Health Research Data Research Articles

The role of inequalities in managing symptoms of menstruation: harnessing shopping data to innovate female reproductive health research

Introduction & BackgroundMenstruation affects half the population, yet its patterns and management are greatly under-researched. A regular and functioning menstrual cycle is considered an important vital sign and menstrual-related issues can be strong indicators of both reproductive and wider health issues. This project explores a novel health data source - shopping data history - to study how individuals manage menstrual symptoms such as pain, intensity of flow, mental health, and other issues, and explore potential social inequalities in these management strategies. Objectives & ApproachWe present a conceptual framework of studying management of menstruation symptoms using shopping data. The core objectives of this research are to enhance our understanding of menstrual management strategies and potential inequalities in these whilst evaluating the utility and acceptability of shopping data for future female reproductive health research. Our research will focus on harnessing loyalty card data from UK supermarkets and pharmaceutical retailers to provide insights into the management of menstrual symptoms at a national level. We will study retail data to identify products and patterns of purchasing which may be relevant to menstrual management and conduct surveys for linkage with shopping data. The public will be consulted to investigate attitudes towards shopping data for health research and inform interpretations of patterns in the data. Relevance to Digital FootprintsThis project contributes to advancing of understanding of using digital data for health research on an important societal challenge. We investigate the practical applications for menstrual health and other female reproductive health issues, with scope to enact meaningful change. Conclusions & ImplicationsBy analysing shopping behaviour, combined with survey data and area-level socioeconomic data, we aim to identify regions of the UK and individual characteristics which influence the risk of experiencing menstrual symptoms and ability to manage these within a high-income context. Our research will contribute to understanding of menstrual management strategies for women and people who menstruate, and associated inequalities.

Development and use of a co-produced short mood survey to collect ground truth in digital footprints research

Introduction & BackgroundTo use digital footprint data for mental health and well-being research we often need to collect concurrent, high-quality measures of ground truth. Delivering frequent surveys to participants using an ecological momentary assessment (EMA) methodology is one way to collect such data. However, existing surveys tend to be long, not focused on momentary states or rely on rating images which are not platform agnostic. Here we present a five-item test-based survey designed with participants and validated for use in EMA studies to collect data about momentary changes in mood. We describe its methodological development and how it has been used to investigate music listening on Spotify as a digital footprint of mood. Objectives & ApproachThe survey is based on the circumplex model of affect. It was co-produced with a participant advisory group (N=5), who gave feedback on the length, content and delivery of the survey. It was then piloted in a group of N=98 participants to assess statistical validity, and congruence with the 20-item Positive and Negative Affect Schedule (PANAS). Following this it was delivered in a wider sample (N=150) four times a day over a two-week period using an EMA app on participant’s phones. Relevance to Digital FootprintsEMA is an increasingly popular method for collecting ground truth to support the interpretation of digital footprint data. This newly developed and tested mood survey offers an opportunity to reduce participant burden for collecting mood data in EMA studies which will support the collection of high quality and high time-resolution ground truth for digital footprints research. ResultsTogether with participants we selected four emotions across the axes of arousal and valence, as well as rumination which participants considered important in their music listening behaviors. Factor analysis of pilot data showed that the questions represented two factors of positive and negative affect. The ratings on a 0-10 scale of the emotions ‘cheerful’ and ‘relaxed’ explained 44% of the variance in positive affect, and ratings of ‘worried’, ‘sad’ and ‘frustrated’ explained 40% of the variance in negative affect. Delivery of the questionnaire in a wider student sample (N=150) four times per day for two weeks allowed for the opportunity to assess typical response rates in a realistic EMA setting. On average participants completed 3 out of the 4 surveys a day. Conclusions & ImplicationsThe co-created, short mood survey for the collection of ground truth in digital footprint studies was validated across two independent samples, and shown to allow for good response rates in a two week study. Future testing on wider samples will provide opportunities to validate the survey and assess its effectiveness across demographic groups and different sample types.

Development of a harmonized sociodemographic and clinical questionnaire for mental health research: A Delphi-method-based consensus recommendation.

