Use Of Healthcare Data Research Articles

Decentralized and Secure Collaborative Framework for Personalized Diabetes Prediction.

Diabetes is a global epidemic with severe consequences for individuals and healthcare systems. While early and personalized prediction can significantly improve outcomes, traditional centralized prediction models suffer from privacy risks and limited data diversity. This paper introduces a novel framework that integrates blockchain and federated learning to address these challenges. Blockchain provides a secure, decentralized foundation for data management, access control, and auditability. Federated learning enables model training on distributed datasets without compromising patient privacy. This collaborative approach facilitates the development of more robust and personalized diabetes prediction models, leveraging the combined data resources of multiple healthcare institutions. We have performed extensive evaluation experiments and security analyses. The results demonstrate good performance while significantly enhancing privacy and security compared to centralized approaches. Our framework offers a promising solution for the ethical and effective use of healthcare data in diabetes prediction.

Hierarchical Clustering Analysis to Inform Classification of Congenital Malformations for Surveillance of Medication Safety in Pregnancy.

There is growing interest in the secondary use of healthcare data to evaluate medication safety in pregnancy. Tree-based scan statistics (TBSS) offer an innovative approach to help identify potential safety signals. TBSS utilize hierarchically organized outcomes, generally based on existing clinical coding systems that group outcomes by organ system. When assessing teratogenicity, such groupings often lack a sound embryologic basis given the etiologic heterogeneity of congenital malformations. The study objective was to enhance the grouping of congenital malformations to be used in scanning approaches through implementation of hierarchical clustering analysis (HCA) and to pilot test an HCA-enhanced TBSS approach for medication safety surveillance in pregnancy in two test cases using >4.2 million mother-child dyads from two US-nationwide databases. HCA identified (1) malformation combinations belonging to the same organ system already grouped in existing classifications, (2) known combinations across different organ systems not previously grouped, (3) unknown combinations not previously grouped, and (4) malformations seemingly standing on their own. Testing the approach with valproate and topiramate identified expected signals, and a signal for an HCA-cluster missed by traditional classification. Augmenting existing classifications with clusters identified through large data exploration may be promising when defining phenotypes for surveillance and causal inference studies.

Assessing Opportunities and Barriers to Improving the Secondary Use of Health Care Data at the National Level: Multicase Study in the Kingdom of Saudi Arabia and Estonia.

Digitization shall improve the secondary use of health care data. The Government of the Kingdom of Saudi Arabia ordered a project to compile the National Master Plan for Health Data Analytics, while the Government of Estonia ordered a project to compile the Person-Centered Integrated Hospital Master Plan. This study aims to map these 2 distinct projects' problems, approaches, and outcomes to find the matching elements for reuse in similar cases. We assessed both health care systems' abilities for secondary use of health data by exploratory case studies with purposive sampling and data collection via semistructured interviews and documentation review. The collected content was analyzed qualitatively and coded according to a predefined framework. The analytical framework consisted of data purpose, flow, and sharing. The Estonian project used the Health Information Sharing Maturity Model from the Mitre Corporation as an additional analytical framework. The data collection and analysis in the Kingdom of Saudi Arabia took place in 2019 and covered health care facilities, public health institutions, and health care policy. The project in Estonia collected its inputs in 2020 and covered health care facilities, patient engagement, public health institutions, health care financing, health care policy, and health technology innovations. In both cases, the assessments resulted in a set of recommendations focusing on the governance of health care data. In the Kingdom of Saudi Arabia, the health care system consists of multiple isolated sectors, and there is a need for an overarching body coordinating data sets, indicators, and reports at the national level. The National Master Plan of Health Data Analytics proposed a set of organizational agreements for proper stewardship. Despite Estonia's national Digital Health Platform, the requirements remain uncoordinated between various data consumers. We recommended reconfiguring the stewardship of the national health data to include multipurpose data use into the scope of interoperability standardization. Proper data governance is the key to improving the secondary use of health data at the national level. The data flows from data providers to data consumers shall be coordinated by overarching stewardship structures and supported by interoperable data custodians.

