potential of telemedicine in strengthening health system resilience, particularly in LMICs where more work is needed to update regulations and policies and to strengthen infrastructure for more affordable and uninterruptable connectivity. Further research is needed to explore the long-term sustainability of telemedicine in these contexts and to identify strategies for successful implementation across diverse public health challenges.
1. Introduction
Non-communicable diseases, also referred to as chronic diseases, count for approximately 75% of non-COVID-19 deaths in 2021 [1]. Patients with chronic diseases such as cancer, heart disease, and diabetes are a major proportion of the populations in many low- and middle-income countries (LIMCs), and they need ongoing long-term healthcare because the impact of poor or inadequate care can surpass the impact of the pandemic during the COVID-19 outbreak [2]. The continuity of healthcare for these patients is, therefore, a matter of life or death, specifically with death rates increasing from 71% in 2018 to 75% in 2021 [1,3].
The lack of preparedness in health systems for hazards [4] explained the disruption caused by the Coronavirus (COVID-19) pandemic to healthcare services, particularly those related to caring for individuals with chronic illnesses [5]. To address this challenge, there has been a significant increase in the adoption of telehealth services to both curb the spread of COVID-19 and provide support to the continuity of healthcare for the elderly, frail individuals, and those with chronic conditions [6]. Telemedicine has played a crucial role in maintaining healthcare services; it encompasses symptom screening and the provision of online medical and mental health consultations during the pandemic [7]. Additionally, numerous telemedicine platforms were established to ensure the ongoing care of individuals living with non-communicable diseases (NCDs) [8]. These findings suggest that telemedicine is indispensable in complementing conventional healthcare delivery during the COVID-19 lockdown, especially for patients with pre-existing health conditions.
Despite its significant contributions, global telemedicine application among countries and sub-populations is still heterogeneous [9] and is affected mainly by technological, infrastructural, and economical factors [10]. Hence, the majority of research found in published literature on telemedicine- or telehealth-related studies was conducted in high-income countries [11,12,13]. Previous studies have identified several challenges to telehealth applications during the COVID-19 outbreak in LMICs, including disparities in access to broadband internet and technology, financial and economic barriers, and lack of institutional involvement [14]. Thus, it is important to evaluate the performance of telemedicine services in LMICs, especially in the context of chronic care management and public health.
Many published studies reported on the performance of telemedicine in chronic care management, based separately on patient and health worker perspectives. From the patient’s point of view, telehealth utilisation improves various aspects of chronic disease management, including patient self-management [15], clinical outcome [16], and patient satisfaction rate [17]. Additionally, various studies evaluated the impact of telemedicine on health worker experience [18], cost-effectiveness [19], and disparity of healthcare access [20]. An integrated point of view is essential to address the gap between patient and health professional expectations.
There is a scarcity of published literature that comprehensively evaluates telemedicine performance for chronic care management in LMICs during the COVID-19 pandemic. A recent review summarises the extent and acceptance of telemedicine in LMICs during COVID-19, but not specifically on chronic diseases [21]. Another previous study only summarises the role of telehealth during COVID-19 without specifically discussing chronic diseases [22]. Briefly, there is minimum evidence available on how telemedicine helped in managing patients with chronic diseases during COVID-19. Against this background, a critical question has arisen: how has telemedicine supported chronic care management in LMICs during the COVID-19 outbreak? This study aims to evaluate the application of telemedicine for chronic diseases in LMICs during COVID-19, with a focus on its role in enhancing health system resilience in disaster-prone and conflict-affected settings.
2. Methods
The current research presents the results of a systematised review [23]. The referred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist [24] was adopted to ascertain rigour and minimise bias while performing this review.
2.1. Search Strategy
The search took place in 2023 to identify valid full-text papers of any design and any setting dealing with telemedicine evaluation in chronic care in developing countries during the COVID-19 timeframe. Articles from the following databases were searched: PubMed, Global Health, Scopus and Google Scholar using a comprehensive search up to August 2023. The search strategy was developed iteratively using English MeSH and non-MeSH terms to target any available published paper (see Appendix A).
2.2. Eligibility Criteria
To ensure comprehensive coverage, all articles that assessed telemedicine services for chronic care during the COVID-19 pandemic were included, regardless of the level of telemedicine perception and the specific evaluation domain. Studies related to COVID-19 or general diseases during COVID-19 and pre-COVID-19 were excluded. Additionally, the scope of the study was limited to LMICs and excluded those from high-income countries or global analyses. The list of LMICs was defined based on the income levels as classified by the World Bank (https://data.worldbank.org/country accessed on 22 February 2023). Only full-text articles were included, whilst letters, posters, conference papers, abstracts, and non-English articles were excluded. Table 1 summarises the inclusion and exclusion criteria following the Population, Intervention, Comparison, and Outcome Study (PICOS) framework.
2.3. Data Charting Process
Studies were extracted to record data using an Excel spreadsheet, which included the first author, year of publication, country, disease category, study design, aim, and samples of study. The studies that met our predefined inclusion criteria were screened by title/abstract. All studies that fulfilled our inclusion criteria were further analysed if full-text papers were available. Any vagueness during the selection process was resolved after further discussion and investigation.
2.4. Methodological Quality Appraisal
Mixed-method Appraisal Tool (MMAT-2018) version 2018 was used to critically appraise each eligible study [25] due to its ability to provide a range of assessment criteria for qualitative, quantitative descriptive, quantitative non-randomised, and randomised controlled trials, as well as mixed methods. The critical appraisal of each included study is presented in Appendix B.
2.5. Coding, Summarising, and Reporting Results
Results were organised under the following categories based on the health systems analytical/conceptual framework developed by Li et al. [26]: (1) type of telemedicine service; (2) level of perception; (3) domain of evaluation.
3. Results
Initially, 1678 studies were identified from four online databases, including PubMed (303), Scopus (335), Global Health (139), and Google Scholar (901). After removing 137 duplicate references, titles and abstracts of the remaining 1541 studies were screened, and 766 studies were excluded as they did not align with the topic or study outcomes or were not conducted in LMICs. Further full-text screening led to the exclusion of 331 additional studies, either due to irrelevance or inaccessibility. In total, 23 studies met the eligibility criteria for the review. Two additional papers that were found through snowballing from a related review were also added (Figure 1).
3.1. Characteristics of Sources of Evidence
Twenty-five studies were conducted in ten LMICs: India, Iran, Bangladesh, Pakistan, Jordan, Morocco, Micronesia, Ethiopia, Sri Lanka, Nigeria, Uganda, and Zimbabwe. The highest number of studies were from India (n = 9), Iran (n = 3), and Bangladesh (n = 3), followed by Pakistan (n = 2) and Jordan (n = 2), while the rest were from one country study each. Based on the type of chronic disease, 40% of included studies reported the performance of telemedicine for diabetic patients. Then, as we included all types of research design, we observed that most studies (n = 18) employed a quantitative approach, including observational analytics, observational descriptive, and randomised clinical trials. The remaining studies used qualitative (n = 4) and mixed methods (n = 3). Based on the level of perception, most evidence (n = 18) came from patient/caregiver perception, while only three papers focused on healthcare perception. Four studies were found that investigated both perspectives. Table 2 displays the characteristics of the included studies.