Harmonized tools are essential for reliable data sharing and accurate identification of relevant factors in mental health research. The primary objective of this study was to create a harmonized questionnaire to collect demographic, clinical and behavioral data in diverse clinical trials in adult psychiatry. We conducted a literature review and examined 24 questionnaires used in previously published randomized controlled trials in psychiatry, identifying a total of 27 domains previously explored. Using a Delphi-method process, a task force team comprising experts in psychiatry, epidemiology and statistics selected 15 essential domains for inclusion in the final questionnaire. The final selection resulted in a concise set of 22 questions. These questions cover factors such as age, sex, gender, ancestry, education, living arrangement, employment status, home location, relationship status, and history of medical and mental illness. Behavioral factors like physical activity, diet, smoking, alcohol and illicit drug use were also included, along with one question addressing family history of mental illness. Income was excluded due to high confounding and redundancy, while language was included as a measure of migration status. The recommendation and adoption of this harmonized tool for the assessment of demographic, clinical and behavioral data in mental health research can enhance data consistency and enable comparability across clinical trials.

A Qualitative Study of Physicians' Views on the Reuse of Electronic Health Record Data for Secondary Analysis.

Electronic health records (EHRs) have become ubiquitous in clinical practice. Given the rich biomedical data captured for a large panel of patients, secondary analysis of these data for health research is also commonplace. Yet, there are many caveats to EHR data that the researchers must be aware of, such as the accuracy of and motive for documentation, and the reason for patients' visits to the clinic. The clinician-the author of the documentation-is thus central to the correct interpretation of EHR data for research purposes. In this study, I interviewed 11 physicians in various clinical specialties to bring attention to their view on the validity of research using EHR data. Qualitative, in-depth, one-on-one interviews were conducted with practicing physicians in inpatient and outpatient medicine. Content analysis using a data-driven, inductive approach to identify themes related to challenges and opportunities in the reuse of EHR data for secondary analysis generated seven themes. Themes that reflected challenges of EHRs for research included (1) audience, (2) accuracy of data, (3) availability of data, (4) documentation practices, and (5) representativeness. Themes that reflected opportunities of EHRs for research included (6) endorsement and (7) enablers. The greatest perceived barriers reflected the intended audience of the EHR, the interpretation and meaning of the data, and the quality of the data for research purposes. Physicians generally expressed more perceived challenges than opportunities in the reuse of EHR data for research purposes; however, they remained optimistic.

Prevention of stunting with nutrition and reproductive health education of adolescents in west Lombok, West Nusa Tenggara, Indonesia

The problem of stunting in Indonesia is a serious threat that requires appropriate handling. Basic Health Research data in 2018 shows that stunting cases in Indonesia are still relatively high, reaching 30.8%. Behavior change is one of the pillars of efforts to deal with malnutrition and stunting. Adolescent reproductive health is defined as a healthy condition in the system, function, and process of adolescent reproduction physically, mentally, and socio-culturally. The Community Service activities that will be carried out are a Community Partnership Program scheme focusing on service in the health sector which focuses on adolescent reproductive health. The targets of this activity are teachers and students of 1st State Senior High School, Gunungsari, Lombok, West of Nusa Tenggara. This Community Service aims to increase knowledge and implementation regarding strengthening character and leadership spirit and using technology wisely, increasing knowledge and skills about motor activities through the socialization of sports movements, anthropometric measurements related to adolescent reproductive readiness, and breast self-examination. The methods used are seminars, focus group discussions, and training.

The Royal Marsden BRIDgE TRE Transparency Project

BackgroundThe BRIDgE platform is the Royal Marsden’s Trusted Research environment, which aims to transform clinical practice and improve outcomes for patients by enabling data analytics and AI development using real-world cancer data within secure, collaborative, cloud-based workspaces. This project evaluated the BRIDgE website against the new UK Health Data Research UK Transparency Standards, leading to changes to implement the following: Open Access Application form and Guidance (Standard 1), Transparent Access Process and Criteria (Standard 2), Clear website navigation (Standard 3), Consider Target Audience (Standard 4), Regular Review of Website Content (Standard 5), and Transparency of Data Use and Auditing (Standard 6). Our primary aim was to improve the content and sign posting so that patients and researchers would be better informed, resulting in increased website traffic and requests via our Contact Us page. MethodsInformation about the transparency project and the updates to the website were presented to a patient panel for feedback and a leaflet was co-designed with patient representatives. ResultsChanges included a new BRIDgE home page, which was re-designed to make navigation simpler and clearer, improved signposting, so both patients and researchers were aware of the sections meant for their consumption, such as the new Researchers’ Frequently Asked Questions (FAQ) page, which contained detailed instructions on how to request data, the governance workflow and costing structure. Finally, we expanded the Research Projects and Publications page, and added a Case Study from one of the Researchers, detailing their personal experience on the platform. ConclusionsWe anticipate that the impact of this project will be that patients will be more informed about Trusted Research Environments in general and what BRIDgE specifically enables in terms of innovative research and data security, leading to greater assurance for patients that their data is being used securely for their benefit. Researchers will get the benefit of the new FAQ page, which includes a great deal more information than was previously available about the platform, the data access methods, and the governance processes. We envisage that this will lead to more traffic on the site and a greater number of requests for information and workspaces via the Contact Us page. Finally, the patient leaflet will be the first time that patients in our waiting areas will be able to read about research informatics at the Royal Marsden and the work of our data scientists, in paper form. The resources developed using the funding from the transparency project are the revamped BRIDgE website https://www.cancerbrc.org/BRIDgE and (soon to be published) patient leaflet.

