A mobile health monitoring-and-treatment system based on integration of the SSN sensor ontology and the HL7 FHIR standard

El–Sappagh, Shaker; Ali, Farman; Hendawi, Abdeltawab; Jang, Jun‐Hyeog; Kwak, Kyung Sup

doi:10.1186/s12911-019-0806-z

Cited by 83 publications

(89 citation statements)

References 62 publications

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“…Our review study are partly consistent with other studies carried out in high-income countries (HICs) (38)(39)(40)54) which found the use of mHealth to manage chronic disease conditions like HIV, TB, hypertension and cancer. Similar studies conducted in low-and middle-income countries (LMICs) also agree with the findings of this review study which revealed the use of mHealth improved medication (51,52) which are similar to our findings.…”

Section: Discussionsupporting

confidence: 91%

Mapping Evidence of Mobile Health Technologies for Disease Diagnosis and Treatment Support by Health Workers in Sub-Saharan Africa: A Scoping Review

Osei

Kuupiel

Vezi

et al. 2019

Preprint

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Background: The rapid growth of mobile technology has given rise to the development of mobile health programmes aimed at treating and preventing a wide range of health conditions. However, evidence on the use of mHealth in high disease burdened settings such as SSA is not clear. We systematically mapped evidence on mHealth for disease diagnosis and treatment support by health workers in SSA. Methods: We conducted a scoping review study guided by the Arksey and O’Malley’s framework, Levac et al recommendations, and Joanna Briggs Institute guidelines. We thoroughly searched the following databases: MEDLINE and CINAHL with full-text via EBSCOhost; PubMed; Science Direct and Google Scholar for relevant articles from inception to July 2019. Two independent reviewers screened abstracts and full-text articles using the eligibility criteria as reference. This study employed the mixed methods appraisal tool version 2018 to assess the methodological quality of the included studies. Results: Out of the 572 articles identified , only 10 published articles presented evidence on mHealth for treatment support by health workers in SSA since 2010. No studies reported evidence on mHealth for disease diagnosis by health workers in SSA. Of the 10 studies, four studies were conducted in Kenya; one in South Africa; one in Malawi; one in Zimbabwe; one in Mozambique; one in Nigeria and one in Lesotho. Of the 10 studies: three reported the use of mHealth to manage HIV; two on the management of HIV/TB; two on treatment of malaria; one each on the management of hypertension; cervical cancer; and one was not specific on any disease condition. All the 10 included studies underwent methodological quality appraisal with a scored between 70 and 100%. Conclusions: The study shows that there is limited research on the availability and use of mHealth by health workers for treatment support in SSA. This study also shows there is no literature on the availability and use of mHealth by health workers for disease diagnosis in SSA. We, therefore, recommend primary studies focusing on the use of mHealth by health workers for disease diagnosis in SSA. Keywords: Mobile Health; Disease diagnosis; Treatment support; sub-Saharan Africa

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Section: Discussionsupporting

confidence: 91%

Mapping Evidence of Mobile Health Technologies for Disease Diagnosis and Treatment Support by Health Workers in Sub-Saharan Africa: A Scoping Review

Osei

Kuupiel

Vezi

et al. 2019

Preprint

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“…However, the Strategy does not address interoperability between mHealth devices and eRecords, despite the anticipated expanded use of mHealth [22]. Although limited in their scope and application, four frameworks were found from the literature review that addressed linking of mHealth to eRecords [18][19][20][21].…”

Section: Discussionmentioning

confidence: 99%

“…PaaS also allowed exible access to health services via desktop, laptop or mobile devices, enabling anywhere and anytime access to data [18]. Cloud based mHealth infrastructure supported integration of CDSS capability for remote monitoring and management of patients with chronic diseases [20]. The e ciency of the CDSS solution was enhanced by using FASTO ontology [20].…”

Section: Discussionmentioning

confidence: 99%

Interoperability frameworks linking mHealth applications to electronic record systems

