Reuse Of Health Data Research Articles

The EU-funded action to strengthen health information systems

Abstract The European Commission initiative to build a European Health Union recognizes the need to address in a coordinated fashion the effects of the pandemic in health and social sectors and to strengthen the resilience, accessibility and effectiveness of health systems through co-operation, best practice exchange, training schemes, technical support and improved data and knowledge management. To make the most of the potential of health data, the European Health Data Space (EHDS) is being established as one of the central building blocks of a strong European Health Union. The EHDS sets out rules, common standards, infrastructures and a governance framework for the use of electronic health data for healthcare, research, innovation and policy making. In line with these policy goals, the European Commission is funding the Action ‘Supporting Member States in the WHO European Region in strengthening health information systems and boosting health data governance’. This Action will be implemented by WHO Regional Office for Europe and aims to boost the use and reuse of health data, including by promoting, where possible, the principles and solutions developed and implemented for the EHDS. It will also contribute to the objectives of the EU Global Health Strategy to improve global health security and deliver better health for all in a changing world. In addition, the Action is designed to strengthen countries’ capacity across critical programmatic areas of health data and digital health such as data quality (including appropriate data management and analytics) and digital health literacy across the 53 Member States in the WHO European region. The main objectives of the Action are to establish a Health Information Network for strategic guidance; and develop and implement tools and capacities to strengthen health information systems, health data governance, data quality and interoperability in countries.

Sustainability in Secondary Use of Health Data - A Scoping Review.

This scoping review investigates sustainability in the reuse of health data on a technological, intra-organizational, inter-organizational, and regulatory level. Thereby, it focuses on the evolutionary, relational, and durational perspective of sustainability. The study highlights various challenges in achieving data sustainability, from regulatory norms such as FAIR principles towards data governance processes and responsibilities in organizations that facilitate data sharing. By highlighting the need for economic sustainability of health data sharing platforms and adapted principles for data sharing, this study aims to analyze current practices that aim for sustainability in the secondary use of health data.

Artificial intelligence based data curation: enabling a patient-centric European health data space.

The emerging European Health Data Space (EHDS) Regulation opens new prospects for large-scale sharing and re-use of health data. Yet, the proposed regulation suffers from two important limitations: it is designed to benefit the whole population with limited consideration for individuals, and the generation of secondary datasets from heterogeneous, unlinked patient data will remain burdensome. AIDAVA, a Horizon Europe project that started in September 2022, proposes to address both shortcomings by providing patients with an AI-based virtual assistant that maximises automation in the integration and transformation of their health data into an interoperable, longitudinal health record. This personal record can then be used to inform patient-related decisions at the point of care, whether this is the usual point of care or a possible cross-border point of care. The personal record can also be used to generate population datasets for research and policymaking. The proposed solution will enable a much-needed paradigm shift in health data management, implementing a 'curate once at patient level, use many times' approach, primarily for the benefit of patients and their care providers, but also for more efficient generation of high-quality secondary datasets. After 15 months, the project shows promising preliminary results in achieving automation in the integration and transformation of heterogeneous data of each individual patient, once the content of the data sources managed by the data holders has been formally described. Additionally, the conceptualization phase of the project identified a set of recommendations for the development of a patient-centric EHDS, significantly facilitating the generation of data for secondary use.

Consent Management System on Patient-Generated Health Data.

We consent to many things in life, but sometimes we do not know what we consent to. When discussing data protection in Europe, consent has been associated with permission under the GDPR, and health data are highly sensitive. Patients cannot make an informed decision without being provided with the information they need upfront: no informed decision, no informed consent. This paper presents a consent management system for patient-generated health data stored with HL7 FHIR specification, tested on Type 1 diabetes synthetic data. This architecture, based on using FHIR as an unequivocal data exchange format, can lead to individuals (patients) taking control of their data, enabling potential data exchange and reuse of health data across countries and organisations, in line with the European Commission proposal of a European Health Data Space.

