scholarly journals How a Service User Knows the Level of Privacy and to Whom Trust in pHealth Systems?

2021 ◽  
Author(s):  
Pekka Ruotsalainen ◽  
Bernd Blobel
Keyword(s):  
Communication Networks ◽  
Service Provider ◽  
Service User ◽  
Rapid Development ◽  
Real Life ◽  
Personal Health Information ◽  
Personal Health ◽  
Related Information ◽  
Health Related ◽  
Multi Stakeholder

pHealth is a data (personal health information) driven approach that use communication networks and platforms as technical base. Often it’ services take place in distributed multi-stakeholder environment. Typical pHealth services for the user are personalized information and recommendations how to manage specific health problems and how to behave healthy (prevention). The rapid development of micro- and nano-sensor technology and signal processing makes it possible for pHealth service provider to collect wide spectrum of personal health related information from vital signs to emotions and health behaviors. This development raises big privacy and trust challenges especially because in pHealth similarly to eCommerce and Internet shopping it is commonly expected that the user automatically trust in service provider and used information systems. Unfortunately, this is a wrong assumption because in pHealth’s digital environment it almost impossible for the service user to know to whom to trust, and what the actual level of information privacy is. Therefore, the service user needs tools to evaluate privacy and trust of the service provider and information system used. In this paper, the authors propose a solution for privacy and trust as results of their antecedents, and for the use of computational privacy and trust. To answer the question, which antecedents to use, two literature reviews are performed and 27 privacy and 58 trust attributes suitable for pHealth are found. A proposal how to select a subset of antecedents for real life use is also provided.

scholarly journals PILOT PROJECT OF HEALTH TESTING MACHINE.

2020 ◽  
Vol 9 (6) ◽  
pp. 35-38
Keyword(s):  
Testing Machine ◽  
Pilot Project ◽  
Personal Health Information ◽  
Personal Health ◽  
High Definition ◽  
Web Browser ◽  
Related Information ◽  
Automated Teller Machine ◽  
Health Related ◽  
Preventive Health Screening

Like an automated teller machine (ATM) in a bank health ATM is a touch screen kiosk hardware designed for managing health related information which allows individuals to access their personal health information through any internet connected web browser. Health ATMs provides quick and convenient preventive health screening they can also connect patients with certified doctors using high definition video conferencing digital medical devices and web/mobile applications. In urban locations these ATMs serves as wellness kiosks as well.

Wearable Health Devices

2016 ◽  
Author(s):  
Michael Snyder
Keyword(s):  
Health Information ◽  
Personal Health Information ◽  
Personal Health ◽  
Health Related ◽  
Doctor's Office

What other types of personal health information can be readily collected? Most health-related measurements are administered in or through a doctor’s office and are typically taken when we are sick; the measurements that are taken when we are healthy are infrequent, and we often...

Privacy Exposure Measure: A Privacy-Preserving Technique for Health-Related Web Search

2019 ◽  
Vol 9 (6) ◽  
pp. 1196-1204 ◽  
Author(s):  
Rafiullah Khan ◽  
Muhammad Arshad Islam ◽  
Mohib Ullah ◽  
Muhammad Aleem ◽  
Muhammad Azhar Iqbal
Keyword(s):  
Health Information ◽  
Private Information ◽  
Web Search ◽  
User Behavior ◽  
Privacy Preserving ◽  
Personal Health Information ◽  
Personal Health ◽  
Sensitive Information ◽  
Private Information Retrieval ◽  
Health Related

The increasing use of web search engines (WSEs) for searching healthcare information has resulted in a growing number of users posting personal health information online. A recent survey demonstrates that over 80% of patients use WSE to seek health information. However, WSE stores these user's queries to analyze user behavior, result ranking, personalization, targeted advertisements, and other activities. Since health-related queries contain privacy-sensitive information that may infringe user's privacy. Therefore, privacy-preserving web search techniques such as anonymizing networks, profile obfuscation, private information retrieval (PIR) protocols etc. are used to ensure the user's privacy. In this paper, we propose Privacy Exposure Measure (PEM), a technique that facilitates user to control his/her privacy exposure while using the PIR protocols. PEM assesses the similarity between the user's profile and query before posting to WSE and assists the user in avoiding privacy exposure. The experiments demonstrate 37.2% difference between users' profile created through PEM-powered-PIR protocol and other usual users' profile. Moreover, PEM offers more privacy to the user even in case of machine-learning attack.