3.2. Synthesis of Results
Based on the literature in this systematised review, we found that various telemedicine platforms were utilised to maintain the delivery of medical service for patients with chronic disease in LMICs during the COVID-19 pandemic. These telemedicine services assisted clinicians or health workers in conducting disease management at diagnostic and therapeutic stages. Moreover, the studies were classified according to the different points of view (e.g., patient, caregiver, physician, stakeholder) to obtain comprehensive findings. Lastly, findings were analysed based on the domain of evaluation as recommended by National Quality Forum (NQF) frameworks to capture a bigger picture of how the telemedicine performance in LMICs in delivering chronic care during the COVID-19 pandemic. The categorisation of eligible studies based on disease type, level of perception, and domain of evaluation is depicted in Figure 2.
3.3. Type of Telemedicine Platform and Level of Clinical Practice Assisted by Telemedicine Services
The application of each telemedicine platform with regard to the area of clinical practices was categorised to obtain insight pertaining to the usability of each telehealth platform. Findings showed that simple phone calls were the most used telemedicine platform for chronic care in LMICs [39,40], while hospital-based telemedicine system and mobile-based apps were the least applied [27,33,46]. Abegaz [47] mentioned that telemedicine is mainly used for appointments, drug prescriptions and least for reassurance, while Atreya [29] stated that telemedicine via phone greatly helped to monitor patients’ mental health, especially in cancer palliative care.
Based on their usability, cloud-based and mobile-based telehealth services cover all clinical practices as both platforms assist the process of screening, health consultation, drug prescription, monitoring, and self-education [33,46]. A study focused on developing mobile- and cloud-based apps for lifestyle modification found that this approach is time-consuming and expensive because it needs adjustment on the features and usability [37]. A qualitative-based study also emphasises the importance of developing integrated telemedicine services that align with the national data collection system, which could help the government tackle national health issues [50]. The type of telemedicine platforms and their coverage in clinical practices are shown in Table 3.
3.4. Domain of Telemedicine Evaluations and Level of Perspective
Evaluation of telemedicine was performed based on the categorisation by the National Quality Forum (NQF) [26]. This approach enables us to evaluate the telehealth implementation systematically and comprehensively in LMICs. Briefly, this framework contains several domains of evaluation, namely access to care, cost, experience, and effectiveness. The details of key findings extracted from each published literature based on these evaluation domains are displayed in Table 4.
3.4.1. Access to Care
Access, defined as the timely receipt of suitable healthcare, is delineated in line with NQF guidelines, encompassing five subdomains: affordability, availability, accessibility, accommodation, and acceptability. From the perspectives of patients and caregivers, a substantial portion of studies has focused on assessing attitudes towards telehealth services and identifying potential influencing factors [35,39,40]. Utilizing structured surveys for quantitative analysis, it was revealed that individuals with chronic ailments generally hold a favourable view of telehealth services [35,39,45], although there are exceptions [40]. It is noteworthy that patients’ perceptions of telemedicine are influenced by demographic characteristics as well as the design and implementation of telehealth initiatives [39,40]. For example, in the context of aged diabetic patients, language and IT literacy could be significant barriers to adopting telehealth [40]. Moreover, to gather more opinions on the design of telehealth services, the qualitative-based study found that telemedicine services should be accessible during a 24/7 period (e.g., to curated data of health status and communication to care team) and allow peer-to-peer sharing [50].
Based on health worker’s perspective, the acceptability of telehealth adoption in their institution varies [42,43]. Perceived barriers that hinder telehealth applications are related to a lack of skill, low IT literacy, and an unsupported environment (lack of infrastructure and IT staff) [42,43]. Furthermore, qualitative analysis of health worker’s expectations towards the ideal design of telehealth mentioned some critical aspects that need serious consideration, such as accurate clinical data collection that enables immediate clinical decisions while preserving patient confidentiality [50]. Beyond clinical practice, health policymakers expect the telehealth system to be implemented accordingly with national data collection, which eventually could direct the stakeholders to solve health issues [50].
3.4.2. Cost
Findings established that telehealth expenses involve patient costs such as internet charges and the purchase of necessary devices, impacting the timing and methods of patient engagement. Potential cost reductions arise from decreased spending on travel, fewer instances of missed workdays, and shorter wait times. Norouzi et al. [36] and Shaikh et al. [43] reported the advantage of telehealth services based on the reduction in travel expenditure, while Saifan et al. [45] stated that patients with cardiovascular diseases were happy to access telehealth services at affordable prices. On the healthcare system’s side, telehealth introduces costs related to training, personnel salaries, equipment acquisition, and telecommunication infrastructure, but it can also generate cost savings through shorter consultations, reduced hospital admissions, lowered readmission rates, diminished emergency department visits, and a decreased reliance on extensive laboratory testing.
3.4.3. Experience
Majority of studies reported that patients with chronic diseases were satisfied with telehealth services as measured by validated questionnaire [27,29,32,33,34,36,43,45,46,47,49]. Further analysis revealed that the higher satisfaction rate was associated with standardised telehealth services [33], friendly staff [29,45], family support, access to nearby laboratories and pharmacies [47], and time-efficient [36]. However, consistent with previous findings, one study found that 56% of elderly diabetic patients were not satisfied with telehealth services because they experienced difficulty in using the platforms and buying the prescribed medications [40]. This finding emphasised the importance of special treatment for elderly patients, particularly the initial assessment of any potential barriers (e.g., language, physical, IT literacy), usability of the platform, and availability of family support during the session.
A study that compares nurse-led vs. physician-led teleconsultation for managing patients with CVDs was also found. Interestingly, they found that the satisfaction rates between those two groups were comparable [31], suggesting that standardised telehealth care could be designed appropriately to share the workload among health professionals. Moreover, a qualitative-based study found that perspicuity and attractiveness of features are essential factors in designing mobile-based lifestyle modification apps [37].
Lastly, only one study focused on investigating the experience of health professionals during telehealth implementation. In accordance with previous findings, Alam and colleagues showed that health professionals tend to be cautious in adopting telemedicine. Special considerations on regulation (e.g., potential malpractice, validity of tools), confidentiality, and limitation of practice (e.g., missed diagnosis due to lack of vitals and anthropometric measurements or time constraints) should be considered before adopting information technology into clinical duties [42].
3.4.4. Effectiveness
According to the NQF framework, the domain effectiveness is classified as system, clinical, operational, and technical effectiveness. In-depth analysis showed that clinical effectiveness is the most studied area based on the patient’s perspective, while the health professional’s perspective investigated broader areas of effectiveness (e.g., technical, system). From the patient’s point of view, most studies analysed the clinical effectiveness of diabetes management by measuring the HbA1c level [27,32,38]. Anjana and colleagues reported that HbA1c levels were improved in patients who utilise online support for diabetes management during lockdown [27]. Moreover, diabetic patients also used telehealth services to report any acute complications (e.g., hypoglycemia, hyperglycemia or DKA) during the Ramadan fasting period [46] or on insulin treatment [32]. Specifically, the case series demonstrated the efficacy of videoconference-based tele-podiatry in monitoring diabetic patients with diabetic foot [30]. Interestingly, telemedicine service could improve medication adherence in patients with chronic diseases, which was comparable with face-to-face visits [36]. These findings indicate that telemedicine service is vital to ensure continuity of care, thus improving the clinical outcome in patients with chronic diseases.