Improving transparency of longitudinal health research: glossary, infographic and accessible study summaries

BackgroundLongitudinal studies collect information repeatedly about the same group of people, allowing for analyses of changes over time. They are vital in mental health research, as elsewhere. As longitudinal studies rely on the participation of patients and the public, their methods, purposes and results must be transparent and accessible. IntroductionMany UK longitudinal research studies with mental health data are indexed via the Catalogue of Mental Health Measures (‘Catalogue’), and organisations including DATAMIND provide broader information about mental health data research. However, the information on such platforms is primarily researcher-oriented, creating a barrier to its transparency and accessibility. Barriers can be alleviated by providing clear definitions of specialist terms, a transparent overview of longitudinal mental health research, and ‘bite-sized’ summaries of the Catalogue studies. MethodsThis project was co-designed and co-created by patient/public representatives from the DATAMIND Super Research Advisory Group (SRAG) and researchers. UK Health Data Research Alliance transparency standards were followed across the delivery of three outputs. (1) To provide clear definitions of specialist terms, SRAG members and researchers collected terms commonly used longitudinal research and researchers clarified definitions. Definitions were revised by SRAG members and terms were added to an existing data science glossary. (2) To create a transparent overview of longitudinal mental health research, the patient/public involvement (PPI) lead and SRAG co-applicant proposed content for an infographic about longitudinal research. The design was discussed with a graphic designer who created the infographic, and involved the PPI lead for the UK Longitudinal Linkage Collaboration. This was then revised iteratively for clarity, accessibility and diversity. (3) To generate accessible summaries of the Catalogue studies, psychology undergraduate students drafted summaries for an initial six studies, which were reviewed via a workshop led by the SRAG. Following revisions to the content and style, summaries were created for all 55+ studies on the Catalogue. Unfamiliar terms encountered during the process were also added to the glossary. ResultsThree new resources were created. (1) We developed a glossary of terms commonly used in longitudinal studies and research, to be incorporated into the DATAMIND glossary (https://datamind.org.uk/glossary/). (2) We created an infographic ‘storyboard’ to show how researchers, patients and the public can work together in the creation and curation of longitudinal research. The infographic illustrates the intertwined relationships between patients and the public, providing a transparent representation of challenges such as sharing studies, data access, patient benefit, and the importance and impact of public involvement. It illustrates many ways to find out about longitudinal research. (3) Accessible and transparent short summaries were created for all longitudinal studies in the Catalogue (https://www.cataloguementalhealth.ac.uk/). These provide clear and concise overviews, enough to capture the essence of each study and inform researchers and the public quickly and easily. ConclusionsCo-production supports the transparency of longitudinal research, and ensures resources designed and produced for the public have public input. Two generic information resources and one specific resource are presented. AcknowledgementsProject funded by HDR UK (HDRUK2023.0465). DATAMIND is funded by the Medical Research Council (MR/W014386/1). All research at the Department of Psychiatry in the University of Cambridge is supported by the NIHR Cambridge Biomedical Research Centre (NIHR203312) and the NIHR Applied Research Collaboration East of England; the views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

