scholarly journals Visualizing Knowledge Evolution Trends and Research Hotspots of Personal Health Data Research: Bibliometric Analysis (Preprint)

2021 ◽  
Author(s):  
Jianxia Gong ◽  
Vikrant Sihag ◽  
Qingxia Kong ◽  
Lindu Zhao
Keyword(s):  
Health Care ◽  
Human Factors ◽  
Computer Science ◽  
Bibliometric Analysis ◽  
Focal Point ◽  
Empirical Studies ◽  
Health Data ◽  
Personal Health ◽  
Knowledge Evolution ◽  
Research Hotspots

BACKGROUND The recent surge in clinical and nonclinical health-related data has been accompanied by a concomitant increase in personal health data (PHD) research across multiple disciplines such as medicine, computer science, and management. There is now a need to synthesize the dynamic knowledge of PHD in various disciplines to spot potential research hotspots. OBJECTIVE The aim of this study was to reveal the knowledge evolutionary trends in PHD and detect potential research hotspots using bibliometric analysis. METHODS We collected 8281 articles published between 2009 and 2018 from the Web of Science database. The knowledge evolution analysis (KEA) framework was used to analyze the evolution of PHD research. The KEA framework is a bibliometric approach that is based on 3 knowledge networks: reference co-citation, keyword co-occurrence, and discipline co-occurrence. RESULTS The findings show that the focus of PHD research has evolved from medicine centric to technology centric to human centric since 2009. The most active PHD knowledge cluster is developing knowledge resources and allocating scarce resources. The field of computer science, especially the topic of artificial intelligence (AI), has been the focal point of recent empirical studies on PHD. Topics related to psychology and human factors (eg, attitude, satisfaction, education) are also receiving more attention. CONCLUSIONS Our analysis shows that PHD research has the potential to provide value-based health care in the future. All stakeholders should be educated about AI technology to promote value generation through PHD. Moreover, technology developers and health care institutions should consider human factors to facilitate the effective adoption of PHD-related technology. These findings indicate opportunities for interdisciplinary cooperation in several PHD research areas: (1) AI applications for PHD; (2) regulatory issues and governance of PHD; (3) education of all stakeholders about AI technology; and (4) value-based health care including “allocative value,” “technology value,” and “personalized value.”

Privacy and Security: Are Your Health Information Systems up to Standard?

1996 ◽  
Vol 26 (4) ◽  
pp. 197-201 ◽  
Author(s):  
Tina Magennis ◽  
Jennifer Mitchell
Keyword(s):  
Health Care ◽  
Information Systems ◽  
Health Information ◽  
Health Information Systems ◽  
Health Data ◽  
Human Behaviour ◽  
Personal Health ◽  
Privacy And Security ◽  
Patient Health ◽  
Privacy And Confidentiality

As electronic patient health information systems become more fully developed and widespread, there are persistent concerns about the privacy and confidentiality of the personal health data being stored and disseminated. Standards Australia has released two Standards which provide useful guidelines for the organisational, technological and human behaviour solutions required to protect privacy and confidentiality in health care organisations. The major requirements of these Standards are outlined and the implications of the Standards for health information managers are discussed.

Managing Privacy and Effectiveness of Patient-Administered Authorization Policies

2012 ◽  
Vol 3 (2) ◽  
pp. 43-62
Author(s):  
Thomas Trojer ◽  
Basel Katt ◽  
Ruth Breu ◽  
Thomas Schabetsberger ◽  
Richard Mair
Keyword(s):  
Health Care ◽  
Information System ◽  
Access Control ◽  
Data Privacy ◽  
Evaluation Criteria ◽  
Control Policy ◽  
Health Data ◽  
Personal Health ◽  
Access Control Policy ◽  
Authorization Policies

A central building block of data privacy is the individual right of information self-determination. Following from that when dealing with shared electronic health records (SEHR), citizens, as the identified individuals of such records, have to be enabled to decide what medical data can be used in which way by medical professionals. In this context individual preferences of privacy have to be reflected by authorization policies to control access to personal health data. There are two potential challenges when enabling patient-controlled access control policy authoring: First, an ordinary citizen neither can be considered a security expert, nor does she or he have the expertise to fully understand typical activities and workflows within the health-care domain. Thus, a citizen is not necessarily aware of implications her or his access control settings have with regards to the protection of personal health data. Both privacy of citizen’s health-data and the overall effectiveness of a health-care information system are at risk if inadequate access control settings are in place. This paper refers to scenarios of a case study previously conducted and shows how privacy and information system effectiveness can be defined and evaluated in the context of SEHR. The paper describes an access control policy analysis method which evaluates a patient-administered access control policy by considering the mentioned evaluation criteria.