Based on the health professional’s perspective, the effectiveness of telemedicine varied depending on the clinical context, although the majority of studies reported a positive impact. For example, virtual counselling intervention improved medication adherence in patients with chronic diseases [28]. Furthermore, telemedicine was reported to strengthen self-care management in hypertensive patients [51] and effectively assisted insulin dosage in T1DM patients [41]. However, a study found that telemedicine usage negatively affected physician’s performance and patient-doctor relationship in the management of chronic gastro-enterology diseases [43], suggesting that disease context alters the physician’s perspective. Lastly, a qualitative-based study found that the design of videoconference for monitoring patients with failing hearts should consider the structure and design of the telemedicine program, factors affecting the program, and the impact of effectiveness. This proposed design is aimed at creating a telemedicine service that is technically or systematically efficient [44].
4. Discussion
The COVID-19 pandemic has disrupted access to preventive and treatment services for NCDs. In this study, evidence on assessing telehealth services for chronic care management across LMICs to mitigate disruptions during this period was identified and synthesised. Twenty-five peer-reviewed journal articles were analysed to provide an analytical overview of the telemedicine evaluation based on the domain recommended by NQF: (1) access to care; (2) experience; (3) cost; (4) effectiveness.
Based on domain access to care, most studies on patient and caregiver perspectives demonstrated a positive attitude towards telehealth services, with some variations related to demographic factors and telehealth design. On the other hand, health workers’ views on telehealth adoption varied, with barriers including skill and IT literacy, while expectations for an ideal telehealth system included accurate clinical data collection and alignment with national data collection for health policymaking. Indeed, several factors should be considered when implementing telehealth services, based on the patient’s and health worker’s sides. A previous study reported that older adults encounter barriers to telemedicine, including technology difficulties and reluctance for video visits [52]. Furthermore, the widespread adoption of telemedicine faces obstacles like digital literacy, cost implications, reimbursement complexities, and legal concerns [53]. According to the health professional’s point of view, access and features of telemedicine platforms should ensure privacy concerns or confidentiality, the accuracy of clinical data, as well as data security, which allows for an accurate diagnosis with superior accessibility and innovativeness [20]. By designing telehealth services that accommodate those factors, trust from both patients and health workers could be achieved as it is a key factor in implementing sustainable telemedicine services [54,55,56].
One critical finding is the scarcity of studies focusing on cost analysis compared to other domains, revealing a gap in the existing literature. We only found three studies that reported cost analysis, but it was not the focus of the research. Accordingly, the previous literature review showed that the number of studies focused on investigating the cost-effectiveness of telehealth services in LMICs is very limited [26]. Existing evidence shows that telehealth services are cost-effective because they reduce acute admissions and hospital stays [57] and improve patients’ awareness about chronic disease management, thus preventing cost expenditure related to its complication [56]. In low-resource settings of LMICs, telemedicine offers substantial economic benefits and the potential to enhance chronic disease outcomes by reducing socioeconomic barriers and enabling early intervention [58]. Moreover, a combination of artificial intelligence (AI) and telemedicine for screening multiple eye diseases is highly cost-effective in both rural and urban areas in China, promoting equity in eye health [59]. However, previous reports demonstrated that telemedicine’s incorporation into type 2 diabetes management led to a modest reduction in HbA1c levels, but cost-effectiveness remains uncertain, warranting further exploration, especially in hard-to-reach populations [2]. These insights underscore the importance of our research in shedding light on the effectiveness of telehealth services in LMICs during a healthcare crisis and highlight the need for further exploration, especially in the underrepresented areas of cost analysis.
Most of the studies indicate that patients with chronic diseases generally expressed satisfaction with telehealth services, with higher satisfaction associated with standardised services, friendly staff, family support, access to nearby healthcare facilities, and time efficiency. Additionally, findings suggest that elderly patients may face unique challenges with telehealth and require special attention to address barriers such as technology literacy and medication access [60]. An integrated systematic review found several factors associated with telehealth and patient satisfaction, including improved outcomes, preferred modality, ease of use, low cost, improved communication, and decreased travel time, accounting for 61% of mentions [61]. High patient and healthcare provider satisfaction with telehealth during the COVID-19 pandemic was observed, contributing to healthcare continuity and preventing the spread of SARS-CoV-2 [62,63]. In summary, patient satisfaction was generally high in telemedicine, with no significant difference from face-to-face care [64]. These data give optimism towards integrated telemedicine service on top of conventional medical visits to improve chronic care management, especially in LMICs.
In telemedicine studies, clinical effectiveness has been a key focus, showing positive patient outcomes such as improved HbA1c levels and medication adherence [65]. These findings are in accordance with previous literature, which demonstrated that telemedicine reduced hospitalisation and improved health outcomes for heart failure patients [66] and improved management of chronic diseases like diabetes and hypertension [67]. Moreover, in the context of telemonitoring, the benefits include increased disease-specific knowledge, earlier assessment, and shared decision-making, balanced with concerns about reduced interpersonal contact [68]. Conversely, integrated telehealth systems for chronic disease management showed no significant effects on depression, anxiety, fatigue, or self-care despite its positive impact on patient’s quality of life [48,69]. However, some challenges should be considered, such as intrinsic motivation, technological difficulties, hearing impairments, and limitations for physicians [70,71], particularly for elderly patients [72]. In regard to health professionals’ perspectives, we found that clinical effectiveness varies by speciality, emphasising the need for tailored telemedicine solutions [73]. Moreover, the evaluation of domain effectiveness is mainly focused on clinical aspects, but limited studies investigating operational or system effectiveness indicate the requirement for further research in those fields.
4.1. Implications for Policy, Research, and Public Health Practice
The majority of studies telemedicine implementations for chronic care management in low- and middle-income countries (LMICs) during the COVID-19 pandemic concurred on the significant benefits of telemedicine in this context, including improvements in patient compliance and self-awareness, streamlining clinical assessment and follow-up processes, and enhancing healthcare accessibility. These findings serve as a valuable basis not only for addressing healthcare challenges during pandemics but also for establishing telemedicine as a complementary service alongside in-person clinical visits. However, several critical factors must be considered when implementing telemedicine, including the usability of the chosen platform, standardisation of services, and seamless integration with hospital information systems, let alone the need to have secure and safe connectivity.
One noteworthy finding was the innovative use of teleconsultation in managing patients with heart failure. This approach, employing experienced nurses as the first responders before referral to cardiologists, yielded patient satisfaction rates comparable to physician-led consultations. This model could serve as an excellent example of an interprofessional approach to telemedicine services. Additionally, a multilevel qualitative-based study conducted in three countries provided valuable insights into the design of ideal telemedicine services from the perspectives of various stakeholders, including patients, caregivers, health workers, and policymakers. This study can guide practical implementations of telehealth services to accommodate the diverse expectations of all stakeholders involved.