From intention to action: The factors affecting health data sharing intention and action

IntroductionEffective prevention and treatment of diseases requires utilization of health-related lifestyle data, which has thus become increasingly important. According to some studies, participants were willing to share their health data for use in medical care and research. Although intention does not always accurately reflect action, few studies have examined the question of whether data-sharing intention leads to data-sharing action. ObjectiveThe aim of this study was to examine the extent of actualizing data-sharing intention to data-sharing action and to identify the factors that influence data-sharing intention and action. MethodsA web-based survey of members of a university examined the data-sharing intention and issues of concern when making decisions on data sharing. The participants were asked to deposit their armband data for use in research at the end of the survey. A comparison of data-sharing intention and action in relation to the participants’ characteristics was performed. Factors having a significant effect on data-sharing intention and action were identified using logistic regressions. ResultsOf 386 participants, 294 expressed willingness to share health data. However, only 73 participants deposited their armband data. The primary reason for refusal to deposit armband data was the inconvenience of the data transfer process (56.3%). Appropriate compensation had a significant effect on data-sharing intention (OR: 3.3, CI: 1.86–5.75) and action (OR: 2.8, CI: 1.14–8.21). The compensation for data sharing (OR:2.8, CI:1.14–8.21) and familiarity with data (OR:3.1, CI:1.36–8.21) were significant predictors of data sharing action, however, data-sharing intention was not (OR: 1.5, CI:0.65–3.72). ConclusionDespite expressing willingness to share their health data, the participants’ intention was not actualized to data-sharing behavior for depositing armband data. Implementation of a streamlined data transfer process and providing appropriate compensation might facilitate data-sharing. These findings could be useful in development of strategies to facilitate sharing and reuse of health data.

Pediatric biobanks to enhance clinical and translational research for children.

Including children in biomedical research is an argument for continual reflection and practice refinement from an ethical and legal standpoint. Indeed, as children reach adulthood, a reconsent method should be used, and data connected with samples should ideally be updated based on the children's growth and long-term results. Furthermore, because most pediatric disorders are uncommon, children's research initiatives should conform to standard operating procedures (SOPs) set by worldwide scientific organizations for successfully sharing data and samples. Here, we examine how pediatric biobanks can help address some challenges to improve biomedical research for children. Indeed, modern biobanks are evolving as complex research platforms with specialized employees, dedicated spaces, information technologies services (ITS), and ethical and legal expertise. In the case of research for children, biobanks can collaborate with scientific networks (i.e., BBMRI-ERIC) and provide the collection, storage, and distribution of biosamples in agreement with international standard procedures (ISO-20387). Close collaboration among biobanks provides shared avenues for maximizing scarce biological samples, which is required to promote the translation of scientific breakthroughs for developing clinical care and health policies tailored to the pediatric population. Moreover, biobanks, through their science communication and dissemination activities (i.e., European Biobank Week), may be helpful for children to understand what it means to be engaged in a research study, allowing them to see it as a pleasant, useful, and empowering experience. Additionally, biobanks can notify each participant about which projects have been accomplished (i.e., through their websites, social media networks, etc.); they can facilitate future reconsent procedures and update sample-associated data based on the children's growth. Finally, because of the increasing interest from public and commercial organizations in research efforts that include the sharing and reuse of health data, pediatric biobanks have a crucial role in this context. Consequently, they could benefit from funding opportunities for sustaining research activities even regarding rare pediatric disorders. Conclusion: Pediatric biobanks are helpful for providing biological material for research purposes, addressing ethical and legal issues (i.e. data protection, consent, etc.), and providing control samples from healthy children of various ages and from different geographical regions and ethnicities. Therefore, it is vital to encourage and maintain children's engagement in medical research programs and biobanking activities, especially as children become adults, and reconsent procedures must be applied. What is Known: • Biobanks are critical research infrastructures for medical research, especially in the era of "omic" science. However, in light of their fragility and rights children's participation in biobanking and medical research programs is a complex argument of continuous debate in scientific literature. What is New: • We propose a review of the literature on pediatric biobanks with a particular focus on oncological biobanks. The main current limitations and challenges for pediatric biobanks are presented and possible solutions are discussed.

8.G. Workshop: European Health Data Space: Dialogue on TEHDAS JA data quality & semantic interoperability proposals

