Privacy Challenges in the Use of eHealth Systems for Public Health Management

Raychaudhuri, Karpurika; Ray, Pradeep

doi:10.4018/jehmc.2010040102

Cited by 19 publications

(11 citation statements)

References 21 publications

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“…One of the main concerns reported by both professionals and users is related to the privacy, ownership, and responsible use of medical information [38,39]. This is one of the major challenges that eHealth needs to address by means of privacy-preserving technologies [40]. Accessibility and difficulties to find reliable sources of medical information are also important concerns in the population, especially among older adults [41].…”

Section: Xsl • Fomentioning

confidence: 99%

Psychiatric Profiles of eHealth Users Evaluated Using Data Mining Techniques: Cohort Study

López-Castromán¹,

Abad‐Tortosa²,

Aguilera³

et al. 2021

JMIR Ment Health

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Background New technologies are changing access to medical records and the relationship between physicians and patients. Professionals can now use e-mental health tools to provide prompt and personalized responses to patients with mental illness. However, there is a lack of knowledge about the digital phenotypes of patients who use e-mental health apps. Objective This study aimed to reveal the profiles of users of a mental health app through machine learning techniques. Methods We applied a nonparametric model, the Sparse Poisson Factorization Model, to discover latent features in the response patterns of 2254 psychiatric outpatients to a short self-assessment on general health. The assessment was completed through a mental health app after the first login. Results The results showed the following four different profiles of patients: (1) all patients had feelings of worthlessness, aggressiveness, and suicidal ideas; (2) one in four reported low energy and difficulties to cope with problems; (3) less than a quarter described depressive symptoms with extremely high scores in suicidal thoughts and aggressiveness; and (4) a small number, possibly with the most severe conditions, reported a combination of all these features. Conclusions User profiles did not overlap with clinician-made diagnoses. Since each profile seems to be associated with a different level of severity, the profiles could be useful for the prediction of behavioral risks among users of e-mental health apps.

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Section: Xsl • Fomentioning

confidence: 99%

Psychiatric Profiles of eHealth Users Evaluated Using Data Mining Techniques: Cohort Study

López-Castromán¹,

Abad‐Tortosa²,

Aguilera³

et al. 2021

JMIR Ment Health

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“…On mHealth apps, several security issues must be considered, such as personal information management, secondary use of personal information, improper use of personal information, and errors with stored personal information. Therefore, cryptographic mechanisms can be seen as a solution to guarantied data confidentiality and protection [34]. …”

Section: Discussionmentioning

confidence: 99%

A Data Encryption Solution for Mobile Health Apps in Cooperation Environments

Silva¹,

Rodrigues²,

Canelo³

et al. 2013

J Med Internet Res

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BackgroundMobile Health (mHealth) proposes health care delivering anytime and anywhere. It aims to answer several emerging problems in health services, including the increasing number of chronic diseases, high costs on national health services, and the need to provide direct access to health services, regardless of time and place. mHealth systems include the use of mobile devices and apps that interact with patients and caretakers. However, mobile devices present several constraints, such as processor, energy, and storage resource limitations. The constant mobility and often-required Internet connectivity also exposes and compromises the privacy and confidentiality of health information.ObjectiveThis paper presents a proposal, construction, performance evaluation, and validation of a data encryption solution for mobile health apps (DE4MHA), considering a novel and early-proposed cooperation strategy. The goal was to present a robust solution based on encryption algorithms that guarantee the best confidentiality, integrity, and authenticity of users health information. In this paper, we presented, explained, evaluated the performance, and discussed the cooperation mechanisms and the proposed encryption solution for mHealth apps.MethodsFirst, we designed and deployed the DE4MHA. Then two studies were performed: (1) study and comparison of symmetric and asymmetric encryption/decryption algorithms in an mHealth app under a cooperation environment, and (2) performance evaluation of the DE4MHA. Its performance was evaluated through a prototype using an mHealth app for obesity prevention and cares, called SapoFit. We then conducted an evaluation study of the mHealth app with cooperation mechanisms and the DE4MHA using real users and a real cooperation scenario. In 5 days, 5 different groups of 7 students selected randomly agreed to use and experiment the SapoFit app using the 7 devices available for trials.ResultsThere were 35 users of SapoFit that participated in this study. The performance evaluation of the app was done using 7 real mobile devices in 5 different days. The results showed that confidentiality and protection of the users’ health information was guaranteed and SapoFit users were able to use the mHealth app with satisfactory quality. Results also showed that the app with the DE4MHA presented nearly the same results as the app without the DE4MHA. The performance evaluation results considered the probability that a request was successfully answered as a function of the number of uncooperative nodes in the network. The service delivery probability decreased with the increase of uncooperative mobile nodes. Using DE4MHA, it was observed that performance presented a slightly worse result. The service average was also slightly worse but practically insignificantly different than with DE4MHA, being considered negligible.ConclusionsThis paper proposed a data encryption solution for mobile health apps, called DE4MHA. The data encryption algorithm DE4MHA with cooperation mechanisms in mobile health allow users to saf...

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“…Computer-supported cooperative work (CSCW) is usually used to share information through broadband and telecommunication networks (e-Mail or instant messaging) [5]. However, CSCW applied to healthcare information systems could enable patients and healthcare professionals to work together and share more efficiently health information even from remote locations [52,12].…”

Section: Introductionmentioning

confidence: 99%

“…A patient or a healthcare professional that manages such information must assure its confidentiality, integrity, and authenticity. Therefore, cryptographic mechanisms can be seen as an excellent solution to guaranty health information privacy and protection [52].…”

Section: Introductionmentioning

confidence: 99%

Towards a cooperative security system for mobile-health applications

Silva

Rodrigues

Canelo

et al. 2018

Electron Commer Res

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Mobile Health (m-Health) system architectures are typically based on mobile and wireless communications, and use mobile devices with data exchange supported by Web Services (WS). Although m-Health systems offer mobility as a potential and precious resource they also present several challenged issues and constraints, such as, battery and storage capacity, broadcast constraints, interferences, disconnections, noises, limited bandwidths, and network delays. Furthermore, constant mobility and often-required Internet connectivity also exposes and compromises the privacy and confidentiality of the m-Health system information. This paper proposes a novel data encryption solution for mobile health systems, considering a novel and early-proposed cooperation strategy. This encryption solution, called data encryption for mobile health applications (DE4MHA), tries to guarantee the best confidentiality, integrity, and authenticity of m-health systems users data. The paper also presents a performance evaluation study comparing the performance an m-Health application with and without the DE4MHA.

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Privacy Challenges in the Use of eHealth Systems for Public Health Management

Cited by 19 publications

References 21 publications

Psychiatric Profiles of eHealth Users Evaluated Using Data Mining Techniques: Cohort Study

Psychiatric Profiles of eHealth Users Evaluated Using Data Mining Techniques: Cohort Study

A Data Encryption Solution for Mobile Health Apps in Cooperation Environments

Towards a cooperative security system for mobile-health applications

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