Data Access Process Research Articles

Implementing a streamlined data access governance process for the release of routinely collected electronic health record data for research

ObjectivesIn Australia, there are no standardised processes for the release of Electronic Health Record (EHR) data for research. We describe our streamlined ethics and data access governance framework for the release of EHR data for research. ApproachIn consultation with our academic and health service partner organisations and with reference to national and international standards, we developed a process to safely and efficiently release EHR data for research. The Five Safes Framework guided our processes ensuring: safe people; safe projects; safe settings; safe data; and safe outputs. Piloting of processes has commenced. ResultsStreamlined data access and release processes acceptable to all stakeholders were implemented using an online system. Independent researcher and consumer review of an Expression of Interest, followed by ethics review/approval from the health service research office ensures projects are methodologically and ethically sound. Completion of a detailed technical assessment form, implementation of a signed data use agreement and release of de-identified data to a secure e-research environment promotes safe data and settings. Constraints around publication are enforced via pre-publication review ensuring safe outputs. Nine projects are in process using our system with an average of 4 days for EOI review and 6 days for TAF review. ConclusionWe have established a streamlined data access pathway to minimise duplication of effort and allow timely and secure access to EHR research data. We have built in efficiencies and promoted a cultural shift for clinicians who have previously not had data access processes governed in this way.

Balancing constraints and requirements in an application process

ObjectivesDeveloping a rigorous application process for linked data within the UK Longitudinal Linkage Collaboration’s Trusted Research Environment (TRE) included balancing the requirements of >20 longitudinal studies and several data providers with the need to provision data to researchers in a safe, ethical and efficient manner. ApproachUK LLC was commissioned as a resource to enable the investigation of COVID-19 questions: a secure setting where longitudinal population studies (LPS) can be linked efficiently to regularly refreshed NHS electronic health records, and then accessed by researchers. UK LLC received funding to continue as a resource for any research in public good and to link to the administrative records (education, occupation, tax and benefits). To accommodate the constraints imposed by a new set of data controllers and to account for wide variety of proposals expected, we expanded our data access process. ResultsUK LLC has a three-stage application and review process. The addition of administrative data meant that there is additional review for those applications requesting that data (Stage 4) and need to align processes with the UK Statistics Authority. There is also need to review complexity of the data requests and ethical implications of any application to access the data. We have developed an ethics decision tree to help guide the decision making around ethics requirements. ConclusionOur process is evolving as we are trying to meet the challenge of balancing the needs of >20 studies, stakeholders, applicants, and participant/public contributors, to create a process that can handle complex needs and requirements.

Barriers and enablers to secondary use of multi-regional linked administrative health data for three distinct user groups: academic researchers, health-system knowledge users, and private sector researchers

Objective and ApproachWe analyzed barriers and enablers to accessing pan-Canadian health sector data and data analytic services for three distinct user groups: 1) academic researchers, 2) health-system knowledge users (KUs), and 3) private sector researchers. Specifically, we a) conducted a legislative and policy scan regarding use of health administrative data for research, quality improvement, and health system management and b) systematically consulted with data centre directors and staff, privacy and legal experts, knowledge users (KUs), private sector entities, and university and government officials. ResultsKUs and private sector organizations face unique barriers because structures and regulations related to data access and use are set at multiple university and government institutions and are primarily designed for academic research. Additionally, data repositories often have specific policy/legislative barriers to working with KUs and/or private sector researchers. However, all groups face common issues including variations in regional regulations and policies making harmonized and streamlined processes challenging; lengthy data access and ethics review processes; and regional variations in data availability. Enablers included diverse expertise and initiatives across Canada such as: initiatives to streamline ethics reviews for multi-regional research, expand data holdings, increase standardization and harmonization, and implement systems for federated analyses. ConclusionsAccess to health system data and analytics in Canada varies by user group and across regions. Although each user group faces unique challenges, they also all have many barriers and enablers in common. ImplicationsImproving health system data access for one use group has the potential to benefit the others.