Abstract The EU Data Strategy foresees the development of shared European data infrastructures, enabling cross-border exchange and availability of comparable and high-quality data. The European Health Data Space (EHDS) is the first of these infrastructures to be launched, making use of the potential of health and social data for the purpose of advancing public health, research and innovation. Quality of digital health data has been the focus of research and debate for a long time and several proposals for improvement have been put forward. While these efforts are ongoing, secondary use or re-use of health data, combined with recent developments in data analytics, AI and real-world data (RWD), have raised new requirements on our understanding of data quality and the means for its assurance. Both the European Commission and Member States have underlined the need to support EU and national authorities, as well as the scientific community to agree on interoperability guidelines addressing data quality and semantic interoperability. The TEHDAS Joint Action has responded to these expectations through work undertaken in the context of WP6 - Excellence in data quality. With expected delivery deadline early 2023, the EUPHA conference offers an excellent platform to present the draft forthcoming proposals to the public health community and engage in meaningful dialogue with participants. Key members of the WP6 team will present the process through which the TEHDAS JA recommendations on data quality and semantic interoperability have been developed, the results achieved thus far and the remaining open questions. The workshop discussion section will allow the JA team to collect direct input and feedback for utilization in the production of the final version of the deliverables. Key messages • Increased awareness and understanding of background and rational of forthcoming proposals on data quality and semantic interoperability in the European Health Data Space. • Opportunity to raise concerns and proposals for improvement and thus have a direct impact on the final TEHDAS JA output on data quality.

A Social Media Campaign (#datasaveslives) to Promote the Benefits of Using Health Data for Research Purposes: Mixed Methods Analysis.

BackgroundSocial media provides the potential to engage a wide audience about scientific research, including the public. However, little empirical research exists to guide health scientists regarding what works and how to optimize impact. We examined the social media campaign #datasaveslives established in 2014 to highlight positive examples of the use and reuse of health data in research.ObjectiveThis study aims to examine how the #datasaveslives hashtag was used on social media, how often, and by whom; thus, we aim to provide insights into the impact of a major social media campaign in the UK health informatics research community and further afield.MethodsWe analyzed all publicly available posts (tweets) that included the hashtag #datasaveslives (N=13,895) on the microblogging platform Twitter between September 1, 2016, and August 31, 2017. Using a combination of qualitative and quantitative analyses, we determined the frequency and purpose of tweets. Social network analysis was used to analyze and visualize tweet sharing (retweet) networks among hashtag users.ResultsOverall, we found 4175 original posts and 9720 retweets featuring #datasaveslives by 3649 unique Twitter users. In total, 66.01% (2756/4175) of the original posts were retweeted at least once. Higher frequencies of tweets were observed during the weeks of prominent policy publications, popular conferences, and public engagement events. Cluster analysis based on retweet relationships revealed an interconnected series of groups of #datasaveslives users in academia, health services and policy, and charities and patient networks. Thematic analysis of tweets showed that #datasaveslives was used for a broader range of purposes than indexing information, including event reporting, encouraging participation and action, and showing personal support for data sharing.ConclusionsThis study shows that a hashtag-based social media campaign was effective in encouraging a wide audience of stakeholders to disseminate positive examples of health research. Furthermore, the findings suggest that the campaign supported community building and bridging practices within and between the interdisciplinary sectors related to the field of health data science and encouraged individuals to demonstrate personal support for sharing health data.

Health Data Processes: A Framework for Analyzing and Discussing Efficient Use and Reuse of Health Data With a Focus on Patient-Reported Outcome Measures.

The collection and use of patient health data are central to any kind of activity in the health care system. These data may be produced during routine clinical processes or obtained directly from the patient using patient-reported outcome (PRO) measures. Although efficiency and other reasons justify data availability for a range of potentially relevant uses, these data are nearly always collected for a single specific purpose. The health care literature reflects this narrow scope, and there is limited literature on the joint use of health data for daily clinical use, clinical research, surveillance, and administrative purposes. The aim of this paper is to provide a framework for discussing the efficient use of health data with a specific focus on the role of PRO measures. PRO data may be used at an individual patient level to inform patient care or shared decision making and to tailor care to individual needs or group-level needs as a complement to health record data, such as that on mortality and readmission, in order to inform service delivery and measure the real-world effectiveness of treatment. PRO measures may be used either for their own sake, to provide valuable information from the patient perspective, or as a proxy for clinical data that would otherwise not be feasible to collect. We introduce a framework to analyze any health care activity that involves health data. The framework consists of four data processes (patient identification, data collection, data aggregation and data use), further structured into two dichotomous dimensions in each data process (level: group vs patient; timeframe: ad hoc vs systematic). This framework is used to analyze various health activities with respect to joint use of data, considering the technical, legal, organizational, and logistical challenges that characterize each data process. Finally, we propose a model for joint use of health data with data collected during follow-up as a base. Demands for health data will continue to increase, which will further add to the need for the concerted use and reuse of PRO data for parallel purposes. Repeated and uncoordinated PRO data collection for the same patient for different purposes results in misuse of resources for the patient and the health care system as well as reduced response rates owing to questionnaire fatigue. PRO data can be routinely collected both at the hospital (from inpatients as well as outpatients) and outside of hospital settings; in primary or social care settings; or in the patient’s home, provided the health informatics infrastructure is in place. In the future, clinical settings are likely to be a prominent source of PRO data; however, we are also likely to see increased remote collection of PRO data by patients in their own home (telePRO). Data collection for research and quality surveillance will have to adapt to this circumstance and adopt complementary data capture methods that take advantage of the utility of PRO data collected during daily clinical practice. The European Union’s regulation with respect to the protection of personal data—General Data Protection Regulation—imposes severe restrictions on the use of health data for parallel purposes, and steps should be taken to alleviate the consequences while still protecting personal data against misuse.