Comprehensive assessment of pediatric acute and inpatient care at a tertiary referral hospital in Malawi: opportunities for quality improvement

BackgroundDespite the reduction in global under-5 mortality over the last decade, childhood deaths remain high. To combat this, there has been a shift in focus from disease-specific interventions to use...

Anonymization and Pseudonymization of FHIR Resources for Secondary Use of Healthcare Data

Anonymization and Pseudonymization of FHIR Resources for Secondary Use of Healthcare Data

Synergies at the Intersection: Exploring the Role of Bioinformatics in Enhancing Physiotherapy and Nursing Practice

In contemporary healthcare, integrating bioinformatics with physiotherapy and nursing science has emerged as a promising approach to personalized patient care and clinical decision-making. This study explores the synergistic potential of this integration, aiming to enhance healthcare delivery and improve patient outcomes. The fundamental concepts and applications of bioinformatics are discussed, highlighting its role in analyzing biological data and informing evidence-based practice. Subsequently, an overview of physiotherapy and nursing roles in patient care is provided, emphasizing their holistic approach and interdisciplinary collaboration. The study examines the benefits and challenges of integrating bioinformatics into clinical practice, including personalized treatment planning, disease diagnosis, and predictive modeling. Case studies and examples illustrating successful integration efforts are presented, along with potential applications and future directions for bioinformatics-driven healthcare. Furthermore, the importance of data management and analysis in healthcare settings is explored, discussing tools, techniques, and ethical considerations related to the use of healthcare data. However, collaborative approaches and interdisciplinary teamwork strategies are discussed, emphasizing the need for education, research, policy development, and infrastructure investments to support the integration of bioinformatics into healthcare delivery. This study highlights the transformative potential of bioinformatics-driven approaches in physiotherapy and nursing practice, providing insights for healthcare professionals, researchers, policymakers, and educators.

Healthcare data quality assessment for improving the quality of the Korea Biobank Network.

Numerous studies make extensive use of healthcare data, including human materials and clinical information, and acknowledge its significance. However, limitations in data collection methods can impact the quality of healthcare data obtained from multiple institutions. In order to secure high-quality data related to human materials, research focused on data quality is necessary. This study validated the quality of data collected in 2020 from 16 institutions constituting the Korea Biobank Network using 104 validation rules. The validation rules were developed based on the DQ4HEALTH model and were divided into four dimensions: completeness, validity, accuracy, and uniqueness. Korea Biobank Network collects and manages human materials and clinical information from multiple biobanks, and is in the process of developing a common data model for data integration. The results of the data quality verification revealed an error rate of 0.74%. Furthermore, an analysis of the data from each institution was performed to examine the relationship between the institution's characteristics and error count. The results from a chi-square test indicated that there was an independent correlation between each institution and its error count. To confirm this correlation between error counts and the characteristics of each institution, a correlation analysis was conducted. The results, shown in a graph, revealed the relationship between factors that had high correlation coefficients and the error count. The findings suggest that the data quality was impacted by biases in the evaluation system, including the institution's IT environment, infrastructure, and the number of collected samples. These results highlight the need to consider the scalability of research quality when evaluating clinical epidemiological information linked to human materials in future validation studies of data quality.

Patient and public involvement to inform priorities and practice for research using existing healthcare data for children’s and young people’s cancers

BackgroundIn the United Kingdom, healthcare data is collected on all patients receiving National Health Service (NHS) care, including children and young people (CYP) with cancer. This data is used to inform service delivery, and with special permissions used for research. The use of routinely collected health data in research is an advancing field with huge potential benefit, particularly in CYP with cancer where case numbers are small and the impact across the life course can be significant.Patient and public involvement (PPI) exercise aims:Identify current barriers to trust relating to the use of healthcare data for research.Determine ways to increase public and patient confidence in the use of healthcare data in research.Define areas of research importance to CYP and their carers using healthcare data.MethodsYoung people currently aged between 16 and 25 years who had a cancer diagnosis before the age of 20 years and carers of a young person with cancer were invited to take part via social media and existing networks of service users. Data was collected during two interactive online workshops totalling 5 h and comprising of presentations from health data experts, case-studies and group discussions. With participant consent the workshops were recorded, transcribed verbatim and analysed using thematic analysis.ResultsTen young people and six carers attended workshop one. Four young people and four carers returned for workshop two. Lack of awareness of how data is used, and negative media reporting were seen as the main causes of mistrust. Better communication and education on how data is used were felt to be important to improving public confidence. Participants want the ability to have control over their own data use. Late effects, social and education outcomes and research on rare tumours were described as key research priorities for data use.ConclusionsIn order to improve public and patient trust in our use of data for research, we need to improve communication about how data is used and the benefits that arise.