scholarly journals Consumers’ Intentions to Adopt Blockchain-Based Personal Health Records and Data Sharing: Focus Group Study (Preprint)

2020 ◽  
Author(s):  
Chang Lu ◽  
Danielle Batista ◽  
Hoda Hamouda ◽  
Victoria Lemieux
Keyword(s):  
Health Care ◽  
Focus Group ◽  
Data Sharing ◽  
Health Data ◽  
Personal Health Records ◽  
Third Party ◽  
Personal Health ◽  
Health Records ◽  
The Third ◽  
The Third Party

BACKGROUND Although researchers are giving increased attention to blockchain-based personal health records (PHRs) and data sharing, the majority of research focuses on technical design. Very little is known about health care consumers’ intentions to adopt the applications. OBJECTIVE This study aims to explore the intentions and concerns of health care consumers regarding the adoption of blockchain-based personal health records and data sharing. METHODS Three focus groups were conducted, in which 26 participants were shown a prototype of a user interface for a self-sovereign blockchain-based PHR system (ie, a system in which the individual owns, has custody of, and controls access to their personal health information) to be used for privacy and secure health data sharing. A microinterlocutor analysis of focus group transcriptions was performed to show a descriptive overview of participant responses. NVivo 12.0 was used to code the categories of the responses. RESULTS Participants did not exhibit a substantial increase in their willingness to become owners of health data and share the data with third parties after the blockchain solution was introduced. Participants were concerned about the risks of losing private keys, the resulting difficulty in accessing care, and the irrevocability of data access on blockchain. They did, however, favor a blockchain-based PHR that incorporates a private key recovery system and offers a health wallet hosted by government or other positively perceived organizations. They were more inclined to share data via blockchain if the third party used the data for collective good and offered participants nonmonetary forms of compensation and if the access could be revoked from the third party. CONCLUSIONS Health care consumers were not strongly inclined to adopt blockchain-based PHRs and health data sharing. However, their intentions may increase when the concerns and recommendations demonstrated in this study are considered in application design.

scholarly journals Consumers’ Intentions to Adopt Blockchain-Based Personal Health Records and Data Sharing: Focus Group Study

10.2196/21995 ◽  
2020 ◽  
Vol 4 (11) ◽  
pp. e21995
Author(s):  
Chang Lu ◽  
Danielle Batista ◽  
Hoda Hamouda ◽  
Victoria Lemieux
Keyword(s):  
Health Care ◽  
Focus Group ◽  
Data Sharing ◽  
Health Data ◽  
Personal Health Records ◽  
Third Party ◽  
Personal Health ◽  
Health Records ◽  
The Third ◽  
The Third Party

Background Although researchers are giving increased attention to blockchain-based personal health records (PHRs) and data sharing, the majority of research focuses on technical design. Very little is known about health care consumers’ intentions to adopt the applications. Objective This study aims to explore the intentions and concerns of health care consumers regarding the adoption of blockchain-based personal health records and data sharing. Methods Three focus groups were conducted, in which 26 participants were shown a prototype of a user interface for a self-sovereign blockchain-based PHR system (ie, a system in which the individual owns, has custody of, and controls access to their personal health information) to be used for privacy and secure health data sharing. A microinterlocutor analysis of focus group transcriptions was performed to show a descriptive overview of participant responses. NVivo 12.0 was used to code the categories of the responses. Results Participants did not exhibit a substantial increase in their willingness to become owners of health data and share the data with third parties after the blockchain solution was introduced. Participants were concerned about the risks of losing private keys, the resulting difficulty in accessing care, and the irrevocability of data access on blockchain. They did, however, favor a blockchain-based PHR that incorporates a private key recovery system and offers a health wallet hosted by government or other positively perceived organizations. They were more inclined to share data via blockchain if the third party used the data for collective good and offered participants nonmonetary forms of compensation and if the access could be revoked from the third party. Conclusions Health care consumers were not strongly inclined to adopt blockchain-based PHRs and health data sharing. However, their intentions may increase when the concerns and recommendations demonstrated in this study are considered in application design.

scholarly journals Patient-Generated Health Data Quality for Clinical Use: Human and Technology Factors (Preprint)

2018 ◽  
Author(s):  
Robab Abdolkhani ◽  
Kathleen Gray ◽  
Ann Borda ◽  
Ruth De Souza
Keyword(s):  
Health Care ◽  
Human Factors ◽  
Data Quality ◽  
Real Time ◽  
Health Care Providers ◽  
Health Data ◽  
Clinical Use ◽  
Care Providers ◽  
Quality Dimensions