4.2. Limitation of Study
Several limitations in the review are acknowledged. Firstly, the search was confined to just four major academic databases, which might have missed some relevant literature. Secondly, the search was restricted to articles published in the English language, which might have led us to overlook important eligible articles published in other languages. Thirdly, because of limited available studies, multilevel analysis could not be performed on some domains which could have limited data interpretations. Lastly, the search could have been limited by an unintentional poor selection of keywords.
5. Conclusions
Despite limited resources, telemedicine services have been successfully adopted to mitigate the disruption of chronic care in LMICs. Overall, the evaluation revealed that telehealth intervention improved healthcare accessibility, clinical outcomes, and patient experience, and it reduced cost expenditure. Further observations are still required to obtain more solid evidence in some domains and different types of NCDs. For policymakers and healthcare managers, investing in telemedicine services represents a compelling option to enhance chronic care in LMICs. However, the successful implementation of telemedicine hinges on selecting the most suitable platforms and standards of care tailored to the unique nature of the care required and the available resources. In the future, telemedicine will play a pivotal role in addressing healthcare gaps and improving health outcomes in LMICs.
Although the study looked mostly at COVID-19, it may be useful for many LMICs in dealing with other forms of disasters, such as extreme weather events associated with climate change, and natural hazards such as wars and earthquakes, where telemedicine could play a major role in ensuring continuous healthcare service. Further research is needed to explore the long-term sustainability of telemedicine in these contexts and identify strategies for successful implementation across diverse public health challenges.
Author Contributions
Conceptualisation, A.U. and N.A.; methodology, A.U.; validation, N.A.; formal analysis, A.U.; writing—original draft preparation, A.U.; writing—review and editing, N.A. and F.P.; supervision, N.A.; project administration, N.A. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data are contained within the articles.
Conflicts of Interest
The authors declare no conflicts of interest.
Appendix A. Search Keywords
| Search Engine | Keywords | HIT Results |
| Scopus | ALL (COVID-19 OR COVID19 OR Coronavirus OR Novel coronavirus OR 2019-nCoV OR Wuhan coronavirus OR SARS-CoV-2 OR SARS2) AND (Telemedicine OR Tele-medicine OR Telehealth OR Tele-health OR Telecare OR Mobile health OR mHealth OR Electronic health OR eHealth OR teleconsultation OR remote consultation OR virtual appointment OR health application) AND (chronic diseases OR hypertension OR diabetes OR diabetes mellitus OR cardiovascular diseases OR coronary heart diseases) AND (evaluation OR clinical outcome OR care effectiveness OR cost effectiveness OR satisfaction OR experience OR access) | 303 |
| PubMed | (COVID-19[title/abstract] OR COVID19[title/abstract] OR Coronavirus [title/abstract] OR Novel coronavirus [title/abstract] OR 2019-nCoV [title/abstract] OR Wuhan coronavirus [title/abstract] OR SARS-CoV-2[title/abstract] OR SARS2[title/abstract]) AND (Telemedicine [title/abstract] OR Tele-medicine [title/abstract] OR Telehealth [title/abstract] OR Tele-health [title/abstract] OR Telecare [title/abstract] OR Mobile health [title/abstract] OR mHealth [title/abstract] OR Electronic health [title/abstract] OR eHealth [title/abstract] OR teleconsultation [title/abstract] OR remote consultation [title/abstract] OR virtual appointment [title/abstract] OR health application [title/abstract]) AND (chronic diseases [title/abstract] OR hypertension [title/abstract] OR diabetes [title/abstract] OR diabetes mellitus [title/abstract] OR cardiovascular diseases [title/abstract] OR coronary heart diseases [title/abstract]) AND (evaluation [title/abstract] OR clinical outcome [title/abstract] OR care effectiveness [title/abstract] OR cost effectiveness [title/abstract] OR satisfaction [title/abstract] OR experience [title/abstract] OR access [title/abstract]) | 304 |
| Global Health | TI (chronic diseases OR hypertension OR diabetes OR diabetes mellitus OR cardiovascular diseases OR coronary heart diseases) AND TX (COVID-19 OR COVID19 OR Coronavirus OR Novel coronavirus OR 2019-nCoV OR Wuhan coronavirus OR SARS-CoV-2 OR SARS2) AND TI (Telemedicine OR Tele-medicine OR Telehealth OR Tele-health OR Telecare OR Mobile health OR mHealth OR Electronic health OR eHealth OR teleconsultation OR remote consultation OR virtual appointment OR health application) AND TX (evaluation OR clinical outcome OR care effectiveness OR cost effectiveness OR satisfaction OR experience OR access) | 139 |
| Google Scholar | telemedicine “chronic diseases” “developing countries” -prenatal -postnatal -malignancy -surgery -mental | 901 |
Appendix B. Critical Appraisal Checklist Using MMAT List (25 Papers)
Table A1.
[47] (Quantitative descriptive).
Table A1.
[47] (Quantitative descriptive).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | |||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | |||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
Table A2.
[42] (Quantitative descriptive).
Table A2.
[42] (Quantitative descriptive).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow to address the research questions? | v | convenient sampling | ||
| 1 | Is the sampling strategy relevant to address the research question? | v | |||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | only 63% response rate | ||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
Table A3.
[44] (Mixed methods, Quantitative descriptive, Qualitative).
Table A3.
[44] (Mixed methods, Quantitative descriptive, Qualitative).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is there an adequate rationale for using a mixed methods design to address the research question? | v | |||
| 2 | Are the different components of the study effectively integrated to answer the research question? | v | |||
| 3 | Are the outputs of the integration of qualitative and quantitative components adequately interpreted? | v | |||
| 4 | Are divergences and inconsistencies between quantitative and qualitative results adequately addressed? | v | |||
| 5 | Do the different components of the study adhere to the quality criteria of each tradition of the methods involved? | v |
| No | Questions | Yes | No | Can’t Tell | Comment |
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | |||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | |||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
| No | Questions | Yes | No | Can’t Tell | Comment |
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the qualitative approach appropriate to answer the research question? | v | |||
| 2 | Are the qualitative data collection methods adequate to address the research question? | v | |||
| 3 | Are the findings adequately derived from the data? | v | |||
| 4 | Is the interpretation of results sufficiently substantiated by data? | v | |||
| 5 | Is there coherence between qualitative data sources, collection, analysis and interpretation? | v |
Table A4.
[27] (Quantitative descriptive).
Table A4.
[27] (Quantitative descriptive).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | random sampling (10%) | ||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | response rate 83.7% | ||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
Table A5.
[28] (Quantitative randomised controlled trial).
Table A5.
[28] (Quantitative randomised controlled trial).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is randomisation appropriately performed? | v | sampling strategy is not described | ||
| 2 | Are the groups comparable at baseline? | v | |||
| 3 | Are there complete outcome data? | v | |||
| 4 | Are outcome assessors blinded to the intervention provided? | v | not described | ||
| 5 | Did the participants adhere to the assigned intervention? | v |
Table A6.