Development of a dictionary of information items inspired by common data models to support health research data access requests

A network of organizations collaborates to provide services to facilitate multi-regional research across Canada. To streamline the data access process, the network is developing a dictionary of information items (InfoItems), providing a label and definition that represent a semantic sourced from an ontology (e.g., “human birth date” from a demography ontology). This allows for a standardized and shareable means to express data requirements. Inspired by health-research common data models (CDMs) like those from the Observational Medical Outcomes Partnership (OMOP) and the Canadian Network for Observational Drug Effects (CNODES), approximately 60 InfoItems were developed by the network. As a pilot exercise, four data centres mapped their data assets to the InfoItems to ensure they are relevant to the Canadian health data context. This has laid the foundation for InfoItems as a basic data harmonization mechanism. The new InfoItems-based data dictionary promotes the standardization of data asset contents across the network’s data centres. Researchers can use the dictionary to specify a project’s data requirements, establishing details like data availability across multiple regions, for inclusion in their data access request. The InfoItems dictionary is pivotal in simplifying data access requests, promoting multi-regional research in Canada. This resource can simultaneously safeguard the quality of analytical results and optimize data extraction into existing data models (e.g., health-research CDMs). Ongoing improvements in this area aim to enhance user experience and facilitate quality research.

Development of a framework to facilitate a data assembly plan for multi-regional research

A network of organizations works together to facilitate multi-regional research across Canada. This network is streamlining the traditionally burdensome data access process, a major part of which is a project’s data assembly plan (DAP). A framework is proposed for the development of a DAP usable by researchers and multiple data centres across Canada. The network of 13 provincial/territorial and pan-Canadian data centres collaborated to understand variations in data request processes and local requirements. During this collaboration, partners used an iterative approach to review local forms, processes, and undertake consultations with the research community, and to identify critical components of the DAP. In April 2022, the network launched the centrally provisioned, standardized DAP form, which to date has been deployed by approximately five projects. Users have found the DAP’s unique aggregation and documentation capabilities particularly helpful. Overall, the preliminary feedback from researchers has been positive. The DAP has allowed aggregation of specific details about a project’s data requirements: cohort definition(s), data extraction(s) and analytical plans, in a single unified form. The DAP is an important component in streamlining the process for requesting data from multiple provinces/territories, organizations, and data sources. The DAP has ensured consistency across the network’s data centres that are providing data, supporting data linkage, and helping safeguard the quality of analytical results. Further process improvements are anticipated to address user experience feedback and to promote quality research.

Robust Left-Right Hashing Scheme for Ubiquitous Computing

Ubiquitous computing systems possess the capability to collect and process data, which is subsequently shared with other devices. These systems encounter resource challenges such as memory constraints, processor speed limitations, power consumption considerations, and the availability of data storage. Therefore, maintaining data access and query processing speed in ubiquitous computing is challenging. Hashing is crucial to search operations and has caught the interest of many researchers. Several hashing techniques have been proposed and Cuckoo Hashing is found efficient to use in several applications. There are two variants of Cuckoo Hashing: Parallel Cuckoo Hashing and Sequential Cuckoo Hashing. Cuckoo Hashing suffers from challenges like high insertion latency, inefficient memory usage, and data migration. This paper proposes two hashing schemes: Left-Right Hashing and Robust Left-Right Hashing that successfully address and solve the major challenges of Sequential Cuckoo Hashing. The proposed schemes adopt the Combinatorial Hashing technique after modification and use this with a new collision resolution technique called Left-Right Random Probing. Left-Right Random Probing is a variant of random probing and uses prime numbers and Fibonacci numbers. In addition, this paper proposes a new performance indicator, degree of dexterity to estimate the performance of hashing techniques. Sequential Cuckoo Hashing suffers from hidden switching costs which are identified and its estimation is given by a new performance indicator called, T.R.C./Key. Performance of Sequential Cuckoo Hashing is order dependent.

An audio-visual resource to improve transparency in SAIL Databank’s data access process.

