Mobile and ubiquitous architecture for the medical control of chronic diseases through the use of intelligent devices: Using the architecture for patients with diabetes

Villarreal, Vladimir; Fontecha, Jesús; Hervás, Ramón; Bravo, José

doi:10.1016/j.future.2013.12.013

Cited by 36 publications

(22 citation statements)

References 14 publications

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“…Patient portals also allow providers and care teams to deliver personalized patient education for disease management and clinical decision support for providers, which can improve quality of care and patient outcomes [41‐43]. Validated, evidence‐based patient education materials can be hyperlinked directly from a patient's problem list, and provide concise or in‐depth information based on the patient or caregiver's preference.…”

Section: Discussionmentioning

confidence: 99%

It Takes Two to Tango: Engaging Patients and Providers With Portals

Shah

Liebovitz

2017

PM&R

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Patient portals are designed to be tools to more fully engage patients in their health care and help enable them to better manage their own health information. As the U.S. health care system rapidly adopted electronic health records (EHRs) over the past decade, many with linked patient portals, enthusiasm and expectations for this new technology as a means to engage and empower patients grew. Most patient portals have a set of core features designed to facilitate health care transactions, information tracking, and communication with care team members. The evidence supporting the anticipated benefits of patient portals on patient outcomes, however, remains mixed and incomplete. Moreover, a paradox exists in that, despite a high consumer interest in patient portals, widespread adoption remains relatively low. Potential reasons include the need for greater provider endorsement, examination and adaptation of clinical workflows, and the recognition of patient engagement as a reciprocal process.

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Section: Discussionmentioning

confidence: 99%

It Takes Two to Tango: Engaging Patients and Providers With Portals

Shah

Liebovitz

2017

PM&R

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“…Examples of these systems are [7] for detecting cardiovascular illnesses, [8] for alerting on physical conditions or [9] for tracking changes in physiological responses of patients with chronic diseases. Some of these systems also provide educational modules and personal coaching for promoting healthier lifestyles and managing health conditions [10], [11]. Broadly speaking, main drawbacks of most of these solutions refer to misperformance, limited application scope and lack of interoperability with other similar systems.…”

Section: Related Workmentioning

confidence: 99%

Mining Minds: an innovative framework for personalized health and wellness support

Baños¹,

Amin²,

Khan³

et al. 2015

EAI Endorsed Trans Perv Health Tech

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Abstract-The world is witnessing a spectacular shift in the delivery of health and wellness care. The key ingredient of this transformation consists in the use of revolutionary digital technologies to empower people in their self-management as well as to enhance traditional care procedures. While substantial domain-specific contributions have been provided to that end in the recent years, there is a clear lack of platforms that may orchestrate, and intelligently leverage, all the data, information and knowledge generated through these technologies. This work presents Mining Minds, an innovative framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized healthcare and wellness support. Mining Minds embraces some of the currently most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, and stateof-the-art concepts and methods, such as Context-Awareness, Knowledge Bases or Analytics, among others. This paper aims at thoroughly describing the efficient and rational combination and interoperation of these modern technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support.

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“…This system provides continuous monitoring and real time services, collecting the information from healthcare and monitoring devices located in the home environment and connected to mobile devices. Again in this area, in [26] the authors discuss the potential benefits of using m-IoT in noninvasive glucose level sensing and the potential m-IoT-based architecture for diabetes management. In [27] the authors report on Mobile Sensor Data Processing Engine (MOSDEN), a plugin-based IoT middleware for mobile devices, that allows collecting and processing sensor data without programming efforts and integrating plugins allowing MOSDEN to communicate with sensor hardware.…”

Section: Related Workmentioning

confidence: 99%

An IoT-Aware Architecture for Collecting and Managing Data Related to Elderly Behavior

Almeida

Fiore

Mainetti

et al. 2017

Wireless Communications and Mobile Computing

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The world population will be made up of a growing number of elderly people in the near future. Aged people are characterized by some physical and cognitive diseases, like mild cognitive impairment (MCI) and frailty, that, if not timely diagnosed, could turn into more severe diseases, like Alzheimer disease, thus implying high costs for treatments and cares. Information and Communication Technologies (ICTs) enabling the Internet of Things (IoT) can be adopted to create frameworks for monitoring elderly behavior which, alongside normal clinical procedures, can help geriatricians to early detect behavioral changes related to such pathologies and to provide customized interventions. As part of the City4Age project, this work describes a novel approach for collecting and managing data about elderly behavior during their normal activities. The data capturing layer is an unobtrusive and low-cost sensing infrastructure abstracting the heterogeneity of physical devices, while the data management layer easily manages the huge quantity of sensed data, giving them semantic meaning and fostering data shareability. This work provides a functional validation of the proposed architecture and introduces how the data it manages can be used by the whole City4Age platform to early identify risks related to MCI/frailty and promptly intervene.

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Mobile and ubiquitous architecture for the medical control of chronic diseases through the use of intelligent devices: Using the architecture for patients with diabetes

Cited by 36 publications

References 14 publications

It Takes Two to Tango: Engaging Patients and Providers With Portals

It Takes Two to Tango: Engaging Patients and Providers With Portals

Mining Minds: an innovative framework for personalized health and wellness support

An IoT-Aware Architecture for Collecting and Managing Data Related to Elderly Behavior

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