Healthcare support for underserved communities using a mobile social media platform

Miah, Shah Jahan; Hasan, Najmul; Hasan, Rashadul; Gammack, John

doi:10.1016/j.is.2017.01.001

Cited by 42 publications

(28 citation statements)

References 46 publications

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“…That is, the positive external impacts of using an mHealth tool. These findings resonate with previous work demonstrating how perceived improvement in health outcomes could influence stakeholders' decision-making process towards positively appraising an mHealth tool (Aranda-Jan, Mohutsiwa-Dibe, & Loukanova, 2014;Miah, Hasan, Hasan, & Gammack, 2017).…”

Section: Discussionsupporting

confidence: 88%

Understanding the Factors that Influence the Primary Appraisal of mHealth Tools in Developing Countries: An Exploratory Case-Study in Nigeria

Eze

Gleasure

Heavin

2019

AJIS

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Shortages of health workers, infrastructural deficiencies, limited access to medical care are just a few of the many barriers to care in developing countries. The integration of smartphones and mobile devices into healthcare systems has been proposed to address some of the physical barriers to care and service delivery. These mHealth solutions extend the reach of medical care into rural areas of developing countries. However, it is not clear how mHealth solutions designed and tested in one developing region can be positively appraised for use in others. This study frames this problem using a coping theory approach based on an exploratory case-study to understand the factors that influence primary appraisal of smartphone-enabled clinical guidelines (mHealth tool) for accessing, classifying and eliciting treatment recommendation for sick children under the age of five by rural healthcare workers (RHCWs). Findings identified a set of factors which are bound as an emerging explanatory positivity model that influence primary appraisal of an mHealth tool in a new context. These factors are the set of individual and social factors that governments, funding bodies and non-governmental organisations should consider before embarking on the introduction of an mHealth tool in rural communities of developing countries. It is envisaged that by understanding the factors that influence primary appraisal, that is, either as an opportunity or a threat, practitioners and organisations will support positive appraisal and minimise the occurrence of negative ones when introducing mHealth tools. These findings have implications for theory, practice, and future research as explained in the concluding section of this paper.

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Section: Discussionsupporting

confidence: 88%

Understanding the Factors that Influence the Primary Appraisal of mHealth Tools in Developing Countries: An Exploratory Case-Study in Nigeria

Eze

Gleasure

Heavin

2019

AJIS

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“…While Emont (2011), suggested that PCHR would best suit people with low income, findings from this project suggest the opposite. Results from this project are inline more with other studies which suggested "digital divide" to be one of the barriers for adopting PCHR (Archer et al, 2011;Detmer et al, 2008;Kim et al, 2009;Miah et al, 2017;Patel et al, 2011;Roblin et al, 2009;Sciadas, 2002). Individuals with low income usually cannot afford computers or internet at their own homes.…”

Section: Usefulness/advantages and Disadvantagessupporting

confidence: 83%

“…Archer et al (2011;Patel et al, 2011). Kim et al (2009); (Miah, Hasan, Hasan, & Gammack, 2017); 3 Healthcare cultural and workflow issues (Archer et al, 2011;Detmer et al, 2008;Patel et al, 2011;Weitzman et al, 2009).…”

Section: Benefits Of Adopting Pchrsmentioning

confidence: 99%

The Experiences of Three Different User Groups Using Personally Controlled Health Record for Multidisciplinary Care Team

Ghandour

2019

AJIS

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Personally Controlled Health Records (PCHR) are patient-centric tools which allow individuals to own, manage, access and share their health information online from anywhere, at any time. Patient-centric tools have received considerable interest and investment in recent years worldwide. These tools are thought to have the potential to increase individuals’ self-management and involvement in their own health, as well as improve healthcare efficiency and delivery. The aim of this study is to report and analyse the experiences of three different user groups using PCHR for Multidisciplinary Care Team (MDCT) including the advantages, disadvantages, barriers and obstacles, and the current state of PCHR. In order to achieve the aim of this study, sixteen interviews with key informants from three different user groups were conducted in Dunedin, New Zealand. Interviews were transcribed and analysed with thematic analysis. The key findings of this research showed that those who can benefit the most from PCHRs are the least able to use it. It suits those who have basic knowledge about computers and the internet and those who can afford to use them. PCHR is also best suited for individuals who are motivated about their health despite their health condition. However, more research is needed in the future with a larger sample, an easier to use PCHR, different population other than community health workers, patients with different chronic illnesses, and healthy patients. This research can be used as a basis and tested in future research on PCHR adoption.

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“…The approach identified the patient's exercise, food, and emotional habits using mobile devices and sensors. Miah et al [31] designed and evaluated an innovative mobile decision support solution (MDSS) to support the health decisions of rural citizens and the dissemination of information. The solution was developed using a design science approach, allowing general practitioners, based on consultation and information support, to virtually assess patient conditions and provide a diagnosis or treatment.…”

Section: Related Workmentioning

confidence: 99%

PISIoT: A Machine Learning and IoT-Based Smart Health Platform for Overweight and Obesity Control

et al. 2019

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Overweight and obesity are affecting productivity and quality of life worldwide. The Internet of Things (IoT) makes it possible to interconnect, detect, identify, and process data between objects or services to fulfill a common objective. The main advantages of IoT in healthcare are the monitoring, analysis, diagnosis, and control of conditions such as overweight and obesity and the generation of recommendations to prevent them. However, the objects used in the IoT have limited resources, so it has become necessary to consider other alternatives to analyze the data generated from monitoring, analysis, diagnosis, control, and the generation of recommendations, such as machine learning. This work presents PISIoT: a machine learning and IoT-based smart health platform for the prevention, detection, treatment, and control of overweight and obesity, and other associated conditions or health problems. Weka API and the J48 machine learning algorithm were used to identify critical variables and classify patients, while Apache Mahout and RuleML were used to generate medical recommendations. Finally, to validate the PISIoT platform, we present a case study on the prevention of myocardial infarction in elderly patients with obesity by monitoring biomedical variables.

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Healthcare support for underserved communities using a mobile social media platform

Cited by 42 publications

References 46 publications

Understanding the Factors that Influence the Primary Appraisal of mHealth Tools in Developing Countries: An Exploratory Case-Study in Nigeria

Understanding the Factors that Influence the Primary Appraisal of mHealth Tools in Developing Countries: An Exploratory Case-Study in Nigeria

The Experiences of Three Different User Groups Using Personally Controlled Health Record for Multidisciplinary Care Team

PISIoT: A Machine Learning and IoT-Based Smart Health Platform for Overweight and Obesity Control

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