BACKGROUND The proliferation of advanced wearable medical technologies is increasing the production of Patient-Generated Health Data (PGHD). However, there is lack of evidence on whether the quality of the data generated from wearables can be effectively used for patient care. In order for PGHD to be utilized for decision making by health providers, it needs to be of high quality, that is, it must comply with standards defined by health care organizations and be accurate, consistent, complete and unbiased. Although medical wearables record highly accurate data, there are other technology issues as well as human factors that affect PGHD quality when it is collected and shared under patients’ control to ultimately used by health care providers. OBJECTIVE This paper explores human factors and technology factors that impact on the quality of PGHD from medical wearables for effective use in clinical care. METHODS We conducted semi-structured interviews with 17 PGHD stakeholders in Australia, the US, and the UK. Participants include ten health care providers working with PGHD from medical wearables in diabetes, sleep disorders, and heart arrhythmia, five health IT managers, and two executives. The participants were interviewed about seven data quality dimensions including accuracy, accessibility, coherence, institutional environment, interpretability, relevancy, and timeliness. Open coding of the interview data identified several technology and human issues related to the data quality dimensions regarding the clinical use of PGHD. RESULTS The overarching technology issues mentioned by participants include lack of advanced functionalities such as real-time alerts for patients as well as complicated settings which can result in errors. In terms of PGHD coherence, different wearables have different data capture mechanisms for the same health condition that create different formats which result in difficult PGHD interpretation and comparison. Another technology issue that is relevant to the current ICT infrastructure of the health care settings is lack of possibility in real-time PGHD access by health care providers which reduce the value of PGHD use. Besides, health care providers addressed a challenge on where PGHD is stored and who truthfully owns the data that affect the feasibility of PGHD access. The human factors included a lack of digital health literacy among patients which shape both the patients’ motivation and their behaviors toward PGHD collection. For example, the gaps in data recording shown in the results indicate the wearable was not used for a time duration. Participants also identified the cost of devices as a barrier to the long-term engagement and use of wearables. CONCLUSIONS Using PGHD garnered from medical wearables is problematic in clinical contexts due to low-quality data influenced by technology and human factors. At present, no guidelines have been defined to assess PGHD quality. Hence, there is a need for new solutions to overcome the existing technology and human-related barriers to enhance PGHD quality.

scholarly journals National nodes: a tool to enable efficient work of Distributed Infrastructure on Population Health

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Zaletel ◽  
P Bogaert ◽  
L A Abboud ◽  
L Palmieri ◽  
H Van Oyen ◽  
...  
Keyword(s):  
Public Health ◽  
Health Care ◽  
Focal Point ◽  
Health Care Systems ◽  
National Level ◽  
Policy Research ◽  
Field Work ◽  
Health Data ◽  
Care Systems ◽  
Future Work

Abstract   The European framework of health information (HI) consists - besides the supra-national framework - of national frameworks of health infrastructures. It is therefore essential to strengthening capacities to provide HI and carry out research in countries. Nowadays, one can experience lack of coordination, communication and cooperation between stakeholders in a country, leading to overlap or duplication of research and field-work. InfAct proposes a tool to overcome a majority of these difficulties by encouraging MSs to establish national nodes (NN) as a national focal point for DIPoH. A NN is a building block of DIPoH often coordinated by a national institution or governmental unit that functions as a NN and brings together relevant national stakeholders in an organised way. Researchers from public health institutes and research groups constitute the NN to share expertise and updated knowledge on HI with each other. Currently, there are some active NN in the EU, with differences in scope, scale and initial purpose, due to different organisation of HI systems in countries. Such heterogeneity can also be found in national eHealth strategies. Diverse organizational arrangements exist which has proven to influence collaborative activities. At the same time new needs are arising, such as to better bridge the digital HI between research and health care, so that our health care systems can faster contribute to integrated data driven insights. This also relates to the debate on the Health Data Space, which creation is stated in the mission letter to the new European Commissioner for Health. For example, the eHealth Network has been discussing policy documents targeted at national level policy with regard to the organization of National eHealth Networks. In this pitch presentation, an overview of different practices will be presented with proposals for future work in this area, including the role of NN in DIPoH and proposals for their sustainability. Panelists: H Van Oyen Epidemiology and Public Health, Sciensano, Brussels, Belgium Department of Public Health, Ghent University, Ghent, Belgium Contact: [email protected] S Montante Brussels Liaison Office, National Institute of Health of Italy (ISS), Brussels, Belgium Contact: [email protected] E Bacry Health Data Hub, Santś publique France, Paris, France E Bernal-Delgado Health Services and Policy Research Group, Institute for Health Sciences in Aragon, Zaragoza, Spain Contact: [email protected] C Sousa Pinto Advanced Analytics and Intelligence, Shared Services In Ministry Of Health, Lisbon, Portugal Contact: [email protected]

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