scholarly journals H-Rec2: A Novel Mobile-Social System for Automatic Health Recognition and Recommendation

2017 ◽  
Author(s):  
Huan Li ◽  
Kejie Lu ◽  
Qi Zhang
Keyword(s):  
Physical Activity ◽  
Health Status ◽  
Food Intake ◽  
Online Social Networks ◽  
Integrated Approach ◽  
Relevant Information ◽  
Overweight And Obesity ◽  
Personal Health Information ◽  
Related Information ◽  
Health Related

Over the past decades, overweight and obesity has become a global epidemic and the leading threat for death. To prevent the serious risk, an overweight or obese individual must apply a long-term weight-management strategy to control food intake and physical activities, which is however, not easy. Recently, with the advances of information technology, more and more people can use wearable devices and smartphones to obtain physical activity information, while they can also access various health-related information from Internet online social networks (OSNs). Nevertheless, there is a lack of an integrated approach that can combine these two methods in an efficient way. In this paper, we address this issue and propose a novel mobile-social framework for health recognition and recommendation, namely, H-Rec2. The main ideas of H-Rec2 include (1) to recognize the individual's health status using smartphone as a general platform, and (2) to recommend physical activity and food intake based on personal health information, life science principles, and health-related information obtained from OSNs. To demonstrate the potentials of the H-Rec2 framework, we develop a prototype that consists of four important components: (1) an activity recognition module that senses physical activity using accelerometer, (2) a health status modeling module that applies a novel algorithm to generate personalized health status index, (3) a restaurant information collection module that collects relevant information from OSN, and (4) a restaurant recommendation module that provides personalized and context-aware recommendation. To evaluate the prototype, we conduct both objective and subjective experiments, which confirm the performance and effectiveness of the proposed system.

scholarly journals Type ll Diabetic Patients’ Attitudes Toward Influenza and Covid-19 Vaccination

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A351-A352
Author(s):  
Reisa Gilfix ◽  
Jack Elstein ◽  
Eleanor Elstein
Keyword(s):  
Real Life ◽  
Primary Source ◽  
Diabetic Patients ◽  
Potential Health ◽  
Mainstream Media ◽  
Telephone Interviews ◽  
Related Information ◽  
Health Related ◽  
The Media ◽  
History Of Use

Abstract Influenza vaccination (fluv) is free and easily accessible to diabetics in Quebec. The importance of vaccination (v) during the Covid19 (CV19) pandemic has been widely discussed in the media. To ascertain the receptiveness of type 2 diabetics (T2D) to fluv during the CV19 pandemic and their acceptance of an eventual CV19 vaccine (CVv) we carried out telephone interviews with 34 unselected T2D pts in Montreal, Quebec post the 1st wave of CV19 in that region. Pts were asked if they planned taking the fluv and/or an eventual CVv, reasons for reticence to v, and attitudes toward and compliance with public health (PH) directives. They were also asked their primary source of health related information. Recent HbA1c and insulin use were recorded. Thirty four T2Ds were surveyed, 22 M 50–87 yrs (mean 69.2) and 12 F 49–84 yrs (mean 68.8). Eleven M and 5 F were on insulin. HbA1c ranged from 5.9–13.0 (mean 7.3). None of the pts had recently discussed v with a healthcare provider (HCP). One pt received his health related information from Facebook, the others from mainstream media. None had contraindications to v. None had been diagnosed with CV19. Past influenza history was unknown. Forty one percent (14/34) of pts, 11 M 50–86 yrs (mean 66.0) and 3 F 49–66 yrs (mean 59.0) did not plan to take the fluv. They explained their decisions as never having taken fluv (12 pts) or having been ill despite having taken it (2 pts). Neither accessibility nor cost were issues. Two F, 62 and 66 yrs, who refused fluv also refused CVv. Six M aged 60–86 yrs (mean 70.5) and 1 F aged 73 yrs were planning to wait to access real life safety (6pts) or efficacy (1pt) data before accepting CVv. All pts claimed to be following PH guidelines including social distancing, hand washing, and mask recommendations; 91.2% (31/34) fully agreed with PH policies, 2 were in moderate agreement and 1 thought PH policy was not strict enough. Of the latter 3 pts none planned on taking the fluv. One planned taking the CVv, 1 planned not to, and the 3rd planned to wait before deciding. Despite a long history of use, recommendations by experts, and free and easy accessibility, T2D pts questioned after the 1st wave of CV19 are not convinced of the fluv’s importance. Despite high case numbers and being themselves at high risk, not all T2Ds are willing to unequivocally accept a potential Health Canada sanctioned CVv. This study underlines the important work HCPs have ahead in educating and reassuring pts with regard to vaccination.