BackgroundSince 2007, SAIL Databank has been entrusted with anonymised health and administrative data for the population of Wales. This includes ~85% of primary and 100% secondary care health records, and a range of administrative data that includes education, employment, environment, housing, justice and social care data. This data is accessible to approved researchers who can demonstrate positive societal impact from its use. IntroductionIt has always been vital for SAIL Databank to build and maintain extremely high levels of trust amongst its stakeholders; data users, data providers and the public who are represented in the anonymised datasets. This trust has been earned through a robust range of technical, physical and procedural safeguards known as SAIL’s ‘privacy-by-design’. Public-facing information has been vital to maintain trust through transparency and manifests in SAIL’s data use register, publications register, and clear information offered via its website. This work represents the next evolution in SAIL’s commitment to transparency in creating an audio-visual representation of its data access process. Method Ensuring current available information on SAIL’s public facing website was clear and accessible through consultation with SAIL’s public involvement panel – The Consumer Panel. Streamlining and presenting this information based on Consumer Panel feedback. Maintaining SAIL’s commitment to Welsh language standards by translating this information. Consultation with colleagues and Swansea University procurement to identify a suitable creative agency to take forward the idea of a data access process animated video. Communicating requirements and providing briefing documents to the selected creative agency, Buffoon Media. Reviewing potential voiceovers for narration of animated video to ensure an accessible tone, pace and dual language delivery. Receipt of completed animated video placed alongside corresponding data access process text on SAIL’s website. ResultsProduction of an audio-visual resource that improves transparency around SAIL’s data access process and compliments its existing process guidance. This resource is freely and publicly accessible via its website, including components such as: Accessible design colours, fonts and presentation in keeping with SAIL’s existing brand. Use of images, graphics and animation that bring the process to life. A professional and accessible voice-over audio explaining each element within the process. A bi-lingual voice-over that recognises Wales’ large number of Welsh language speakers. Resource can be found at: https://saildatabank.com/data/apply-to-work-with-the-data/ ConclusionBuilding on SAIL’s commitment to trust and transparency since inception its anticipated that this new video resource will improve transparency for all of SAIL’s stakeholders in understanding and engaging with SAIL’s data access process.

Generation Scotland – Transparency in the data access process

BackgroundGeneration Scotland (GS) is large family-based cohort study established as a resource for research into the genetic and environmental determinants of physical and mental health. Participants completed a baseline questionnaire and clinic visit in 2006-2011. 24,084 Participants 5,501 Families NHS data linkage 22,402 (93%) Genotype array data 20,026 (83%) DNA methylation data 18,876 (78%) In 2019 funding was obtained to expand the existing GS cohort. By 2025 NextGenScot aims to: Recruit 20,000 new participants online Expand eligibility to 12-17 year olds Collect saliva samples by post for genotyping Linkage to NHS and other administrative data Details on how to join at www.gen.scot Participants consented to linkage to NHS Scotland medical records which offer longitudinal phenotype information. Linkage is conducted using the Community Health Index (CHI). IntroductionGS receives 30-40 requests for access to data and/or samples every year, and has been included in over 380 publications. Research proposals are subject to review by the GS Access Committee. Details of the application process terms and conditions for access are available on the GS website, and now on the new research access website. The previous GS access process was based on an application form in Word, downloaded from the main GS website. We are replacing this with a new online research access system, adhering to transparency standards1, helped by HDR Alliance Transparency funding. After researchers publish their results, a link to the publication and a lay summary is currently posted on the GS website, with a spreadsheet listing papers. We will now make this information available and searchable for researchers, participants and the public on the new research access website. MethodsWe are developing a website, using in-house staff, with HDR Alliance Transparency contributing to their salaries. The system coding uses Django (a Python tool) linked to a MySQL database, a platform widely used for such projects, enabling faster development in a secure environment. Transparent access to GS data for registered users View summary of data available Query the summary data to see if it fits research requirements Select data requested from data dictionaries Get a detailed quote for access charges Complete application form showing the project complies with the Five Safes2 Upload supporting documentation (e.g. protocol, DPIA, ethics, etc) Track progress of their application review, approval and delivery Researchers will be required to submit a lay summary of their application GS participants, researchers and the public can view: List of approved applications with lay summaries Summaries of ongoing projects which will link to eventual publications Searchable list of publications ResultThe new system is undergoing internal testing, using data imported from previous and ongoing access requests (May 2024). We will then pilot it with selected external researchers and GS participants (June 2024), with a plan to launch it for public access in July/August 2024. The GS Access Committee and admin team will be able to streamline the review and approval process, giving an improved turnaround time. ConclusionsWe were already planning to develop a new online application system, but the Transparency grant funding has enabled us to extend the functionality beyond a simple form-filling system. The new access website will give researchers more information about the application process, the data and samples available, see what other research has been approved in their area of interest, and track the progress of their project from enquiry through to publication. By adding a participant/public access area, with lay summaries of projects and publications, GS participants will be able to see how their data is being used for public benefit, as can potential new volunteers or other interested parties. NotesThe URL for the new website is www.gsaccess.orgThe main GS website is at www.generationscotland.org References Transparency Standards https://zenodo.org/record/8262453 Five Safes https://ukdataservice.ac.uk/help/secure-lab/what-is-the-five-safes-framework/

