New technologies are increasingly evaluated for use within the clinical practice to monitor patients' medical and lifestyle data. This development could contribute to a more personalized approach to patient care and potentially improve health outcomes. To date, patient perspective on this development has mostly been neglected in the literature. Hence, this study aims to shed more light on the patient perspective on health data privacy and management. Focus groups with cardiac patients were done at the Elizabeth TweeSteden Ziekenhuis (ETZ) in the Netherlands as part of the DoCHANGE project. The focus groups were conducted using a semistructured protocol which was organized around three themes: privacy regulations, data storage, and transparency and privacy management. Five focus groups with a total of 23 patients were conducted. The majority of the patients preferred to have access to their medical data; however, the knowledge on who has access to data was limited. Patients indicated that they do not want to share their medical data with health insurance companies or the pharmaceutical industry. Furthermore, most patients do not see the added value of supplementing their medical dossier with lifestyle data. Current findings showed patients prefer access to and control over own data but that the knowledge concerning data privacy and management is limited. Sharing of non-medical health data (e.g.,, physical activity) was considered unnecessary. Future studies should address patient preferences and develop infrastructure which facilitates medical data access for patients.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6304538 | PMC |
http://dx.doi.org/10.1155/2018/3838747 | DOI Listing |
PLoS One
January 2025
Taiyuan University, Taiyuan, China.
Internal auditing demands innovative and secure solutions in today's business environment, with increasing competitive pressure and frequent occurrences of risky and illegal behaviours. Blockchain along with secure databases like encryption improves internal audit security through immutability and transparency. Hence integrating blockchain with homomorphic encryption and multi-factor authentication improves privacy and mitigates computational overhead.
View Article and Find Full Text PDFCurr Res Transl Med
January 2025
Department of Research and Innovation, Medway NHS Foundation Trust, Gillingham ME7 5NY, United Kingdom; Faculty of Medicine, Health and Social Care, Canterbury Christ Church University, United Kingdom.
This narrative review examines the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in organ retrieval and transplantation. AI and ML technologies enhance donor-recipient matching by integrating and analyzing complex datasets encompassing clinical, genetic, and demographic information, leading to more precise organ allocation and improved transplant success rates. In surgical planning, AI-driven image analysis automates organ segmentation, identifies critical anatomical features, and predicts surgical outcomes, aiding pre-operative planning and reducing intraoperative risks.
View Article and Find Full Text PDFBig Data
January 2025
Department of Engineering Management, University of Antwerp, Antwerp, Belgium.
Our online lives generate a wealth of behavioral records--which are stored and leveraged by technology platforms. These data can be used to create value for users by personalizing services. At the same time, however, it also poses a threat to people's privacy by offering a highly intimate window into their private traits (e.
View Article and Find Full Text PDFJ Family Med Prim Care
December 2024
Department of Research Development and Cooperation, Pakistan Medical Research Council, Islamabad, Pakistan.
Background: Breaking bad news is one of the most difficult tasks for practicing doctors, especially for those working in health care specialties where life-threatening diseases are diagnosed and managed routinely. Our aim was to elicit the knowledge and practices of doctors and identify barriers faced by them in disclosure of bad news across the provinces of Pakistan.
Methods: Cross-sectional, multi-centered study supported by an external grant in 15 Government and Private Hospitals across Pakistan.
BMC Nurs
January 2025
Department of Healthcare Management Research Center, Chiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba, 260-8677, Japan.
Aim: This study aimed to explore the emotions of operating room nurses in Japan towards perioperative nursing using generative AI and human analysis, and to identify factors contributing to burnout and turnover.
Methods: A single-center cross-sectional study was conducted from February 2023 to February 2024, involving semi-structured interviews with 10 operating room nurses from a national hospital in Japan. Interview transcripts were analyzed using generative AI (ChatGPT-4o) and human researchers for thematic, emotional, and subjectivity analysis.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!