Improving Transparency of NHS Trust uses of data for Research Purposes

BackgroundIn 2022, the UK Health Data Research Alliance published a Data Transparency Standards white paper (UK Health Data Research Alliance, 2022). This guideline encourages organisations using health data for research to take an approach which creates increased transparency around how this data is utilised and what the proposed benefits of projects may be. The guidelines are split into six themed standards encouraging organisations to; publish their application forms and application process, have a clearly marked website which considers their target audience and is regularly reviewed, and to publish a register of projects which have used their data. IntroductionMFT CDSU operates a Safe Haven for research using health and social care data which includes a public panel for reviewing project applications. As such, it was felt that adopting the Data Transparency Standards would be a crucial step in furthering our public involvement and transparency of operations within the service. MethodsCDSU and RCD adapted the already existing MFT intranet site to be an outward-facing public website (Figure 1), hosted on the MFT Research and Innovation website and accessible for two main audiences; public citizens and researchers. Existing processes and descriptions were adapted to try and meet the Data Transparency Standards in the best-fit way, working within the constraints of existing Trust site infrastructure and publishing rules, and content was reviewed by the RCD. Agreed content and website structure was then sent to the CDSU Data Access Committee (DAC) for review and approval before publishing on the website. ResultsA public-facing website was published near the end of March 2024 with dedicated sections for CDSU workstreams (Figure 2) of Operational Data Science, Research Data and Clinical Trials Recruitment and a direct means to contact CDSU. The DAC has its own dedicated tab (Figure 3) explaining their role in reviewing projects, listing all projects which have received approvals so far. ConclusionsThe website is published (https://research.cmft.nhs.uk/innovation-at-mft/manchester-clinical-data-science-unit) but will still require some further edits to the content. There is also a planned change for the MFT content management site so there may be some temporary disruption while this move is enabled. There is an existing schedule in place to review the site content for relevance every 6 months. There are constraints on content and structure due to the MFT comms rules on publications and the content management site MFT use. This meant that we are unable to easily meet certain criteria in the Data Transparency Standards, such as structuring the content in a particular way or providing a downloadable copy of files. The CDSU website will be a useful engagement tool, encouraging more interest in the service and types of project undertaken and we are working to make more information available. References UK Health Data Research Alliance (2022), Improving transparency in the use of health data for research: Recommendations for a data use register standard, https://zenodo.org/records/5902743#.ZDgTHcrMKUn MFT Clinical Data Science Unit (2024), https://research.cmft.nhs.uk/innovation-at-mft/manchester-clinical-data-science-unit

Understanding Longitudinal Population Study Data and the Law

BackgroundUK Longitudinal Linkage Collaboration (UK LLC) is the national Trusted Research Environment for the UK's longitudinal studies. The need for a clear way to communicate Longitudinal Population Study (LPS) participants’ rights was identified through public contributor consultations. UK LLC gathered public views to inform meaningful discussion with NHS England, the National Data Guardian’s Office, and the Health Research Authority to develop a new framework for agreeing consistency in assessment of the legal basis for linking participant self-reported data to participants' health records. The consultation flagged that the legislation around LPS data is complex, confusing, and often inaccessible. This means that it may prove difficult for LPS participants to fully understand who is allowed to access their data, for what purposes, under what circumstances and what their rights are. IntroductionThe legal basis for using LPS data is complex. Of particular importance are the UK GDPR (General Data Protection Regulations), Common Law Duty of Confidentiality, Digital Economy Act (DEA) 2017 and Section 251 of the NHS Act 2016. Our vision was to produce transparency materials to help LPS participants understand LPS data and the law. MethodsWe surveyed public contributors from UK LLC, Health Data Research UK and DATAMIND to establish current understanding. We worked in partnership with UK LLC’s Public Advisory Group (PAG) and external organisations to produce a series of infographics (over time also available in audio, BSL and additional languages) to reach as wide an audience as possible. We collaborated with DATAMIND throughout the project sharing insights and ideas. ResultsA total of 56 people participated in the survey, most of whom lived in England: 30% were LPS participants; 55% were aged 55 and over; and 18% identified as belonging to an ethnic minority group. Survey results showed that the levels of awareness of the laws/legal principles relating to the use of LPS data is generally low. The DEA was least well-known, with 11% of people aware of this legislation. The most well-known among the infographic topics was GDPR, with 88% awareness. We co-developed key messages for LPS participants on what they should be aware of as individuals, including what they should expect from their LPS. This was not a straightforward process due to the exemptions and conditions under each law/legal principle. This led to focus on highlighting the practical implications for participants rather than explaining the laws/legal principles. Across the series, participants are directed to official organisations for further information. ConclusionsThis series of transparency materials provides a more accessible and easy-to-understand way for LPS participants to fully understand who is allowed to access their data, for what purposes, under what circumstances and what their rights are.

