Privacy in characterizing and recruiting patients for IoHT-aided digital clinical trials

Nowadays there is a tremendous amount of smart and connected devices that produce data. The so-called IoT is so pervasive that its devices (in particular the ones that we take with us during all the day - wearables, smartphones...) often provide some insights on our lives to third parties. People habitually exchange some of their private data in order to obtain services, discounts and advantages. Sharing personal data is commonly accepted in contexts like social networks but individuals suddenly become more than concerned if a third party is interested in accessing personal health data. The healthcare systems worldwide, however, begun to take advantage of the data produced by eHealth solutions. It is clear that while on one hand the technology proved to be a great ally in the modern medicine and can lead to notable benefits, on the other hand these processes pose serious threats to our privacy. The process of testing, validating and putting on the market a new drug or medical treatment is called clinical trial. These trials are deeply impacted by the technological advancements and greatly benefit from the use of eHealth solutions. The clinical research institutes are the entities in charge of leading the trials and need to access as much health data of the patients as possible. However, at any phase of a clinical trial, the personal information of the participants should be preserved and maintained private as long as possible. During this thesis, we will introduce an architecture that protects the privacy of personal data during the first phases of digital clinical trials (namely the characterization phase and the recruiting phase), allowing potential participants to freely join trials without disclosing their personal health information without a proper reward and/or prior agreement. We will illustrate what is the trusted environment that is the most used approach in eHealth and, later, we will dig into the untrusted environment where the concept of privacy is more challenging to protect while maintaining usability of data. Our architecture maintains the individuals in full control over the flow of their personal health data. Moreover, the architecture allows the clinical research institutes to characterize the population of potentiant users without direct access to their personal data. We validated our architecture with a proof of concept that includes all the involved entities from the low level hardware up to the end application. We designed and realized the hardware capable of sensing, processing and transmitting personal health data in a privacy preserving fashion that requires little to none maintenance

Patient Controlled, Privacy Preserving IoT Healthcare Data Sharing Framework

Healthcare data personally collected by individuals with wearable devices have become important sources of information for healthcare professionals and medical research worldwide. User-Generated Data (UGD) offers unique and sometimes fine-grained insight into the lived experiences and medical conditions of patients. The sensitive subject-matter of medical data can facilitate the exploitation and/or control of victims. Data collection in medical research therefore restricts access control over participant-data to the researchers. Therefore, cultivating trust with prospective participants concerned about the security of their medical data presents formidable challenges. Anonymization can allay such concerns, but at the cost of information loss. Moreover, such techniques cannot necessarily be applied on real-time streaming health data. In this paper, we aim to analyze the technical requirements to enable individuals to share their real-time wearable healthcare data with researchers without compromising privacy. An extension for delay-free anonymization techniques for real-time streaming health data is also proposed

pSCANNER: Patient-centered scalable national network for effectiveness research

pre-printThis article describes the patient-centered Scalable National Network for Effectiveness Research (pSCANNER), which is part of the recently formed PCORnet, a national network composed of learning healthcare systems and patient-powered research networks funded by the Patient Centered Outcomes Research Institute (PCORI). It is designed to be a stakeholder-governed federated network that uses a distributed architecture to integrate data from three existing networks covering over 21 million patients in all 50 states: (1) VA Informatics and Computing Infrastructure (VINCI), with data from Veteran Health Administration's 151 inpatient and 909 ambulatory care and community-based outpatient clinics; (2) the University of California Research exchange (UC-ReX) network, with data from UC Davis, Irvine, Los Angeles, San Francisco, and San Diego; and (3) SCANNER, a consortium of UCSD, Tennessee VA, and three federally qualified health systems in the Los Angeles area supplemented with claims and health information exchange data, led by the University of Southern California. Initial use cases will focus on three conditions: (1) congestive heart failure; (2) Kawasaki disease; (3) obesity. Stakeholders, such as patients, clinicians, and health service researchers, will be engaged to prioritize research questions to be answered through the network. We will use a privacy-preserving distributed computation model with synchronous and asynchronous modes. The distributed system will be based on a common data model that allows the construction and evaluation of distributed multivariate models for a variety of statistical analyses