[29] (Quantitative descriptive).
Table A6.
[29] (Quantitative descriptive).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | convenient sampling, only 50 out of 7629 patients using teleconsultation | ||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | |||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
Table A7.
[49] (Quantitative descriptive).
Table A7.
[49] (Quantitative descriptive).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | consecutive | ||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | |||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
Table A8.
[38] (Quantitative non-randomised).
Table A8.
[38] (Quantitative non-randomised).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Are the participants representative of the target population? | v | |||
| 2 | Are measurements appropriate regarding both the outcome and intervention (or exposure)? | v | |||
| 3 | Are there complete outcome data? | v | |||
| 4 | Are the confounders accounted for in the design and analysis? | v | |||
| 5 | During the study period, is the intervention administered (or exposure occurred) as intended? | v |
Table A9.
[39] (Quantitative descriptive).
Table A9.
[39] (Quantitative descriptive).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | convenient (face to face) + snowballing (telephone calls) | ||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | |||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
Table A10.
[40] (Mixed methods, Quantitative descriptive, Qualitative).
Table A10.
[40] (Mixed methods, Quantitative descriptive, Qualitative).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is there an adequate rationale for using a mixed methods design to address the research question? | v | |||
| 2 | Are the different components of the study effectively integrated to answer the research question? | v | |||
| 3 | Are the outputs of the integration of qualitative and quantitative components adequately interpreted? | v | |||
| 4 | Are divergences and inconsistencies between quantitative and qualitative results adequately addressed? | v | |||
| 5 | Do the different components of the study adhere to the quality criteria of each tradition of the methods involved? | v |
| No | Questions | Yes | No | Can’t Tell | Comment |
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | |||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | lack data presentation, only description | ||
| 4 | Is the risk of nonresponse bias low? | v | |||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
| No | Questions | Yes | No | Can’t Tell | Comment |
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the qualitative approach appropriate to answer the research question? | v | |||
| 2 | Are the qualitative data collection methods adequate to address the research question? | v | |||
| 3 | Are the findings adequately derived from the data? | v | |||
| 4 | Is the interpretation of results sufficiently substantiated by data? | v | |||
| 5 | Is there coherence between qualitative data sources, collection, analysis and interpretation? | v |
Table A11.
[30] (Qualitative).
Table A11.
[30] (Qualitative).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the qualitative approach appropriate to answer the research question? | v | |||
| 2 | Are the qualitative data collection methods adequate to address the research question? | v | |||
| 3 | Are the findings adequately derived from the data? | v | |||
| 4 | Is the interpretation of results sufficiently substantiated by data? | v | |||
| 5 | Is there coherence between qualitative data sources, collection, analysis and interpretation? | v |
Table A12.
[31] (Quantitative non-randomised).
Table A12.
[31] (Quantitative non-randomised).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Are the participants representative of the target population? | v | |||
| 2 | Are measurements appropriate regarding both the outcome and intervention (or exposure)? | v | |||
| 3 | Are there complete outcome data? | v | |||
| 4 | Are the confounders accounted for in the design and analysis? | v | |||
| 5 | During the study period, is the intervention administered (or exposure occurred) as intended? | v |
Table A13.
[46] (Quantitative non-randomised).
Table A13.
[46] (Quantitative non-randomised).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Are the participants representative of the target population? | v | sampling strategy is not clear | ||
| 2 | Are measurements appropriate regarding both the outcome and intervention (or exposure)? | v | |||
| 3 | Are there complete outcome data? | v | |||
| 4 | Are the confounders accounted for in the design and analysis? | v | |||
| 5 | During the study period, is the intervention administered (or exposure occurred) as intended? | v |
Table A14.
[32] (Quantitative non-randomised).
Table A14.
[32] (Quantitative non-randomised).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Are the participants representative of the target population? | v | sampling strategy is not clear | ||
| 2 | Are measurements appropriate regarding both the outcome and intervention (or exposure)? | v | |||
| 3 | Are there complete outcome data? | v | |||
| 4 | Are the confounders accounted for in the design and analysis? | v | |||
| 5 | During the study period, is the intervention administered (or exposure occurred) as intended? | v |
Table A15.
[33] (Quantitative non-randomised).
Table A15.
[33] (Quantitative non-randomised).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Are the participants representative of the target population? | v | |||
| 2 | Are measurements appropriate regarding both the outcome and intervention (or exposure)? | v | |||
| 3 | Are there complete outcome data? | v | |||
| 4 | Are the confounders accounted for in the design and analysis? | v | |||
| 5 | During the study period, is the intervention administered (or exposure occurred) as intended? | v |
Table A16.
[50] (Qualitative).
Table A16.
[50] (Qualitative).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the qualitative approach appropriate to answer the research question? | v | |||
| 2 | Are the qualitative data collection methods adequate to address the research question? | v | |||
| 3 | Are the findings adequately derived from the data? | v | |||
| 4 | Is the interpretation of results sufficiently substantiated by data? | v | |||
| 5 | Is there coherence between qualitative data sources, collection, analysis and interpretation? | v |
Table A17.
[36] (Quantitative non-randomised).
Table A17.
[36] (Quantitative non-randomised).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Are the participants representative of the target population? | v | |||
| 2 | Are measurements appropriate regarding both the outcome and intervention (or exposure)? | v | |||
| 3 | Are there complete outcome data? | v | |||
| 4 | Are the confounders accounted for in the design and analysis? | v | |||
| 5 | During the study period, is the intervention administered (or exposure occurred) as intended? | v |
Table A18.
[34] (Mixed methods, Quantitative descriptive, Qualitative).
Table A18.
[34] (Mixed methods, Quantitative descriptive, Qualitative).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is there an adequate rationale for using a mixed methods design to address the research question? | v | |||
| 2 | Are the different components of the study effectively integrated to answer the research question? | v | |||
| 3 | Are the outputs of the integration of qualitative and quantitative components adequately interpreted? | v | |||
| 4 | Are divergences and inconsistencies between quantitative and qualitative results adequately addressed? | v | |||
| 5 | Do the different components of the study adhere to the quality criteria of each tradition of the methods involved? | v |
| No | Questions | Yes | No | Can’t Tell | Comment |
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | convenient sampling | ||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | response rate low 55.7% | ||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
| No | Questions | Yes | No | Can’t Tell | Comment |
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the qualitative approach appropriate to answer the research question? | v | |||
| 2 | Are the qualitative data collection methods adequate to address the research question? | v | |||
| 3 | Are the findings adequately derived from the data? | v | |||
| 4 | Is the interpretation of results sufficiently substantiated by data? | v | |||
| 5 | Is there coherence between qualitative data sources, collection, analysis and interpretation? | v |
Table A19.
[45] (Qualitative).
Table A19.
[45] (Qualitative).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the qualitative approach appropriate to answer the research question? | v | |||
| 2 | Are the qualitative data collection methods adequate to address the research question? | v | |||
| 3 | Are the findings adequately derived from the data? | v | |||
| 4 | Is the interpretation of results sufficiently substantiated by data? | v | |||
| 5 | Is there coherence between qualitative data sources, collection, analysis and interpretation? | v |
Table A20.