scholarly journals Consumer health information and question answering: helping consumers find answers to their health-related information needs

2019 ◽  
Vol 27 (2) ◽  
pp. 194-201 ◽  
Author(s):  
Dina Demner-Fushman ◽  
Yassine Mrabet ◽  
Asma Ben Abacha
Keyword(s):  
Information Retrieval ◽  
Deep Learning ◽  
Real Life ◽  
Mean Average Precision ◽  
Consumer Health ◽  
National Library ◽  
Average Precision ◽  
Related Information ◽  
Health Related ◽  
Reciprocal Rank

Abstract Objective Consumers increasingly turn to the internet in search of health-related information; and they want their questions answered with short and precise passages, rather than needing to analyze lists of relevant documents returned by search engines and reading each document to find an answer. We aim to answer consumer health questions with information from reliable sources. Materials and Methods We combine knowledge-based, traditional machine and deep learning approaches to understand consumers’ questions and select the best answers from consumer-oriented sources. We evaluate the end-to-end system and its components on simple questions generated in a pilot development of MedlinePlus Alexa skill, as well as the short and long real-life questions submitted to the National Library of Medicine by consumers. Results Our system achieves 78.7% mean average precision and 87.9% mean reciprocal rank on simple Alexa questions, and 44.5% mean average precision and 51.6% mean reciprocal rank on real-life questions submitted by National Library of Medicine consumers. Discussion The ensemble of deep learning, domain knowledge, and traditional approaches recognizes question type and focus well in the simple questions, but it leaves room for improvement on the real-life consumers’ questions. Information retrieval approaches alone are sufficient for finding answers to simple Alexa questions. Answering real-life questions, however, benefits from a combination of information retrieval and inference approaches. Conclusion A pilot practical implementation of research needed to help consumers find reliable answers to their health-related questions demonstrates that for most questions the reliable answers exist and can be found automatically with acceptable accuracy.

Coding and Messaging Systems for Women's Health Informatics

2009 ◽  
pp. 38-52
Author(s):  
David Parry
Keyword(s):  
Health Informatics ◽  
Rapid Development ◽  
International Classification Of Diseases ◽  
Computer Data ◽  
Related Information ◽  
Data Store ◽  
Classification Of Diseases ◽  
Systematic Nomenclature ◽  
Health Related

Recording information about symptoms, observations, actions, and outcomes is a key task of health informatics. Standardization of records is vital if data is to be used by different groups, and transferred between organizations. Originally, coding focused on causes of death and other outcomes. Such systems include the international classification of diseases (ICD). However, more recently the need to allow communication between health organizations has encouraged the development of standards such as health level seven (HL7). Further work has focussed on vocabularies such as systematic nomenclature of medical terms (SNOMED), which allow standardised recording of any health-related information. Coded data is necessary to allow computers to assist in decision making and for audit purposes. With the rapid development of computer networks and the Internet, there has been a growing effort to include semantic information with computer data so that the meaning of the data can be bound to the data store. The chapter discusses these standards and the areas that are undergoing rapid development.