Between Scylla and Charybdis: Charting the Wicked Problem of Reusing Health Data for Clinical Research Informatics.

Summary Objectives: Recognising dilemmas posed by the sharing and reuse of health data as a classic wicked problem and uncover some current key challenges to clinical research informatics. Methods: A modified thematic review process including identification of agreed critical research questions, appropriate query terms and search strategy, identification of relevant papers in accordance with inclusion criteria, and authors' co-review of full text papers. Results: Queries returned 4,779 papers published between January 2014 and November 2017. A shortlist of 197 abstracts was analysed and 18 papers were finally selected for review. Thematic assessment of findings revealed four key challenges: (1) uncertain reliability of consent as a cornerstone of trust due to the limits to understanding and awareness of data sharing; (2) ethical challenges around equity and autonomy; (3) ambitious overly theoretical governance frameworks lacking practical validity; and (4) a clear desire for further public and individual engagement to achieve clearer and more nuanced knowledge dissemination around data sharing practice and governance frameworks. Conclusions: Understanding the wicked problem of reusing clinically acquired health data for research purposes is essential if clinical research is to benefit from informatics advances. A lack of understanding around the context of data acquisition and sharing undermines the foundations of patient-professional trust. Efforts to protect privacy, where tailoring to specific contexts is a key driver, should support the development of solutions which more adequately honour privacy needs, justify access, and protect equity and autonomy.

Assessing the Financial Impact of Reusing Electronic Health Records Data for Clinical Research: Results from the EHR4CR European Project

Background: The new technological platform developed by the Electronic Health Records for Clinical Research (EHR4CR) European research project (2011-2016) has been specially designed to enable the trustworthy reuse of health data contained in hospital-based electronic health records (EHR) for enhancing and speeding up clinical research scenarios. In particular, protocol feasibility assessments, patient identification for recruitment, and clinical data exchange for study conduct, in accordance with data privacy, ethical and legal requirements. The objective of our study was to assess the financial impact of adopting these advanced solutions compared to current practices, from the perspective of the primary sponsors of clinical trials in Europe. Methods: Considering a scalable implementation of EHR4CR solutions in up to 5-10% of Phase II, III and IV clinical trials to be commercially sponsored in Europe over 5 years, two potential market sizes were defined. The first has a European initial scope (i.e., for European clinical trials only), and the second has a European subsequent broader scope (also including European arms of global studies). Based on expert opinions, the EHR4CR initial scope target market was estimated to be 30% of the broader scope. Direct costs to clinical research sponsors were estimated under current practices, and with the EHR4CR platform. Uncertainty was managed using 100,000 Monte Carlo simulations. Results: Compared to current practices, the potential average 5-year savings with EHR4CR solutions for Phase II, III and IV commercially sponsored clinical trials in Europe were estimated at €175.5 m for the European initial scope market, and at €585.3 m for the European broader scope market. These results were confirmed by robust probabilistic sensitivity analyses. Conclusions: Compared to current practices, EHR4CR solutions appear cost-saving for primary sponsors of clinical trials. These results suggest that the potential for savings would increase with a broader adoption of EHR4CR solutions in Europe, and beyond.

Discussion of "Combining Health Data Uses to Ignite Health System Learning".

This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Combining Health Data Uses to Ignite Health System Learning" written by John D. Ainsworth and Iain E. Buchan [1]. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the paper of Ainsworth and Buchan. In subsequent issues the discussion can continue through letters to the editor. With these comments on the paper "Combining Health Data Uses to Ignite Health System Learning", written by John D. Ainsworth and Iain E. Buchan [1], the journal seeks to stimulate a broad discussion on new ways for combining data sources for the reuse of health data in order to identify new opportunities for health system learning. An international group of experts has been invited by the editor of Methods to comment on this paper. Each of the invited commentaries forms one section of this paper.