The Data-Driven Future of Healthcare: A Review

The future of disease detection, treatment, and prevention may very well lie in data-driven healthcare. Here, we take stock of where things stand and highlight certain emerging issues and long-standing difficulties. We looked at all the research that has been published on the topic of data-driven healthcare decision-making. Our research shows that the use of data in healthcare has already improved patient care and results. However, there are substantial obstacles that must be overcome, such as the need to more effectively integrate data from multiple sources, as well as issues with data quality, privacy, and security. Furthermore, healthcare data use raises significant ethical concerns. We examine what these results mean for the future of data-driven healthcare and offer suggestions on where future research should focus. We conclude that data-driven healthcare has the potential to transform healthcare delivery and enhance patient outcomes, but that the inherent difficulties and dangers of this approach must be carefully considered.

Privacy and health data management.

The effective use of data in healthcare, and the use of information to support decision-making processes is a key issue. Experiencing the Covid-19 pandemic drove to important developments in a relatively short time. In this context, Cittadinanzattiva, which has been dealing with citizens' rights in the health field for years, is really interested in exploring the boundaries between citizens' right to privacy and the promotion of health as a fundamental human right. New strategies to protect the individual and his dignity should be identified, without hindering the use of data to support health policy. The relationship between health and privacy is a pivotal issue because it involves two of the fundamental rights that are most exposed to the evolution of technology and innovation.

Register-based research and clinical studies : Possibilities, limitations and perspectives

Register-based research offers agood opportunity to generate knowledge on questions from the clinical practice. Methodologically high-quality register studies can complement clinical studies, especially for questions that cannot be answered with randomized controlled trials (RCT). The ad hoc committee on healthcare data of the German Network for Health Services Research (DNVF) has set methodological guidelines for register-based studies with a manual for methods and the use of healthcare data. The methodological advantages of both approaches can be integrated through RCTs embedded in registers. In Germany there is a diverse register landscape as shown by the register report commissioned by the Federal Ministry of Health, which, however, show avarying degree of internationally recognized quality criteria. The relevance of register-based studies for the clinical practice (e.g. guideline development) is shown in the examples of applications cited in the article. Although alot has already been done here in Germany with existing register data, sustainable coordination and promotion of the research infrastructure and research culture, especially in international comparison are necessary.

Lack of consensus on the definition of severe congenital heart defects for research: A challenge for comparing international studies.

Lack of consensus on the definition of severe congenital heart defects for research: A challenge for comparing international studies.

Koncept privatnosti podataka u elektronskom zdravstvenom sistemu zasnovan na blokčejn tehnologiji

Introduction/purpose: Advances in information and communication technologies have enabled the creation of a symbiotic environment of humans and machines in which humans interact with machines to get better quality of everyday life. In that interaction, environment problems of information security and in particular data privacy are at the forefront. In many countries, there is legal regulation that regulates this problem in terms of securing the goals that must be realized when manipulating private data, and the technology itself is the choice of the creators of information systems. Blockchain technology is one of the methods of choice to ensure the integrity of data and undeniable transactions while digital certificates in conjunction with it enable the realization of data privacy of patients. Methods: The cryptographic methods of asymmetric cryptography apply blockchain technology and reliable methods of identification in cyberspace, which enables the preservation of data privacy at a high level. Results: This paper describes the method of patient health data privacy protection in a healthcare system based on digital certificates as an identification method in cyberspace and Blockchain technology as a method for preserving the integrity of transactions and a healthcare information system. The proposed concept enables the separation of private and medical data in such a way that with the accepted principle of patient ownership of medical data, it is possible to achieve primary and secondary use of healthcare data without compromising the patient's privacy. Conclusions: The concept of identity assignment to every element in the healthcare information system and the organization/storage of data in accordance with the principles of Blockchain technology proposed in this paper enable the realization of a high level of data privacy in accordance with the European Union General Data Protection Regulation at the international level. In addition, the proposed concept enables the detection of unregistered devices or entities in the system and thus preserves the integrity of the system and increases its overall information security.