[37] (Quantitative descriptive).
Table A20.
[37] (Quantitative descriptive).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | |||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | |||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
Table A21.
[43] (Quantitative descriptive).
Table A21.
[43] (Quantitative descriptive).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | convenient sampling | ||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | |||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
Table A22.
[71] (Qualitative).
Table A22.
[71] (Qualitative).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the qualitative approach appropriate to answer the research question? | v | |||
| 2 | Are the qualitative data collection methods adequate to address the research question? | v | |||
| 3 | Are the findings adequately derived from the data? | v | |||
| 4 | Is the interpretation of results sufficiently substantiated by data? | v | |||
| 5 | Is there coherence between qualitative data sources, collection, analysis and interpretation? | v |
Table A23.
[51] (Quantitative randomised controlled trial).
Table A23.
[51] (Quantitative randomised controlled trial).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is randomisation appropriately performed? | v | |||
| 2 | Are the groups comparable at baseline? | v | |||
| 3 | Are there complete outcome data? | v | |||
| 4 | Are outcome assessors blinded to the intervention provided? | v | |||
| 5 | Did the participants adhere to the assigned intervention? | v |
Table A24.
[35] (Quantitative descriptive).
Table A24.
[35] (Quantitative descriptive).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | |||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | |||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
Table A25.
[41] (Quantitative descriptive).
Table A25.
[41] (Quantitative descriptive).
| No | Questions | Yes | No | Can’t Tell | Comment |
|---|---|---|---|---|---|
| S1 | Are there clear research questions? | v | |||
| S2 | Do the collected data allow us to address the research questions? | v | |||
| 1 | Is the sampling strategy relevant to address the research question? | v | |||
| 2 | Is the sample representative of the target population? | v | |||
| 3 | Are the measurements appropriate? | v | |||
| 4 | Is the risk of nonresponse bias low? | v | |||
| 5 | Is the statistical analysis appropriate to answer the research question? | v |
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Figure 1.
Adapted from PRISMA flowchart.
Figure 2.
Characteristics of reported studies.
Table 1.
Implementation criteria using PICOS.
| Criteria | Definition |
|---|---|
| Population | Studies reported on people with NCDs or NCD patients in any healthcare facility (primary care, institute, pharmacy). |
| Intervention | Any telemedicine services in LMICs |
| Comparator | None |
| Outcomes | Results from patients, health professionals, and stakeholders are considered. |
| Study | All primary studies with quantitative, qualitative or mixed method design |
Table 2.
List of eligible studies.
| No | Study (Year) | Country | Aim/Objectives | Study Design/Report | Participants, Age, Samples/Setting | Type of Chronic Disease | Telemedicine Service and Platform |
|---|---|---|---|---|---|---|---|
| 1 | [27] | India | To assess how the prolonged COVID-19 lockdown has influenced the adoption of new technologies and its impact on glycemic control in patients. | Cross-sectional (Descriptive) | The study sample was drawn from a pool of 30,748 individuals who had visited a major tertiary diabetes center in the past year, with 3000 individuals randomly selected for the study, all of whom had type 2 diabetes (T2D). | T2D | Telemedicine system via phone to hospital call centre (telemedicine van to do phlebotomy, teleconsultation with video and audio, tele-prescription) |
| 2 | [28] | India | To evaluate the influence of virtual patient education on medication adherence and to gauge the effects of virtual pharmacist counselling on medication adherence, particularly in geriatric populations. | Interventional | All elderly patients admitted to the hospital with at least one chronic ailment were considered for inclusion, resulting in a total of 401 eligible patients participating in the study. | NCDs | Tele-consultation via mobile phone led by pharmacist |
| 3 | [29] | India | To analyse the changes in hospital-based practices brought about by the COVID-19 pandemic and to understand how patients and caregivers perceive the provision of telehealth services. | Exploratory survey (semi-structured interview) | A semi-structured interview guide was employed to interview 50 cancer patients who attended outpatient department (OPD) consultations between 1 January 2020 and 19 May 2020. | Cancer | Tele-consultation via phone for triaging patient |
| 4 | [30] | India | To share our experiences in managing three diverse cases of diabetic foot, highlighting the practicality of the “triage” concept in real-world scenarios. We will also discuss the advantages and disadvantages of telemedicine or “tele-podiatry” in diabetic foot care. | Case series (qualitative) | The study encompassed three distinct case series involving patients with diabetic foot complications. | Diabetic foot | Tele-podiatry via an online platform for triaging diabetic foot cases |
| 5 | [31] | India | To demonstrate the feasibility of implementing a nurse-led teleconsultation approach for managing cardiovascular disease (CVD) during the COVID-19 pandemic in India and to evaluate its impact on patient satisfaction with treatment. | Experimental study | A total of 12,042 patients who had previously sought care at the DMC hospital in Punjab, either as outpatients (OPD) or inpatients (IPD), between September 2019 and March 2020 were invited to participate in the study. Out of these, 7242 patients had visited the outpatient facility, while 4800 patients had been recently hospitalised. | CVDs | Teleconsultation via mobile phone (real-time audio interaction) for three tier pyramid screening model |
| 6 | [32] | India | To compare the effectiveness of telemedicine consultations for diabetic patients during Ramadan with conventional follow-up methods. | Experimental study | The study included 46 patients diagnosed with type 1 diabetes (DM) who were registered for follow-up at our centre as of 1 February 2020. | T1D | Tele-consultation via WhatsApp and Web-based meeting |
| 7 | [33] | India | To evaluate the practicality, contentment, and efficiency of mobile phone-based video teleconsultations for the management of individuals with epilepsy. | Experimental (descriptive) study | Between June 2020 and October 2020, a total of 1100 individuals with epilepsy (PWEs) were screened, and 336 participants who met the specific inclusion and exclusion criteria were recruited. | Epilepsy | Video and Audio teleconsultation via a custom-made app |
| 8 | [34] | India | To share our insights regarding the effectiveness of using WhatsApp for delivering follow-up care to children with type 1 diabetes. | Mixed methods (qualitative + cross-sectional survey) | During the study period, a total of 578 inquiries were resolved using WhatsApp, primarily related to report reviews, insulin adjustment, and minor health concerns. These inquiries involved 332 participants in two WhatsApp groups, resulting in 183 responses (55.1%). | T1D | Tele-care via WhatsApp Group to answer patient inquiries and self-monitoring blood glucose |
| 9 | [35] | India | To measure patient perceptions and acceptance levels of telemedicine compared to in-person consultations, particularly among those with non-communicable diseases (NCDs). | Cross-sectional study | Out of the seven departments providing care for non-communicable diseases (NCDs) at the study centre, 220 patients with routine appointments were randomly selected. | NCDs | Teleconference via Zoom for routine follow-up |
