Case study mobile health

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Case studies. In support of this mission, Novant Health decided to implement an electronic health record EHR system that would create enterprise-wide access to patient records and streamline care. After several years of working to define and standardize what was to become the Novant Health way of providing health care, the organization reengaged Deloitte to expedite its Dimensions EHR program with Epic software as the foundation. They taught us how to fish. Since the initial launch of the Epic EHR solution in October , deployment has increased in velocity and complexity.
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Kilkari, Mobile Academy & Mobile Kunji

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Health Related Mobile App Development | Pairroxz

Objective: To report a methodological approach for the development of a usable mHealth application app. Materials and methods: This work was guided by a 3-level stratified view of health information technology IT usability evaluation framework. We first describe a number of methodologies for operationalizing each level of the framework. Following the description of each methodology, we present a case study which illustrates the use of our preferred methodologies for the development of a mHealth app. At level 1 user-task , we applied a card sorting technique to guide the information architecture of a mobile HIV symptom self-management app, entitled mVIP.
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Mobile Health Essay

T hese days, the world is transforming regarding how we treat our health. Mobile devices, tablets and wearable devices make it possible to have continuous access to personal health information. However, the lack of interoperability and the presence of data silos prevent users and health professionals from getting an integrated view of health and fitness data.
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Never lose your health data, even if you lose your phone. Using all of the features of the Open mHealth platform, Linq is a way for people to collaborate with their doctor on health tracking using the apps and devices they love. Mobility is an open-source activity-tracking app that allows users to own all of their data. It can passively sense data like sedentary state and driving, in addition to tracking the usual types of physical activity data.
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