Secondary use of health care data and left-over biosamples within the ‘Medical Informatics Initiative’ (MII): a quasi-randomized controlled evaluation of patient perceptions and preferences regarding the consent process

BackgroundData collected during routine health care and ensuing analytical results bear the potential to provide valuable information to improve the overall health care of patients. However, little is known about how patients prefer to be informed about the possible usage of their routine data and/or biosamples for research purposes before reaching a consent decision. Specifically, we investigated the setting, the timing and the responsible staff for the information and consent process.MethodsWe performed a quasi-randomized controlled trial and compared the method by which patients were informed either in the patient admission area following patient admission by the same staff member (Group A) or in a separate room by another staff member (Group B). The consent decision was hypothetical in nature. Additionally, we evaluated if there was the need for additional time after the information session and before taking the consent decision. Data were collected during a structured interview based on questionnaires where participants reflected on the information and consent process they went through.ResultsQuestionnaire data were obtained from 157 participants in Group A and 106 participants in Group B. Overall, participants in both groups were satisfied with their experienced process and with the way information was provided. They reported that their (hypothetical) consent decision was freely made. Approximately half of the interested participants in Group B did not show up in the separate room, while all interested participants in Group A could be informed about the secondary use of their routine data and left-over samples. No participants, except for one in Group B, wanted to take extra time for their consent decision. The hypothetical consent rate for both routine data and left-over samples was very high in both groups.ConclusionsThe willingness to support medical research by allowing the use of routine data and left-over samples seems to be widespread among patients. Information concerning this secondary data use may be given by trained administrative staff immediately following patient admission. Patients mainly prefer making a consent decision directly after information is provided and discussed. Furthermore, less patients are informed when the process is organized in a separate room.

Using data to drive service improvement: false dawns and a promised land?

Increasing emphasis and expectation is being placed on the role of healthcare data in addressing the problems faced by the NHS. The ideal is to replace the current fragmented system of individual systems and registries with a universal, integrated data system that provides frontline staff with what they need while also allowing monitoring of services, intelligent population-based commissioning and the facilitation of quality improvement (QI) and research. With the recently published tender for the creation of a federated data platform (FDP) there is optimism that these aspirations are being addressed; however, concerns remain that the future use of healthcare data in the UK will not fulfil its potential if the current well-recognised shortcomings of existing systems and processes are not dealt with.

Data protection-compliant broad consent for secondary use of health care data and human biosamples for (bio)medical research: Towards a new German national standard

BackgroundThe secondary use of deidentified but not anonymized patient data is a promising approach for enabling precision medicine and learning health care systems. In most national jurisdictions (e.g., in Europe), this type of secondary use requires patient consent. While various ethical, legal, and technical analyses have stressed the opportunities and challenges for different types of consent over the past decade, no country has yet established a national consent standard accepted by the relevant authorities. MethodsA working group of the national Medical Informatics Initiative in Germany conducted a requirements analysis and developed a GDPR-compliant broad consent standard. The development included consensus procedures within the Medical Informatics Initiative, a documented consultation process with all relevant stakeholder groups and authorities, and the ultimate submission for approval via the national data protection authorities. ResultsThis paper presents the broad consent text together with a guidance document on mandatory safeguards for broad consent implementation. The mandatory safeguards comprise i) independent review of individual research projects, ii) organizational measures to protect patients from involuntary disclosure of protected information, and iii) comprehensive information for patients and public transparency. This paper further describes the key issues discussed with the relevant authorities, especially the position on additional or alternative consent approaches such as dynamic consent. DiscussionBoth the resulting broad consent text and the national consensus process are relevant for similar activities internationally. A key challenge of aligning consent documents with the various stakeholders was explaining and justifying the decision to use broad consent and the decision against using alternative models such as dynamic consent. Public transparency for all secondary use projects and their results emerged as a key factor in this justification. While currently largely limited to academic medicine in Germany, the first steps for extending this broad consent approach to wider areas of application, including smaller institutions and medical practices, are currently under consideration.