Skylark Wiki: Accessing research data of the MRC National Survey of Health and Development

Background & IntroductionThe Medical Research Council National Survey of Health and Development (NSHD) is the oldest and longest-running of the British birth cohort studies. In 2018 we launched the Skylark Wiki, a central metadata repository and the first port of call for any data sharing queries. In 2023 we utilised the HDRUK funding initiative to work with our advisory group and research community to improve the transparency of our data access process and make the content more accessible. MethodsWe conducted a focus group session with the NSHD Participant Advisory Panel to understand their views on the data sharing process and whether the information we provided them, sufficiently explained how their data are shared. We also sent out a questionnaire to all Skylark Users to identify areas of improvement. Lastly, we undertook an audit of the website’s content and used Google Analytics to see how Users navigated across the site. Combining all this information we identified areas requiring improvements, from the point of view of our stakeholders, and comparing these to the requirements indicated in the HDRUK Transparency Standards we mapped out updates to the Skylark Wiki. The work was carried out by an external agency (Aubergine262 Ltd). ResultsTo increase transparency and searchability, we improved the flow diagram of the data sharing process to include links to the relevant web pages. We also created guidance to explain why the information in the data request application form is being asked. As feedback from Skylark Users suggested difficulties in finding the required information, the navigation has been updated. We have also changed the layout of the front page to include navigation boxes that takes users straight to the content. The NSHD Advisory Panel reinforced the notion of trust that study participants place in the study and its approach to data sharing. They confirmed the information provided on data sharing was adequate and appreciated that this information was placed on the main study website (https://nshd.mrc.ac.uk/) for their benefit. Initial feedback from Users indicates that it is easier to find information on the website. We will keep monitoring access to the website, the number of queries, and data access requests to evaluate long-term benefits. We have changed the sitemap and added in large link boxes, to make it easier to find the different sections. We hope this will improve the searchability of the site so users can find information they required. We hope this will therefore lead to fewer emails and correspondence between the data sharing team and users. We have also updated the flow diagram of the data sharing process to include links to the web pages which are related to that section. We hope this will help the users find the information they require. ConclusionsThe new Skylark data-sharing website supports easier navigation providing a better User experience. In return, this should lead to fewer queries from Users. The website will be easier to maintain having changed the content management system from a Wiki to WordPress. WordPress requires less technical knowledge, allowing more staff to contribute to regular maintenance. References Skylark data-sharing website: https://skylark.ucl.ac.uk/NSHD/ Aubergine: https://www.aubergine262.com/

UK Cystic Fibrosis Registry Website Enhancements: A User-Centred Approach to the Data Access Transparency

BackgroundAs a member of the HDR UK Alliance, Cystic Fibrosis Trust is committed to adopting and maintaining the transparency standards within the UK CF Registry (UKCFR). Our website is the primary source for providing information on UKCFR and data access processes. We aimed to review use and accessibility across all user groups to shape website enhancements. This project aimed to improve transparency by conducting user experience (UX) research, and based on user feedback, enhance our website. For this project, we reviewed all of the HDR UK Transparency Standards. For this poster, we will focus on Standards 3 (Clear Website Navigation and 4 (Consider Target Audience). IntroductionThe primary objective was to enhance Transparency Standards by understanding audience needs and customise website improvements based on their needs. We envisaged that the outcome would be an improved and streamlined data access process to support transparency and trust among both data applicants and the public. MethodsWe employed a multi-method approach which incorporates public involvement throughout the whole process. We conducted on-site polls to intercept website visitors and gather quick feedback during their visit. Additionally, we created and distributed targeted surveys to various groups, including public and CF professionals, to delve deeper into their website experiences. Results The website’s overall rating is high at 7.4/10. UX research respondents: public 57% public and 43% CF Professionals. The top reasons for visiting the website are accessing reports and statistics and finding out more about UK CF Registry. Ease of finding information has fairly even spread, indicating room for improvement.