The Use of Blockchain Technology in the Health Care Sector:Systematic Review

BACKGROUND: Blockchain technology is a part of Industry 4.0’s new Internet of Things applications: decentralized systems, distributed ledgers, and immutable and cryptographically secure technology. This technology entails a series of transaction lists with identical copies shared and retained by different groups or parties. One field where blockchain technology has tremendous potential is health care, due to the more patient-centric approach to the health care system as well as blockchain’s ability to connect disparate systems and increase the accuracy of electronic health records. OBJECTIVE: The aim of this study was to systematically review studies on the use of blockchain technology in health care and to analyze the characteristics of the studies that have implemented blockchain technology. METHODS: This study used a systematic review methodology to find literature related to the implementation aspect of blockchain technology in health care. Relevant papers were searched for using PubMed, SpringerLink, IEEE Xplore, Embase, Scopus, and EBSCOhost. A quality assessment of literature was performed on the 22 selected papers by assessing their trustworthiness and relevance. RESULTS: After full screening, 22 papers were included. A table of evidence was constructed, and the results of the selected papers were interpreted. The results of scoring for measuring the quality of the publications were obtained and interpreted. Out of 22 papers, a total of 3 (14%) high-quality papers, 9 (41%) moderate-quality papers, and 10 (45%) low-quality papers were identified. CONCLUSIONS: Blockchain technology was found to be useful in real health care environments, including for the management of electronic medical records, biomedical research and education, remote patient monitoring, pharmaceutical supply chains, health insurance claims, health data analytics, and other potential areas. The main reasons for the implementation of blockchain technology in the health care sector were identified as data integrity, access control, data logging, data versioning, and nonrepudiation. The findings could help the scientific community to understand the implementation aspect of blockchain technology. The results from this study help in recognizing the accessibility and use of blockchain technology in the health care sector

Ethical Issues of Social Media Usage in Healthcare

Accepted manuscript version. This article is not an exact copy of the original published article in The IMIA Yearbook of Medical Informatics. The definitive publisher-authenticated version of "Ethical Issues of Social Media Usage in Healthcare" is available online at http://doi.org/10.15265/IY-2015-001.OBJECTIVE: Social media, web and mobile technologies are increasingly used in healthcare and directly support patientcentered care. Patients benefit from disease self-management tools, contact to others, and closer monitoring. Researchers study drug efficiency, or recruit patients for clinical studies via these technologies. However, low communication barriers in socialmedia, limited privacy and security issues lead to problems from an ethical perspective. This paper summarizes the ethical issues to be considered when social media is exploited in healthcare contexts. METHODS: Starting from our experiences in social-media research, we collected ethical issues for selected social-media use cases in the context of patient-centered care. Results were enriched by collecting and analyzing relevant literature and were discussed and interpreted by members of the IMIA Social Media Working Group. RESULTS: Most relevant issues in social-media applications are confidence and privacy that need to be carefully preserved. The patient-physician relationship can suffer from the new information gain on both sides since private information of both healthcare provider and consumer may be accessible through the Internet. Physicians need to ensure they keep the borders between private and professional intact. Beyond, preserving patient anonymity when citing Internet content is crucial for research studies. CONCLUSION: Exploiting medical social-media in healthcare applications requires a careful reflection of roles and responsibilities. Availability of data and information can be useful in many settings, but the abuse of data needs to be prevented. Preserving privacy and confidentiality of online users is a main issue, as well as providing means for patients or Internet users to express concerns on data usage

Identifying Technology(ies) for clinical research post COVID-19

Clinical research aims to understand diagnostic methods, diseases, and new treatments or medical devices that can advance patient care. The COVID-19 pandemic in 2020, a respiratory disease caused by SARS-CoV-2, impacted clinical research units in healthcare and brought new perspectives on how to better the future of clinical research by adopting modern technology. Clinical research has encountered much advancement over the years, with technology being the primary factor that accelerates clinical research growth. Incorporating new technology in clinical research translates to increased productivity and efficacy in patient engagements, trial management, novel outcomes, and reduced patient burden. The application of new technology in clinical research and next-generation clinical trials can be made effectively with lower costs and more accurate data. In this paper, an in-depth literature review was done to evaluate and discuss how the COVID-19 pandemic brought new transformations to clinical research and how the incorporated technology will transform in the future to optimize patient care. Many remote technologies were deployed, such as eConsent, home care visits, and direct drug delivery, resulting in better data collection and saving time and resources