| 10 | [36] | Iran | To investigate the impact of telephone-based telehealth visits on medication adherence among chronic patients, both before and after implementing a tele-visit program during the COVID-19 pandemic. | Experimental (time-series) | The selection process aimed to reach the estimated sample size of 314 patients, with 183 patients chosen from 17 Shahrivar hospitals and 131 from Farabi hospital. | NCDs | 2 months of tele-visit appointments via mobile phone. |
| 11 | [37] | Iran | To design a self-management mobile app for individuals with type 2 diabetes based on a needs assessment analysis and grounded in theory. | Descriptive study | The study involved fourteen patients and seven healthcare providers, with patients aged between 24 and 53 years, and a majority of them being female (ten out of fourteen, 71%). Healthcare providers ranged in age from 35 to 42 years, with most of them being female (six out of seven, 85%). | T2D | Telemedicine via mobile and cloud-based app |
| 12 | [38] | Iran | To assess the influence of telenursing on the management of self-care behaviours in patients dealing with chronic hypertension. | Randomised clinical trial | The sample population consisted of 82 patients with hypertension. They were initially selected using a two-stage cluster sampling method and then allocated into intervention and control groups using permuted block randomisation, with six patients in each block. | HT | Tele-nursing via phone call |
| 13 | [39] | Bangladesh | To explore the attitudes and views of individuals with chronic illnesses towards telemedicine during the COVID-19 pandemic. | Cross-sectional (Descriptive) | A total of 878 adults who had at least one chronic ailment participated in the study. | NCDs | Telemedicine via phone or videoconferencing |
| 14 | [40] | Bangladesh | To provide deeper insights into the specialised telehealth services in Bangladesh, as viewed by both service providers and elderly service recipients. | Mixed methods (qualitative + cross-sectional survey) | A specific group of 100 elderly individuals with diabetes was purposefully selected for quantitative interviews, and an additional 10 In-depth Interviews (IDIs) and Key Informant Interviews (KIIs) were carried out. | T2D | Tele-consultation via phone call |
| 15 | [41] | Bangladesh | To share our telemedicine encounter with patients having type 1 diabetes who used insulin pumps and observed fasting during Ramadan in 2020 amid the COVID-19 pandemic. | Cross-sectional study | Nine patients who expressed a desire to observe fasting during Ramadan reached out to our diabetes team via phone. | T1D | Telemedicine via phone for education and instruction before fasting in Ramadhan |
| 16 | [42] | Pakistan | To assess the experiences and opinions of medical doctors regarding telemedicine and to identify the perceived obstacles. | Cross-sectional (Descriptive) | The survey involved 240 practising physicians with a minimum clinical experience of six months, achieving a response rate of 63%. | NCDs | Not specified |
| 17 | [43] | Pakistan | To appraise the utility and challenges of telemedicine in the field of gastroenterology, considering both the viewpoints of physicians and patients, to uncover potential drawbacks. | Cross-sectional study | Over a three-month period, from mid-March to mid-June 2020, approximately 280 patients scheduled telemedicine appointments, with an average of 5–7 patients per clinic. Adjusting for population size, the calculated minimum sample size was approximately 150, and data analysis was primarily descriptive. | Chronic Gastro-Entero Disease | Tele-clinic via phone call and videoconference |
| 18 | [44] | Jordan | To achieve a consensus on the design, acceptability, and practicality of videoconferencing for individuals with heart failure in Jordan, with the aim of enhancing healthcare access and clinical outcomes. | Survey studies (mixed methods) | One survey included 32 healthcare professionals well-versed in heart failure clinical practice and telehealth. Delphi 2 enlisted the input of seven individuals from the information technology centre. | HF | Videoconferencing group program |
| 19 | [45] | Jordan | To explore the perspectives and experiences of patients with cardiovascular disease (CVD) and healthcare providers on how telehealth can help manage critical and long-term CVD health problems. | Qualitative study | Individual interviews were conducted with 12 healthcare providers and 12 cardiac patients from Abdali and Prince Hamzah Hospitals in Jordan. | CVD | Tele-consultation via phone call or videoconference |
| 20 | [38] | Morocco | To examine glycaemic control in individuals with type 2 diabetes since the onset of the “COVID-19” pandemic by contrasting their glycaemic and degenerative profiles before, during, and after lockdown measures. | Cross-sectional study (descriptive + analytic) | From mid-March to mid-October 2020, a total of 720 patients with type 2 diabetes received teleconsultation services at the Endocrinology, Diabetology, and Nutrition Department. | T2D | Teleconsultation via HOSIX and phone call/message/pictures/video via WhatsApp |
| 21 | [46] | Morocco | To gauge the efficacy of telemedicine consultations for diabetic patients during the Ramadan period in comparison to traditional follow-up methods | Comparative cross-sectional study | In this research, 61 patients were included. The median age of these patients was 63 years (with a range of 57 to 69 years), and slightly over half (55.7%) of them were male. | T2D | Tele-education and teleconsultation via VisioMedica Maroc© platform |
| 22 | [47] | Ethiopia | To gauge the contentment of caregivers with teleconsultations and identify factors linked to their satisfaction during the COVID-19 crisis at Tikur Anbessa Specialized Hospital in Addis Ababa, Ethiopia. | Cross-sectional (Descriptive) | Initially, there were 1170 caregivers of children who were offered teleconsultation services. After factoring in a 10% nonresponse rate, the final required sample size for the study was determined to be 299. | Chronic Pediatric Disease | Teleconsultation service via mobile phone |
| 23 | [48] | Micronesia | To pinpoint the facilitating factors and obstacles associated with health communication and technology in Pohnpei aimed at addressing the prevention of non-communicable diseases. | Qualitative study | For interviews and group discussions concerning e-health readiness and non-communicable disease (NCD) priorities, 37 local stakeholders were identified using snowball sampling. These discussions were conducted in local settings. | NCDs | Not specified |
| 24 | [49] | Sri Lanka | To evaluate the influence of the COVID-19 lockdown on the behaviour related to health and management of diseases in individuals with diabetes | Cross-sectional (Descriptive) | The study involved 1727 adults diagnosed with diabetes who attended a diabetes clinic in Colombo, Sri Lanka, during the period of June to July 2020. | T1D T2D | Not specified |
| 25 | [50] | Nigeria, Uganda, Zimbabwe | To ascertain the data and information requirements of stakeholders and understand how digital technologies can enhance the accessibility and provision of palliative care for individuals with advanced cancer in Nigeria, Uganda, and Zimbabwe. | Qualitative study | There was a total of 195 individuals who took part in the study, with representation from Nigeria, Uganda, and Zimbabwe. These participants included 62 advanced cancer patients, 48 informal caregivers, 59 healthcare professionals, and 26 policymakers. | Cancer | Not specified |
Table 3.
Telemedicine platforms and their utilisation in clinical setting.
| Telemedicine Platform | Stage of Clinical Practice | Number of Studies | ||||
|---|---|---|---|---|---|---|
| Screening | Consultation | Prescription | Routine Follow-Up | Education for Self-Management | ||
| Hospital-based system | ᵛ | ᵛ | ᵛ | ᵛ | 2 | |
| Videoconferencing | ᵛ | ᵛ | ᵛ | ᵛ | 8 | |
| Phone calls | ᵛ | ᵛ | ᵛ | ᵛ | 10 | |
| WhatsApp message | ᵛ | ᵛ | ᵛ | ᵛ | 4 | |
| Cloud-based/Mobile-based apps | ᵛ | ᵛ | ᵛ | ᵛ | ᵛ | 3 |
v represents the availability of corresponding aspects within the published literature.