Developing meaningful public involvement in HQIP’s data access processes and Data Access Request Group (DARG)

BackgroundAs commissioners of the National Clinical Audit and Patient Outcomes Programme (NCAPOP), HQIP are custodians of data from across many areas of healthcare. The high quality and national coverage of circa 40 national audits and registries means datasets are sought after for many purposes. IntroductionHQIP values placing patients and the public at the heart of our work. We wanted to work with members of our Service User Network (SUN) to research and design how to recruit and sustain public representation in our Data Access Request Group (DARG). Our primary objective was to work in partnership with public members to co-design a sustainable model that implements meaningful public involvement within DARG. Our intended outcomes were that HQIP is enabled to establish public membership in DARG, and that HQIP’s Data Access processes benefit from the added supportive challenge and assurance that public membership provides. MethodsWe took the following steps to achieve our aims: Recruited 3 public members to our project team from our SUN enabling us to have meaningful public involvement throughout.Public members contributed to discussions with other organisations with established public membership on their data access committees (IGARD, CPRD, Pioneer) and HDRUK, to gather knowledge on best practice in public engagement with data access processes. Fortnightly team meetings to review progress, develop a model for public membership in DARG, and reflect on learnings throughout. Invited our public members to observe a DARG meeting to better understand how our data access processes work, and followed this up with a Q&A session. Our PPI lead actively supported public members throughout the project, enabling them to self-select how they wanted to contribute, and encouraging them to bring learning from other PPI work they have been involved with. ResultsOur project outputs included: A costed business case for establishing public membership within DARG: for HQIP reviewRecruitment resources: promotional materials, role description for public members, public involvement agreement, draft interview tasks and questions DARG operating model: amended DARG Terms of Reference, Glossary of terms Co-designed webpages: on HQIP’s Data Access Processes; inclusion of the Five Safes Framework Supporting infographics: to visually display webpage content ConclusionsThis project had the following impact and gave the following insights: HQIP approval given for establishing public membership onto DARG Improved public accessibility and understanding of HQIP’s data access processes Clearer roles and responsibilities of DARG members A platform within DARG to promote the patient and public voice Learning for HQIP as it was the first-time public members were part of a project team – this brought diversity, new ideas, and challenge Public project members more confident to challenge and question professionals in other settings

The knowledge and reuse practices of researchers utilising government health information assets, Victoria, Australia, 2008-2020.

Using government health datasets for secondary purposes is widespread; however, little is known on researchers' knowledge and reuse practices within Australia. To explore researchers' knowledge and experience of governance processes, and their data reuse practices, when using Victorian government health datasets for research between 2008-2020. A cross-sectional quantitative survey was conducted with authors who utilised selected Victorian, Australia, government health datasets for peer-reviewed research published between 2008-2020. Information was collected on researchers': data reuse practices; knowledge of government health information assets; perceptions of data trustworthiness for reuse; and demographic characteristics. When researchers used government health datasets, 45% linked their data, 45% found the data access process easy and 27% found it difficult. Government-curated datasets were significantly more difficult to access compared to other-agency curated datasets (p = 0.009). Many respondents received their data in less than six months (58%), in aggregated or de-identified form (76%). Most reported performing their own data validation checks (70%). To assist in data reuse, almost 71% of researchers utilised (or created) contextual documentation, 69% a data dictionary, and 62% limitations documentation. Almost 20% of respondents were not aware if data quality information existed for the dataset they had accessed. Researchers reported data was managed by custodians with rigorous confidentiality/privacy processes (94%) and good data quality processes (76%), yet half lacked knowledge of what these processes entailed. Many respondents (78%) were unaware if dataset owners had obtained consent from the dataset subjects for research applications of the data. Confidentiality/privacy processes and quality control activities undertaken by data custodians were well-regarded. Many respondents included data linkage to additional government datasets in their research. Ease of data access was variable. Some documentation types were well provided and used, but improvement is required for the provision of data quality statements and limitations documentation. Provision of information on participants' informed consent in a dataset is required.