To share or not to share – understanding individuals’ willingness to share biomarkers, sensor data, and medical records

ABSTRACT Technological advances in the recent past made it possible for researchers to collect and analyze large amounts of health data at unprecedented scale and speed. For example, fitness trackers and smartwatches produce steady flows of information on individuals’ health. Biomarker data and medical records allow to study individuals at new levels of granularity. The COVID-19 pandemic has highlighted that access to such data for health research and evidence-based public policy decision-making is essential. However, having access to data depends on individuals’ willingness to share their data with others. In this paper, we analyze the factors that may affect the probability of individuals to share their biomarker, health, and sensor data using German survey data and a survey experimental vignette design. We study the impact of data type, recipient, and research purpose on respondents’ willingness to share their data as well as the effects of respondents’ own medical and data sharing history. Overall, participants’ willingness to share biomarker data was higher than the willingness to share other data types. Moreover, those who had shared data before were more willing to do so again. In addition, natural language processing analysis of textual responses capturing respondents’ motives to share their data shows that individuals do understand how valuable their data is for researchers. However, results also underscore that addressing concerns about the protection of data need to be taken seriously. Emphasizing the value of data shared for research and their purpose may help to increase trust and willingness to share data.

Cross-jurisdictional Data Transfer in Health Research: Stakeholder Perceptions on the Role of Law

Large data-intensive health research programmes benefit from collaboration amongst researchers who may be located in different institutions and international contexts. However, complexities in navigating privacy frameworks and data protection laws across various jurisdictions pose significant challenges to researchers seeking to share or transfer data outside of institutional boundaries. Research on the awareness of data protection and privacy laws amongst stakeholders is limited. Our qualitative study, drawn from a larger project in Singapore, revealed insights into stakeholders’ perceptions of the role of law in cross-national health data research. Stakeholders in our study demonstrated a range of perceptions regarding the role of data protection law in governing the collection and transfer of health data for research. The main criticisms included inadequate legal protection to data and lack of uniformed data protection standards. Despite these criticisms, participants recognised the importance of data protection law in supporting cross-border data transfers and proposed measures to improve perceived limitations of existing laws. These measures include strengthening existing legal framework, establishing contractual agreements and imposing severe punishments for data misuse.

Risk Factor Analysis for Stroke Incidence in North Sulawesi: Based on the 2018 Indonesia Basic Health Research

Stroke is a serious public health issue and the main cause of disability and death after ischemic heart disease. Every year, 12.2 million individuals worldwide suffer from a stroke, which results in 6.5 million deaths. There has been an increasing incidence of stroke in Indonesia, including in North Sulawesi. This study aims to examine the risk factors for stroke incidence in North Sulawesi in a population aged ≥35 years based on the 2018 Indonesia Basic Health Research data. This quantitative research was an analytical observational study with a cross-sectional design. The Chi-square test and multiple logistic regression were performed during data analysis involving 7,111 respondents. The multivariate analysis results showed that hypertension (p=0.000; AOR 8.739; 95% CI 5.758-13.263), physical activity (p=0.000; AOR 2.771; 95% CI 1.944-3.948), gender (p=0.000; AOR 2.047; 95% CI 1.388-3.017), heart disease (p=0.015; AOR 1.919; 95% CI 1.133-3.250), age (p=0.008; AOR 1.669; 95% CI 1.144-2.434), occupation (p=0.008; AOR 1.693; 95% CI 1.145-2.504), and fatty foods consumption (p=0.023; AOR 0.603; 95% CI 0.390-0.932) had a significant correlation with stroke incidence in this study. The main finding of this study shows that hypertension is the most influential risk factor for stroke incidence in a population aged ≥35 years in North Sulawesi. Regular blood pressure screenings are needed as an early hypertension detection effort to prevent stroke incidence.