Trust and digital privacy in healthcare: a cross-sectional descriptive study of trust and attitudes towards uses of electronic health data among the general public in Sweden

BackgroundThe ability of healthcare to protect sensitive personal data in medical records and registers might influence public trust, which in turn might influence willingness to allow healthcare to use such data. The aim of this study was to examine how the general public’s trust relates to their attitudes towards uses of health data.MethodsA stratified sample from the general Swedish population received a questionnaire about their willingness to share health data. Respondents were also asked about their trust in the management and protection of electronic health data.ResultsA large majority (81.9%) of respondents revealed high levels of trust in the ability of healthcare to protect electronic patient data. Good health was associated with significantly higher levels of trust compared to bad health. Respondents with low levels of trust were significantly less willing to allow personal data to be used for different purposes and were more inclined to insist on being asked for permission beforehand. Those with low levels of trust also perceived risks of unauthorized access to personal data to be higher and the likely damage of such unauthorized access worse, compared to those with high levels of trust.ConclusionsTrust in the ability of healthcare to protect electronic health is generally high in Sweden. Those with higher levels of trust are more willing to let their data be used, including without informed consent. It thus seems crucial to promote trust in order to be able to reap the benefits that digitalization makes possible through increased access and use of data in healthcare.

Mental Health Surveillance at federal state level - Reporting on psychiatry in Bavaria.

In Germany, mental health reporting is organised at the federal, federal state and municipal level. At federal level, a number of concepts and approaches are implemented. In 2020 and 2021, in accordance with Article 4 of the Mental Health Assistance Act the first Bavarian Psychiatry Report was prepared. Important data bases include the billing and care data of Bavaria’s Association of Statutory Health Insurance Physicians and the administrative data of the Bavarian districts. The aim is to enhance coordination between these federal state projects and Mental Health Surveillance at national level, in particular regarding the use of health care data.

CASIDE: A data model for interoperable cancer survivorship information based on FHIR

Cancer survivorship has traditionally received little research attention although it is associated with a variety of long-term consequences and also many other comorbidities. There is an urgent need to increase research on this area, and the secondary use of healthcare data has the potential to provide valuable insights on survivors' health trajectories. However, cancer survivors' data is often stored in silos and collected inconsistently. In this study we present CASIDE, an interoperable data model for cancer survivorship information that aims to accelerate the secondary use of healthcare data and data sharing across institutions. It is designed to provide a holistic view of the cancer survivor, taking into account not just the clinical data but also the patient’s own perspective, and is built upon the emerging Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. Advantages of adopting FHIR and challenges in information modelling using this standard are discussed. CASIDE is a generalizable approach that is already being used as a support tool for the development of downstream applications to support clinical decision making and can contribute to translational collaborative research on cancer survivorship.

Hidden labour: the skilful work of clinical audit data collection and its implications for secondary use of data via integrated health IT

BackgroundSecondary use of data via integrated health information technology is fundamental to many healthcare policies and processes worldwide. However, repurposing data can be problematic and little research has been undertaken into the everyday practicalities of inter-system data sharing that helps explain why this is so, especially within (as opposed to between) organisations. In response, this article reports one of the most detailed empirical examinations undertaken to date of the work involved in repurposing healthcare data for National Clinical Audits.MethodsFifty-four semi-structured, qualitative interviews were carried out with staff in five English National Health Service hospitals about their audit work, including 20 staff involved substantively with audit data collection. In addition, ethnographic observations took place on wards, in ‘back offices’ and meetings (102 h). Findings were analysed thematically and synthesised in narratives.ResultsAlthough data were available within hospital applications for secondary use in some audit fields, which could, in theory, have been auto-populated, in practice staff regularly negotiated multiple, unintegrated systems to generate audit records. This work was complex and skilful, and involved cross-checking and double data entry, often using paper forms, to assure data quality and inform quality improvements.ConclusionsIf technology is to facilitate the secondary use of healthcare data, the skilled but largely hidden labour of those who collect and recontextualise those data must be recognised. Their detailed understandings of what it takes to produce high quality data in specific contexts should inform the further development of integrated systems within organisations.