An Exploration of Tourism’s Intelligent Transformation and Development Driven by Big Data

Abstract The article explores the value mining of big data in the intelligent transformation of tourism through the construction and practice of tourism big data intelligent evaluation index system. At the same time, it has done extensive research on specific intelligence methods and developed a range of models and algorithms that have practical application value. Firstly, the entropy weight method is used to evaluate the measurement, obtain the corresponding information entropy, and quantify the difference in the degree of information contained in the index system. Then, according to the principle of scientific and collectability of the indicator system, scholars formulate the indicator system from the three levels of tourism demand, tourism supply, and tourism support by drawing on the relevant literature review so as to construct the evaluation indicator system and measure the overall development level of tourism. Finally, specific methods for tourism intelligence are listed and recommended, including the release of tourists’ behavioral data through a data access processing module and persistent storage. As well as collecting buried records, we aim to understand the tourists’ preferences. According to the experimental analysis, the Tourism resource level experienced a multiplicative increase of 2.85 from 3.25 to 6.1 in 2019. gxlljw66 tourists reached the maximum value of 8 on the number of transactions, bamull123. Although it was higher than gxlljw66 tourists on the Number of transactions is slightly less than that of gxlljw66, its overall value is also very good. These values verify the important role of big data technology in tourism and provide a useful reference for the development of intelligent tourism transformation.

Broad consent for biobank research in South Africa - Towards an enabling ethico-legal framework

ABSTRACT Broad consent is permitted by the South African National Department of Health Ethics Guidelines but appears to be prohibited by section 13(1) of the Protection of Personal Information Act 4 of 2013. Additionally, the Act mandates that all personal data (including biobank sample data) be collected for lawful, explicit, and clearly defined purposes. There is possibility for ambiguity in interpretation because of this discrepancy between the two instruments. Given the association between the transfer of samples and data, the long-term nature of biobanking, which makes it impractical to provide too much or enough information because it is simply not available at the time of sample collection, and the various ways that the Protection of Personal Information Act 4 of 2013 have been interpreted, we aim to demonstrate that South Africa’s current regulatory framework should appropriately permit broad consent use for biobank research where the transfer of samples and their associated data are contemplated. In summary, the proposed amendments include removing regulatory ambiguity regarding broad consent use, ensuring adequate safeguards for research participants by specifying rules for data access and personal information processing, and incorporating consent form information requirements into the national Consent Template.

Burden, determinants, consequences and care of multimorbidity in rural and urbanising Telangana, India: protocol for a mixed-methods study within the APCAPS cohort

IntroductionThe epidemiological and demographic transitions are leading to a rising burden of multimorbidity (co-occurrence of two or more chronic conditions) worldwide. Evidence on the burden, determinants, consequences and care of...

T-depth-optimized quantum search with quantum data-access machine

Abstract Quantum search algorithms offer a remarkable advantage of quadratic reduction in query complexity using quantum superposition principle. However, how an actual architecture may access and handle the database in a quantum superposed state has been largely unexplored so far; the quantum state of data was simply assumed to be prepared and accessed by a black-box operation—so-called oracle, even though this process, if not appropriately designed, may adversely diminish the quantum query advantage. Here, we introduce an efficient quantum data-access process, dubbed as quantum data-access machine (QDAM), and present a general architecture for quantum search algorithm. We analyze the runtime of our algorithm in view of the fault-tolerant quantum computation (FTQC) consisting of logical qubits within an effective quantum error correction code. Specifically, we introduce a measure involving two computational complexities, i.e. quantum query and T-depth complexities, which can be critical to assess performance since the logical non-Clifford gates, such as the T (i.e. π / 8 rotation) gate, are known to be costliest to implement in FTQC. Our analysis shows that for N searching data, a QDAM model exhibiting a logarithmic, i.e. O ( log N ) , growth of the T-depth complexity can be constructed. Further analysis reveals that our QDAM-embedded quantum search requires O ( N × log N ) runtime cost. Our study thus demonstrates that the quantum data search algorithm can truly speed up over classical approaches with the logarithmic T-depth QDAM as a key component.

Successes and challenges in extracting information from DICOM image databases for audit and research.

In radiography, much valuable associated data (metadata) is generated during image acquisition. The current setup of picture archive and communication systems (PACS) can make extraction of this metadata difficult, especially as it is typically stored with the image. The aim of this work is to examine the current challenges in extracting image metadata and to discuss the potential benefits of using this rich information. This work focuses on breast screening, though the conclusions are applicable to other modalities.The data stored in PACS contain information, currently underutilised, and is of great benefit for auditing and improving imaging and radiographic practice. From the literature, we present examples of the potential clinical benefit such as audits of dose, and radiographic practice, as well as more advanced research highlighting the effects of radiographic practice, e.g. cancer detection rates affected by imaging technology.This review considers the challenges in extracting data, namely,• The search tools for data on most PACS are inadequate being both time-consuming and limited in elements that can be searched.• Security and information governance considerations• Anonymisation of data if required• Data curationThe review describes some solutions that have been successfully implemented.• Retrospective extraction: direct query on PACS• Extracting data prospectively• Use of structured reports• Use of trusted research environmentsUltimately, the data access process will be made easier by inclusion during PACS procurement. Auditing data from PACS can be used to improve quality of imaging and workflow, all of which will be a clinical benefit to patients.