Exploratory study of personal health information management using health literacy model

2018 ◽  
Vol 70 (1) ◽  
pp. 104-122 ◽  
Author(s):  
Sujin Kim ◽  
Sue Yeon Syn ◽  
Donghee Sinn
Keyword(s):  
Real Time ◽  
Information Management ◽  
Personal Health Record ◽  
Personal Health Information ◽  
Personal Health ◽  
Content Type ◽  
Future Studies ◽  
Health Related ◽  
User Groups ◽  
Personal Health Information Management

Purpose The purpose of this paper is to empirically test whether individuals’ internal factors (prior knowledge, resources, and capability) and environmental factors (stimuli, limitation) have any influence on the development of personal health information management (PHIM) literacy skills and which constructs are statistically associated with general health-related outcomes. Design/methodology/approach Survey responses were collected from Amazon’s Mechanical Turk (mTurk), a crowdsourcing internet service, in December 2013. A total of 578 responses were analyzed using partial-least squares structural equation modeling technique. Findings The model as a whole exhibited 62.8 percent of variance in health-related outcomes. The findings suggest that prior knowledge has a direct effect on health literacy (HL) skills (H3: β=0.212, p<0.001). The PHIM stimuli (H4: β=0.475, p<0.001) have a direct impact on HL skills, and they have an indirect effect on the comprehension of stimuli (H6: β=0.526, p<0.001) through the mediator of stimuli and the knowledge variable. Research limitations/implications One possible limitation of this study is that the study may include a highly technology literate group, as survey respondents were recruited from the online service mTurk. Practical implications The study poses implications for further research and practice. This research was an exploratory work for further model development so future studies should investigate deeper into real personal health record (PHR) user groups (e.g. patients and caregivers). For example, studies by White and Horvitz (2009a, b) conducted real-time user studies that the authors could apply to the authors’ future PHR studies. Since the findings cannot be generalizable to these specific groups, similar research may be conducted. Using caregiver groups of PHR users in comparison to patient groups could determine the similarities and differences of their PHIM activities and related outcomes for optimal design of self-care management. Social implications Further, it is suggested to conduct large scale, real-time-based studies using a PHR transaction log analysis to achieve conclusiveness and generalizability. Additionally, future studies should address not only diverse real-time user groups, but also various PHR data sources and their presentation issues. Originality/value This study model offers an important perspective on PHIM and its causal pathway for use not only by patient educators and healthcare providers but also information providers, personal health record (PHR) system developers, and PHR users.

Coding and Messaging Systems for Women’s Health Informatics

2011 ◽  
pp. 2192-2205
Author(s):  
David Parry
Keyword(s):  
Health Informatics ◽  
Rapid Development ◽  
International Classification Of Diseases ◽  
Computer Data ◽  
Related Information ◽  
Data Store ◽  
Classification Of Diseases ◽  
Systematic Nomenclature ◽  
Health Related

Recording information about symptoms, observations, actions, and outcomes is a key task of health informatics. Standardization of records is vital if data is to be used by different groups, and transferred between organizations. Originally, coding focused on causes of death and other outcomes. Such systems include the international classification of diseases (ICD). However, more recently the need to allow communication between health organizations has encouraged the development of standards such as health level seven (HL7). Further work has focussed on vocabularies such as systematic nomenclature of medical terms (SNOMED), which allow standardised recording of any health-related information. Coded data is necessary to allow computers to assist in decision making and for audit purposes. With the rapid development of computer networks and the Internet, there has been a growing effort to include semantic information with computer data so that the meaning of the data can be bound to the data store. The chapter discusses these standards and the areas that are undergoing rapid development.

scholarly journals From sense making to decision making when living with cancer

2018 ◽  
Vol 14 (3) ◽  
pp. 268-273
Author(s):  
Elizabeth M. Goering ◽  
Andrea Krause
Keyword(s):  
Decision Making ◽  
Sense Making ◽  
Personal Health ◽  
Shared Decision ◽  
Methodological Framework ◽  
Related Information ◽  
Catastrophic Illness ◽  
Health Related ◽  
Decision Making Processes ◽  
Living With Cancer

The diagnosis of a catastrophic illness, such as cancer, brings with it a whirlwind of decisions to be made. As healthcare systems rely increasingly on shared decision making (SDM), understanding how patients make sense of health-related information and equip themselves to participate as equal partners in health-related decision making is essential. Coordinated management of meaning’s (CMM) LUUUTT (lived, unknown, untold, unheard, told stories, telling stories) model provides a useful conceptual and methodological framework for better understanding how stories are woven together to create meaning and influence decision making. This Research Note illustrates the potential of applying the LUUUTT model to autoethnographic vignettes and personal health narratives to reach a deeper understanding of the sense-making and decision-making processes related to living with cancer.

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