Ndlovu

Mars

Scott

2020

Preprint

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Background: mHealth presents innovative approaches to enhance primary healthcare delivery in developing countries like Botswana. The impact of mHealth solutions can be improved if they are interoperable with eRecord systems such as electronic health records, electronic medical records and patient health records. eHealth interoperability frameworks exist but their availability and utility for linking mHealth solutions to eRecords in developing world settings like Botswana is unknown. The recently adopted eHealth Strategy for Botswana recognises interoperability as an issue and mHealth as a potential solution for some healthcare needs, but does not address linking the two.Aim: This study reviewed published reviews of eHealth interoperability frameworks for linking mHealth solutions with eRecords, and assessed their relevance to informing interoperability efforts with respect to Botswana’s eHealth Strategy.Methods: A structured literature review and analysis of published reviews of eHealth interoperability frameworks was performed to determine if any are relevant to linking mHealth with eRecords. The Botswanan eHealth Strategy was reviewed.Results: Four articles presented and reviewed eHealth interoperability frameworks that support linking of mHealth interventions to eRecords and associated implementation strategies. While the frameworks were developed for specific circumstances and therefore were based upon varying assumptions and perspectives, they entailed aspects that are relevant and could be drawn upon when developing an mHealth interoperability framework for Botswana. Common emerging themes of infrastructure, interoperability standards, data security and usability were identified and discussed; all of which are important in the developing world context such as in Botswana. The Botswana eHealth Strategy recognises interoperability, mHealth, and eRecords as distinct issues, but not linking of mHealth solutions with eRecords.Conclusion: Delivery of healthcare is shifting from hospital-based to patient-centered primary healthcare and community-based settings, using mHealth interventions. The impact of mHealth solutions can be improved if data generated from them are converted into digital information ready for transmission and incorporation into eRecord systems. The Botswana eHealth Strategy stresses the need to have interoperable eRecords, but mHealth solutions must not be left out. Literature insight about mHealth interoperability with eRecords can inform implementation strategies for Botswana and elsewhere.

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“…And thus the public healthcare facilities can derive some key information from the activity records to support management decisions on the derail of the spread of chronic diseases that can cause a pandemic. Researches show that there is an increasing number of patients with chronic health conditions over the years [7]. Therefore, managing chronic diseases has considerably become a global issue and continues to place pressure on patients in particular and the healthcare setting as well as the society in general [8].…”

Section: Introductionmentioning

confidence: 99%

“…Besides, Smyth [4] conducts a comparative study on sensors and real laboratory data and consequentially reveal that it is much easier to predict the health status of patients via sensor data. Also, El-Sappagh el al [7] prove how easier it is to track the fitness of patients using sensor data. Notwithstanding, Or et al [14] propose that most of the modern health information systems have under-explored design technique challenges [5].…”

Section: Introductionmentioning

confidence: 99%

EDDAMAP: efficient data-dependent approach for monitoring asymptomatic patient

Adu-Gyamfi

Zhang

Ansah

2020

BMC Med Inform Decis Mak

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Background A pandemic affects healthcare delivery and consequently leads to socioeconomic complications. During a pandemic, a community where there lives an asymptomatic patient (AP) becomes a potential endemic zone. Assuming we want to monitor the travel and/or activity of an AP in a community where there is a pandemic. Presently, most monitoring algorithms are relatively less efficient to find a suitable solution as they overlook the continuous mobility instances and activities of the AP over time. Conversely, this paper proposes an EDDAMAP as a compelling data-dependent technique and/or algorithm towards efficient continuous monitoring of the travel and/or activity of an AP. Methods In this paper, it is assumed that an AP is infected with a contagious disease in which the EDDAMAP technique exploits a GPS-enabled mobile device by tagging it to the AP along with its travel within a community. The technique further examines the Spatio-temporal trajectory of the AP to infer its spatial time-bounded activity. The technique aims to learn the travels of the AP and correlates them to its activities to derive some classes of point of interests (POIs) in a location. Further, the technique explores the natural occurring POIs via modelling to identify some regular stay places (SP) and present them as endemic zones. The technique adopts concurrent object feature localization and recognition, branch and bound formalism and graph theory to cater for the worst error-guaranteed approximation to obtain a valid and efficient query solution and also experiments with a real-world GeoLife dataset to confirm its performance. Results The EDDAMAP technique proofs a compelling technique towards efficient monitoring of an AP in case of a pandemic. Conclusions The EDDAMAP technique will promote the discovery of endemic zones and hence some public healthcare facilities can rely on it to facilitate the design of patient monitoring system applications to curtail a global pandemic.

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A mobile health monitoring-and-treatment system based on integration of the SSN sensor ontology and the HL7 FHIR standard

Cited by 83 publications

References 62 publications

Mapping Evidence of Mobile Health Technologies for Disease Diagnosis and Treatment Support by Health Workers in Sub-Saharan Africa: A Scoping Review

Mapping Evidence of Mobile Health Technologies for Disease Diagnosis and Treatment Support by Health Workers in Sub-Saharan Africa: A Scoping Review

Interoperability frameworks linking mHealth applications to electronic record systems

EDDAMAP: efficient data-dependent approach for monitoring asymptomatic patient

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