Determinant Factors of The Incidence of Low Birth Weight in Central Java Province: Analysis of 2018 Basic Health Research Data

Determinant Factors of The Incidence of Low Birth Weight in Central Java Province: Analysis of 2018 Basic Health Research Data

OA42 Effect of intra-articular corticosteroid injections for osteoarthritis on subsequent use of pain medications: an instrumental variable and propensity score analysis

Abstract Background/Aims Intra-articular corticosteroid injections (IACI) are recommended in the UK by NICE as an adjunctive treatment for uncontrolled pain from osteoarthritis (OA). NICE guidance states there is no evidence for therapeutic benefit lasting beyond three months, and that more evidence is needed on effectiveness at non-knee joints. We therefore aimed to assess the longer-term effect of IACI use on pain medication prescriptions among people with hand, hip, knee or shoulder OA. Methods We conducted a cohort study using UK primary care (CPRD GOLD) data for patients aged ≥20 years with a first diagnosis of OA during 2005-2019, excluding those with prior orthopaedic surgery referral or OA diagnosed at multiple joints. Exposure to IACI was defined using Read codes. The primary outcome was incident prescribing of pain medication: oral non-steroidal anti-inflammatory drugs (NSAIDs), opioids, oral corticosteroids, paracetamol, partial opioids, and topical NSAIDs. In main analyses, an instrumental variable (IV) approach was used. Index date was six months after OA diagnosis date and IV was defined as practice preference for IACI use in the year prior to index date (single and recurrent use considered separately). Outcomes were measured over five years from index date. Covariate balance was assessed, and two-step Poisson regression used where assumptions met. In secondary analyses, propensity score (PS) matching was carried out and time-varying exposure Cox models used to estimate treatment effect. Results Of 181,818 eligible patients, 92,157 (50.7%) were retained in IV analyses of single IACI and 89,103 (49.0%) of repeat IACI. Covariates were well balanced (SMD ≤0.1) across IV groups for hand (single IACI only) and knee OA, but not hip or shoulder OA. In IV analyses of hand OA, single IACI was associated with lower 5-year cumulative incidence of several pain medications including oral corticosteroids (relative risk [RR] 0.27 [95% CI 0.10, 0.76], paracetamol (RR 0.27 [0.09, 0.78] and partial opioids (RR 0.24 [0.10, 0.60]). IACI for knee OA was associated with lower 5-year cumulative incidence of most pain medications, e.g., for partial opioids a RR 0.46 [95% CI 0.34, 0.61] and RR 0.33 [0.21, 0.51] for single and recurrent IACI, respectively. Most PS matched analyses had >20,000 included patients (all joints combined), with covariates well balanced across IACI exposure status. PS matching confirmed a reduction in incidence of several pain medications associated with single IACI, e.g., lower incidence of partial opioids following IACI for any of hand, hip, knee or shoulder OA. Conclusion Our main findings suggest IACI use for hand or knee OA may reduce subsequent need for analgesics. Among knee OA patients, generally larger reductions were observed following recurrent than single IACI. In secondary analyses, single IACI for hand, hip, knee or shoulder OA was associated with lower subsequent use of partial opioids. Disclosure S. Hawley: None. A. Prats-Uribe: Grants/research support; European Medicines Agency. G. Matharu: Grants/research support; National Institute of Health and Care Research, Academy of Medical Sciences. A. Delmestri: None. D. Prieto-Alhambra: Consultancies; AstraZeneca, UCB Biopharma. Grants/research support; European Medicines Agency, Innovative Medicines Initiative, Amgen, Chiesi-Taylor, Lilly, Janssen, Novartis, UCB Biopharma. Other; Amgen, Astrellas, Janssen, Synapse Management Partners, UCB Biopharma. A. Judge: Grants/research support; National Institute of Health and Care Research, Health Data Research UK, Versus Arthritis, Healthcare Quality Improvement Partnership (HQIP), Royal College of Physicians (RCP), Tommy's, The Health Foundation. M. Whitehouse: Royalties; Taylor Francis. Member of speakers’ bureau; Heraeus. Grants/research support; National Institute of Health and Care Research, Healthcare Quality Improvement Partnership (HQIP), Ceramtec.

European Health Data Space – Is the Proposed Certification System Effective against Cyber Threats?

Abstract The proposal for a European Health Data Space aims at creating a common space where individuals may control their health data in a trusted and secure way. The objective is not only improving healthcare delivery, but also enhancing the opportunities to use health data for research and innovation. To achieve these results, the proposal implements a mandatory self-certification scheme for European health records systems as well as for wellness devices and applications, setting up essential requirements related to interoperability and security. Although this is the first intervention that sets a horizontal framework that is mandatory for all Member States, the security requirements that are included in the legislative proposal are not sufficiently detailed and comprehensive. Given that cyberthreats are increasing and security incidents affecting health data may potentially have an impact on the lives of patients, it is important that cybersecurity measures are adopted and implemented in the most effective way. The paper will analyse the European Health Data Space proposal pointing to the open issues and doubts that may be emerging and it will compare them with the proposed Cyber Resilience Act, identifying the issues that may be solved thanks to this horizontal regulation and the ones that instead remain open.

