(Preprint)

2018 ◽  
Author(s):  
Ram Dixit ◽  
Sahiti Myneni

BACKGROUND Connected Health technologies are a promising solution for chronic disease management. However, the scope of connected health systems makes it difficult to employ user-centered design in their development, and poorly designed systems can compound the challenges of information management in chronic care. The Digilego Framework addresses this problem with informatics methods that complement quantitative and qualitative methods in system design, development, and architecture. OBJECTIVE To determine the accuracy and validity of the Digilego information architecture of personal health data in meeting cancer survivors’ information needs. METHODS We conducted a card sort study with 9 cancer survivors (patients and caregivers) to analyze correspondence between the Digilego information architecture and cancer survivors’ mental models. We also analyzed participants’ card sort groups qualitatively to understand their conceptual relations. RESULTS We observed significant correlation between the Digilego information architecture and cancer survivors’ mental models of personal health data. Heuristic analysis of groups also indicated informative discordances and the need for patient-centric categories relating health tracking and social support in the information architecture. CONCLUSIONS Our pilot study shows that the Digilego Framework can capture cancer survivors’ information needs accurately; we also recognize the need for larger studies to conclusively validate Digilego information architectures. More broadly, our results highlight the importance of complementing traditional user-centered design methods and innovative informatics methods to create patient-centered connected health systems.

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Jih-Fu Tu ◽  
Chih-yung Chen

We used the modular technique to design a personal health data transmitter (PHDT) that is composed of the following components: (1) the core is an embedded signal chip, (2) three kinds of transmutation modules such as USB, RF, and UART, (3) an I2C interface is used to acquire the users data, and (4) through Internet it links to the cloud server to store the personal-health data. By the experiment, we find that the modular manner is feasible, stable of functional, integral, and accurate, while it is exploited to design the PHDT. For the experiment, we present each module algorithm to find that our system is very helpful to people.


2021 ◽  
Vol 10 (1) ◽  
pp. 72
Author(s):  
Du'a Alzaleq ◽  
Suboh Alkhushayni ◽  
Austin FitzGerald

This paper describes HealthTracker, a mobile health application to record, store, display, and analyze personal health data. This application allows an individual to log several types of data encompassing their personal health. HealthTracker serves as a model for both a recording and a recommending system. Its goal is to serve as a bridge for future personal health systems to build from. A person’s health information is displayed in an easy-to-understand manner but is also practical for medical professionals. Users should find the system useful and effective no matter if they use it simply or extensively. Currently, the system serves as a prototype for determining the practical applications for smart health systems running on mobile platforms.  


10.2196/14537 ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. e14537 ◽  
Author(s):  
Maria Karampela ◽  
Sofia Ouhbi ◽  
Minna Isomursu

Background Connected health has created opportunities for leveraging health data to deliver preventive and personalized health care services. The increasing number of personal devices and advances in measurement technologies contribute to an exponential growth in digital health data. The practices for sharing data across the health ecosystem are evolving as there are more opportunities for using such data to deliver responsive health services. Objective The objective of this study was to explore user attitudes toward sharing personal health data (PHD). The study was executed within the first year after the implementation of the new General Data Protection Regulation (GDPR) legal framework. Methods The authors analyzed the results of an online questionnaire survey to explore the willingness of 8004 people using connected health services across four European countries to share their PHD and the conditions under which they would be willing to do so. Results Our findings indicate that the majority of users are willing to share their personal PHD for scientific research (1811/8004, 22.63%). Age, education level, and occupation of the participants, in addition to the level of digitalization in their country were found to be associated with data sharing attitudes. Conclusions Positive attitudes toward data sharing for scientific research can be perceived as an indication of trust established between users and academia. Nevertheless, the interpretation of data sharing attitudes is a complex process, related to and influenced by various factors.


2019 ◽  
Author(s):  
Maria Karampela ◽  
Sofia Ouhbi ◽  
Minna Isomursu

BACKGROUND Connected health has created opportunities for leveraging health data to deliver preventive and personalized health care services. The increasing number of personal devices and advances in measurement technologies contribute to an exponential growth in digital health data. The practices for sharing data across the health ecosystem are evolving as there are more opportunities for using such data to deliver responsive health services. OBJECTIVE The objective of this study was to explore user attitudes toward sharing personal health data (PHD). The study was executed within the first year after the implementation of the new General Data Protection Regulation (GDPR) legal framework. METHODS The authors analyzed the results of an online questionnaire survey to explore the willingness of 8004 people using connected health services across four European countries to share their PHD and the conditions under which they would be willing to do so. RESULTS Our findings indicate that the majority of users are willing to share their personal PHD for scientific research (1811/8004, 22.63%). Age, education level, and occupation of the participants, in addition to the level of digitalization in their country were found to be associated with data sharing attitudes. CONCLUSIONS Positive attitudes toward data sharing for scientific research can be perceived as an indication of trust established between users and academia. Nevertheless, the interpretation of data sharing attitudes is a complex process, related to and influenced by various factors.


Author(s):  
Annabelle Cumyn ◽  
Roxanne Dault ◽  
Adrien Barton ◽  
Anne-Marie Cloutier ◽  
Jean-François Ethier

A survey was conducted to assess citizens, research ethics committee members, and researchers’ attitude toward information and consent for the secondary use of health data for research within learning health systems (LHSs). Results show that the reuse of health data for research to advance knowledge and improve care is valued by all parties; consent regarding health data reuse for research has fundamental importance particularly to citizens; and all respondents deemed important the existence of a secure website to support the information and consent processes. This survey was part of a larger project that aims at exploring public perspectives on alternate approaches to the current consent models for health data reuse to take into consideration the unique features of LHSs. The revised model will need to ensure that citizens are given the opportunity to be better informed about upcoming research and have their say, when possible, in the use of their data.


Cancer ◽  
2016 ◽  
Vol 122 (13) ◽  
pp. 2101-2109 ◽  
Author(s):  
Catherine Benedict ◽  
Bridgette Thom ◽  
Danielle N. Friedman ◽  
Debbie Diotallevi ◽  
Elaine M. Pottenger ◽  
...  

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Mira W. Vegter ◽  
Hub A. E. Zwart ◽  
Alain J. van Gool

AbstractPrecision Medicine is driven by the idea that the rapidly increasing range of relatively cheap and efficient self-tracking devices make it feasible to collect multiple kinds of phenotypic data. Advocates of N = 1 research emphasize the countless opportunities personal data provide for optimizing individual health. At the same time, using biomarker data for lifestyle interventions has shown to entail complex challenges. In this paper, we argue that researchers in the field of precision medicine need to address the performative dimension of collecting data. We propose the fun-house mirror as a metaphor for the use of personal health data; each health data source yields a particular type of image that can be regarded as a ‘data mirror’ that is by definition specific and skewed. This requires competence on the part of individuals to adequately interpret the images thus provided.


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