Table 4.
Level of perception and domain of evaluation of telemedicine services.
| Domain of Evaluation | Level of Perception | Key Findings/Potential Impact | Study (Year) |
|---|---|---|---|
| Access to care | Patient/caregiver | The majority of patients with chronic disease have a positive attitude towards using telemedicine, especially during COVID-19 confinement. Willingness to use telehealth is significantly associated with age, educational status, income, and occupation. | [39] |
| Barriers to telehealth care in aged diabetic patients: poor counselling, limited allocated time, health education and language, cost of service, lack of family support. | [40] | ||
| Require telemedicine platform that provides 24/7 access to palliative care, which accommodates peer-to-peer sharing and valid curated information about health condition. | [50] | ||
| Telehealth usage improves healthcare accessibility for cardiac patients by delivering streamlined work processes. | [45] | ||
| Willingness to use telemedicine is positively associated with difficulty in making in-person clinical visit. | [35] | ||
| Health professionals | Perceived barriers to telemedicine application: inadequate training, low technological literacy, lack of infrastructure. | [42] | |
| Ideal design of telehealth tools: Accessible platforms, especially in rural areas, facilitate accurate clinical data collection, which can help with immediate clinical decisions. | [50] | ||
| Most physicians are against the use of telemedicine because of limited IT teams and a lack of training | [48] | ||
| Patient’s clinical data could be accessed easily with the telemedicine system but still preserve its confidentiality. | [45] | ||
| Policy maker | Telehealth implementation ideally should be in line with national informatics platforms that help to direct the policy or regulation. | [50] | |
| Health professionals and policy maker | NCDs should be tackled with the inclusion of information technology to spread healthy lifestyle messages, especially for the prevention of diabetes. | [48] | |
| Cost | Patient | Telehealth utilisation reduces the cost of transportation | [36] |
| Cardiac patients could access telemedicine service at affordable prices. | [45] | ||
| Telemedicine reduces travel cost. | [43] | ||
| Experience | Patient/caregiver | In 30.6% of patients who utilised telemedicine, 82% of them were satisfied. | [27] |
| Most patients are satisfied with teleconsultation provided by the palliative care team in terms of conversation, politeness, and helping reduce anxiety. | [29] | ||
| The good satisfaction rate is 83.1% in diabetic patients who use telehealth service. | [17] | ||
| Fifty-six percent of elderly diabetic patients are not satisfied with telehealth services, and it is associated with difficulty in accessing the technology, diagnosis of disease, and purchasing the prescription. | [40] | ||
| Patient treatment satisfaction level is comparable between nurse-led vs. physician-led teleconsultation in managing cardiovascular diseases. | [31] | ||
| Patient satisfaction rate is high in both insulin-treated vs. MSII-treated diabetic patients. | [32] | ||
| Overall satisfaction rate is high (>95%). Further investigation showed that they were satisfied because telemedicine platforms provide enough time and access to healthcare, along with comfort and consistent care. | [33] | ||
| High satisfaction rate because of time efficiency. | [36] | ||
| The satisfaction rate for teleconsultation is 61.5%. The satisfactory rate was associated with the female gender, having family support, and access to nearby laboratories and pharmacies. | [47] | ||
| Most reported queries are insulin titration, reviewing the report, and minor ailments. The usability of the Whatsapp platform is a major contributing factor to a high satisfaction rate. | [34] | ||
| Telemedicine service is convenient and delivered by friendly and qualified staff. | [45] | ||
| Patient’s satisfaction rate is high mostly due to effective communication between doctor and patient. | [43] | ||
| In terms of mobile-based apps that facilitate lifestyle modifications, the clearness of the message and attractiveness of the feature should be considered during the development of the apps. | [37] | ||
| Health professionals | Concern about regulations (malpractice, accreditation) and limitation of practice (missed diagnosis, prescription errors, lack of vital and anthropometric measurements). | [42] | |
| Effectiveness | Patient | Improved HbA1c level in patients using online support for diabetes management during lockdown. | [27] |
| Assist in monitoring HbA1c level, development of complications, and drug dosage adjustments. | [38] | ||
| Tele-podiatry is an effective tool for initial assessment, monitoring, and providing referrals in patients with low-risk diabetic foot. | [30] | ||
| The major episodes of complication in diabetic patients (e.g., hypoglycemia, hyperglycemia or ketoacidosis) and fasting interruption are comparable between Ramadan 2019 (face-to-face visit) vs. Ramadan 2020 (telemedicine approach). | [46] | ||
| Episodes of acute diabetic complications and the level of HbA1c are comparable between insulin-treated vs. MSII-treated diabetic patients. | [32] | ||
| Medication adherence in patients accepting telemedicine services is comparable with in-person clinical visits based on the Morisky Medication Adherence-8 survey. | [36] | ||
| In NCD patients who used telehealth services, mostly to obtain medicines. | [35] | ||
| Health professionals | Propose the ideal design of videoconference-based telemedicine for monitoring patients with heart failure. Delphi one: The videoconference should be concerned about the structure (number of patients, allocated time, topic of discussion during the session), factors affecting the program, and impact of effectiveness. | [44] | |
| Virtual counselling improved medication adherence of geriatric patients at days 30 and 60 following telemedicine intervention compared to the control group. | [28] | ||
| Telemedicine usage negatively impacted the physician’s productivity and patient-doctor relationship. | [43] | ||
| Telenursing has positive impacts on self-care management (choosing healthy nutrition and disease management) in patients with chronic hypertension. | [51] | ||
| Telemedicine effectively assisted the monitoring of complications and adjustment of insulin pump dosage in children with T1DM. | [41] |
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Utami, A.; Achour, N.; Pascale, F. Evaluating Telemedicine for Chronic Disease Management in Low- and Middle-Income Countries During Corona Virus Disease 2019 (COVID-19). Hospitals 2025, 2, 9. https://doi.org/10.3390/hospitals2020009
AMA Style
Utami A, Achour N, Pascale F. Evaluating Telemedicine for Chronic Disease Management in Low- and Middle-Income Countries During Corona Virus Disease 2019 (COVID-19). Hospitals. 2025; 2(2):9. https://doi.org/10.3390/hospitals2020009
Chicago/Turabian StyleUtami, Anisa, Nebil Achour, and Federica Pascale. 2025. "Evaluating Telemedicine for Chronic Disease Management in Low- and Middle-Income Countries During Corona Virus Disease 2019 (COVID-19)" Hospitals 2, no. 2: 9. https://doi.org/10.3390/hospitals2020009
APA StyleUtami, A., Achour, N., & Pascale, F. (2025). Evaluating Telemedicine for Chronic Disease Management in Low- and Middle-Income Countries During Corona Virus Disease 2019 (COVID-19). Hospitals, 2(2), 9. https://doi.org/10.3390/hospitals2020009