Health data social licence: An inclusive process to learn more about the perspectives of experienced public and patient advisors

The term "social licence" has been used to describe which uses and users of health data the public supports - and under what conditions. From November 2022 to January 2023, Health Data Research Network Canada was funded by the Public Health Agency of Canada to explore whether there was consensus among experienced public and patient advisors on: (i) uses of health data that all members supported or opposed and (ii) what constitutes an essential requirement for a health data use or user to be within social licence. The project was conducted in English and French in collaboration with the Interdisciplinary Research Group in Health Informatics (GRIIS) at the University of Sherbrooke. It involved 20 public/patient advisor "participants" and an additional 13 public/patient advisors who served as peer-reviewers, all of whom had prior experience working in a health-related field and/or with health data. The process followed inclusive design principles in that it captured views held by the majority and minority of participants, including views expressed by only one or two participants. After two 2-hour facilitated sessions, participants agreed that it is within social licence for health data to be used (i) by healthcare practitioners to improve patient care, (ii) by governments and administrators to improve the health system, and (iii) by university-based researchers to understand disease and well-being. There was consensus opposition to (i) an individual or organisation selling someone else's identified health data and (ii) health data being used for a purpose that has no public or societal benefit. There was no consensus about what constitutes an essential requirement for a use or users of health data to be with social licence. The results of the process have been published in a non-peer-reviewed report co-authored with participants. This paper has been co-authored with a subset of the participants and peer-reviewers to present a high-level summary of the findings, methodological details, and templates to enable other groups to adapt the process to their own settings. It also presents the results of an anonymous evaluation of the process using the Public and Patient Engagement Evaluation Tool (PPEET), which were mostly positive and identified some areas for improvement.

Creating a next-generation phenotype library: the health data research UK Phenotype Library.

To enable reproducible research at scale by creating a platform that enables health data users to find, access, curate, and re-use electronic health record phenotyping algorithms. We undertook a structured approach to identifying requirements for a phenotype algorithm platform by engaging with key stakeholders. User experience analysis was used to inform the design, which we implemented as a web application featuring a novel metadata standard for defining phenotyping algorithms, access via Application Programming Interface (API), support for computable data flows, and version control. The application has creation and editing functionality, enabling researchers to submit phenotypes directly. We created and launched the Phenotype Library in October 2021. The platform currently hosts 1049 phenotype definitions defined against 40 health data sources and >200K terms across 16 medical ontologies. We present several case studies demonstrating its utility for supporting and enabling research: the library hosts curated phenotype collections for the BREATHE respiratory health research hub and the Adolescent Mental Health Data Platform, and it is supporting the development of an informatics tool to generate clinical evidence for clinical guideline development groups. This platform makes an impact by being open to all health data users and accepting all appropriate content, as well as implementing key features that have not been widely available, including managing structured metadata, access via an API, and support for computable phenotypes. We have created the first openly available, programmatically accessible resource enabling the global health research community to store and manage phenotyping algorithms. Removing barriers to describing, sharing, and computing phenotypes will help unleash the potential benefit of health data for patients and the public.