Utilizing blockchain technology for clinical trial optimization

Clinical trials are the cornerstone of treatment discovery because they provide comprehensive scientific evidence on the safety, efficacy, and optimal use of therapeutics. However, current clinical trials are facing multiple challenges such as patient recruitment, data capture, and overall management. There are various causes of patient recruitment challenges such as inefficient advertising models, complex protocols, and distant trial sites. Data inconsistency is the main challenge of the data capture process. Source data verification, a standard method used for data monitoring, is resource-intensive that can cost up to 25 percent of the total budget. The current clinical trial management system market is fragmented and lacks thorough designs with all desired features so that nearly all respondents to management systems from the annual global survey reported dissatisfaction with the current management system. Based on these challenges, disruptive technologies such as blockchain may provide feasible solutions by utilizing its unique features. Blockchain is an open-source distributed ledger technology that was first applied in the financial sector. Its features such as public audibility, data security, immutability, anonymity, and smart contracts are a good fit for the needs of many healthcare applications. However, there are several common challenges of blockchain technology so that most blockchain designs for healthcare applications are still in the early stage of implementation. This dissertation aims at optimizing clinical trials by developing multiple applications using blockchain technology to provide feasible solutions to the current challenges. We will use real-world data to conduct large-scale simulations to evaluate the feasibility and performance of proposed blockchain models for clinical trial applications

Rationale and design of the United Kingdom Heart Failure with Preserved Ejection Fraction Registry

\ua9 Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.Objective: Heart failure with preserved ejection fraction (HFpEF) is a common heterogeneous syndrome that remains imprecisely defined and consequently has limited treatment options and poor outcomes. Methods: The UK Heart Failure with Preserved Ejection Fraction Registry (UK HFpEF) is a prospective data-enabled cohort and platform study. The study will develop a large, highly characterised cohort of patients with HFpEF. A biobank will be established. Deep clinical phenotyping, imaging, multiomics and centrally held national electronic health record data will be integrated at scale, in order to reclassify HFpEF into distinct subgroups, improve understanding of disease mechanisms and identify new biological pathways and molecular targets. Together, these will form the basis for developing diagnostics and targeted therapeutics specific to subgroups. It will be a platform for more effective and efficient trials, focusing on subgroups in whom targeted interventions are expected to be effective, with consent in place to facilitate rapid recruitment, and linkage for follow-up. Patients with a diagnosis of HFpEF made by a heart failure specialist, who have had natriuretic peptide levels measured and a left ventricular ejection fraction >40% are eligible. Patients with an ejection fraction between 40% and 49% will be limited to no more than 25% of the cohort. Conclusions: UK HFpEF will develop a rich, multimodal data resource to enable the identification of disease endotypes and develop more effective diagnostic strategies, precise risk stratification and targeted therapeutics. Trial registration number: NCT05441839

You scratch my back, and I scratch yours: Bartering for qualitative data

Recruiting research participants has been one of the significant challenges faced by qualitative researchers. Barter gained momentum during the Covid pandemic across a broad spectrum of professionals, including scholars searching to recruit research participants, despite being surrounded by ethical concerns of coercion or undue influence. This reflective paper created a barter reflective and ethical protocol showing how bartering created the entrepreneurial opportunity for 16 migrant entrepreneurs to exchange an average of 60 minutes of their time for participating in a qualitative interview with an average of 2.25 hrs (145 minutes) of business counselling and translation services delivered by the researcher. This paper contributes to the methodological practice of bartering. It argues that bartering is an ethical and efficient research practice in need of a code of ethics and protocol and should not be dismissed as ethically suspect until substantial evidence is brought forwar