Foresight—a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study

An electronic health record (EHR) holds detailed longitudinal information about a patient's health status and general clinical history, a large portion of which is stored as unstructured, free text. Existing approaches to model a patient's trajectory focus mostly on structured data and a subset of single-domain outcomes. This study aims to evaluate the effectiveness of Foresight, a generative transformer in temporal modelling of patient data, integrating both free text and structured formats, to predict a diverse array of future medical outcomes, such as disorders, substances (eg, to do with medicines, allergies, or poisonings), procedures, and findings (eg, relating to observations, judgements, or assessments). Foresight is a novel transformer-based pipeline that uses named entity recognition and linking tools to convert EHR document text into structured, coded concepts, followed by providing probabilistic forecasts for future medical events, such as disorders, substances, procedures, and findings. The Foresight pipeline has four main components: (1) CogStack (data retrieval and preprocessing); (2) the Medical Concept Annotation Toolkit (structuring of the free-text information from EHRs); (3) Foresight Core (deep-learning model for biomedical concept modelling); and (4) the Foresight web application. We processed the entire free-text portion from three different hospital datasets (King's College Hospital [KCH], South London and Maudsley [SLaM], and the US Medical Information Mart for Intensive Care III [MIMIC-III]), resulting in information from 811 336 patients and covering both physical and mental health institutions. We measured the performance of models using custom metrics derived from precision and recall. Foresight achieved a precision@10 (ie, of 10 forecasted candidates, at least one is correct) of 0·68 (SD 0·0027) for the KCH dataset, 0·76 (0·0032) for the SLaM dataset, and 0·88 (0·0018) for the MIMIC-III dataset, for forecasting the next new disorder in a patient timeline. Foresight also achieved a precision@10 value of 0·80 (0·0013) for the KCH dataset, 0·81 (0·0026) for the SLaM dataset, and 0·91 (0·0011) for the MIMIC-III dataset, for forecasting the next new biomedical concept. In addition, Foresight was validated on 34 synthetic patient timelines by five clinicians and achieved a relevancy of 33 (97% [95% CI 91-100]) of 34 for the top forecasted candidate disorder. As a generative model, Foresight can forecast follow-on biomedical concepts for as many steps as required. Foresight is a general-purpose model for biomedical concept modelling that can be used for real-world risk forecasting, virtual trials, and clinical research to study the progression of disorders, to simulate interventions and counterfactuals, and for educational purposes. National Health Service Artificial Intelligence Laboratory, National Institute for Health and Care Research Biomedical Research Centre, and Health Data Research UK.

Hubungan Tingkat Pengetahuan dan Sikap dalam Upaya Menjaga Kesehatan Gigi dan Mulut pada Wali Murid TK di Kecamatan Jelbuk Kabupaten Jember

Based on Basic Health Research Data (RISKESDAS) in 2018, the number of dental and oral diseases in Indonesia was 57.6% while the number of visits to the dental clinic was only 45.3%. As a result, in order to avoid disease, guardians must understand and apply efforts to maintain dental and oral health from an early age. These efforts can be influenced by the level of knowledge and the level of individual attitudes. The data is in line with the condition of Jelbuk District, Jember Regency, in 2020 the total visits to the dental clinic are still relatively low compared to existing dental and oral health cases. The aim of this research is to determine the level of knowledge, the level of attitude and analyzing the relationship between the level of knowledge and the level of attitude in an effort to maintain dental and oral health in the kindergarten guardians in Jelbuk District, Jember Regency. This research used analytic observational method with a cross sectional design. There are 3 samples in this study including Dharma Wanita Kindergarten, Al Baiturrahmah Kindergarten, and Gemilang Kindergarten. The data obtained were analyzed by the Kendall tau correlation test. The characteristics of the respondents include the average gender of women aged 20-30 years with the latest education level of Junior High school and Senior High school and the majority work as housewives. The level of knowledge and level of attitude of respondents in an effort to maintain dental and oral health is in the good category. The level of knowledge and level of attitude in an effort to maintain dental and oral health for the guardians of kindergarten students in Jelbuk District, Jember Regency are mostly in the good category and there are some belonging to the less category and the relationship between the level of knowledge and attitude is significant, strong and unidirectional.

Considerations for the use of biochemical laboratory registry data in clinical and public health research

ObjectivesTo inform researchers of central considerations and limitations when applying biochemical laboratory-generated registry data in clinical and public health research. Study Design and SettingAfter review of literature on registry-based studies and the utilization of clinical laboratory registry data, relevant paragraphs and their applicability toward the creation of considerations for the use of biochemical registry data in research were evaluated. This led to the creation of an initial ten considerations. These were elaborated, edited, and merged after several read-throughs by all authors and discussed thoroughly under influence by the authors’ personal experiences with laboratory databases and research registries in Denmark, leading to the formulation of five central considerations with corresponding items and illustrative examples. ResultsWe recommend that the following considerations should be addressed in studies relying on biochemical laboratory-generated registry data: why are biochemical laboratory data relevant to examine the hypothesis, and how were the variable(s) utilized in the study? What were the primary indications for specimen collection in the study population of interest? Were there any pre-analytical circumstances that could influence the test results? Are data comparable between producing laboratories and within the single laboratory over time? Is the database representative in terms of completeness of study populations and key variables? ConclusionIt is crucial to address key errors in laboratory registry data and acknowledge potential limitations.