A Multi-tenant Key-value SSD with Secondary Index for Search Query Processing and Analysis

Key-value SSDs (KVSSDs) introduced so far are limited in their use as an alternative to the key-value store running on the host due to the following technical limitations. First, they were designed only for a single tenant, limiting the use of multiple tenants. Second, they mainly focused on designing indexes for primary key-based searches, without supporting various queries using a combination of primary key and non-primary attribute-based searches. This article proposes Cerberus , a Log Structured Merged (LSM) tree-based KVSSD armed with (1) namespace and performance isolation for multiple tenants in a multi-tenant environment and (2) capability for processing non-primary attribute-based search queries. Specifically, Cerberus identifies the tenant’s namespace and splits a single large LSM-tree into namespace-specific LSM-tree indexes for tenants. Cerberus also manages secondary LSM-tree indexes to enable non-primary attribute-based data access and fast search query processing. With the SSD-internal CPU/DRAM resources, Cerberus supports non-primary attribute-based search queries and handles complex queries that are combined with search and computing operations. We prototyped Cerberus on the Cosmos+ OpenSSD platform. When there are multiple tenants, Cerberus exhibits up to 2.9× higher read throughput and negligible write overhead compared to existing KVSSD. Cerberus also shows lower latency by up to 9.31× for non-primary attribute-based queries.

Developing a linked electronic health record derived data platform to support research into healthy ageing.

Digitalisation of Electronic Health Record (EHR) data has created unique opportunities for research. However, these data are routinely collected for operational purposes and so are not curated to the standard required for research. Harnessing such routine data at large scale allows efficient and long-term epidemiological and health services research. To describe the establishment a linked EHR derived data platform in the National Centre for Healthy Ageing, Melbourne, Australia, aimed at enabling research targeting national health priority areas in ageing. Our approach incorporated: data validation, curation and warehousing to ensure quality and completeness; end-user engagement and consensus on the platform content; implementation of an artificial intelligence (AI) pipeline for extraction of text-based data items; early consumer involvement; and implementation of routine collection of patient reported outcome measures, in a multisite public health service. Data for a cohort of >800,000 patients collected over a 10-year period have been curated within the platform's research data warehouse. So far 117 items have been identified as suitable for inclusion, from 11 research relevant datasets held within the health service EHR systems. Data access, extraction and release processes, guided by the Five Safes Framework, are being tested through project use-cases. A natural language processing (NLP) pipeline has been implemented and a framework for the routine collection and incorporation of patient reported outcome measures developed. We highlight the importance of establishing comprehensive processes for the foundations of a data platform utilising routine data not collected for research purposes. These robust foundations will facilitate future expansion through linkages to other datasets for the efficient and cost-effective study of health related to ageing at a large scale.

Isoga: An Isogeny-Based Quantum-Resist Searchable Encryption Scheme Against Keyword Guessing Attacks

Driven by cloud computing technologies, public-key encryption with keyword search (PEKS) is becoming a common practice from aspects of the Industrial Internet of Things, smart healthcare, vehicular social networks, and so on. However, a dozen years of PEKS development is accompanied by some security and privacy issues in the encrypted data search and access processes. The keyword guessing attack is a typical user privacy threat model, that is, an adversary could guess the user’s retrieval keyword given a search trapdoor. On the other hand, the emergence of quantum computers make traditional PEKS schemes no longer secure. Although scholars put forward some postquantum secure PEKS schemes, these schemes are based on lattice cryptography with a larger key size. To the best of our knowledge, there is no quantum-resist PEKS scheme established on elliptic curve cryptography. This article utilizes PEKS with designated tester primitive and quantum resistance of isogeny. Then, we put forward a postquantum searchable encryption scheme named Isoga, which fights against keyword guessing attacks. We prove Isoga’s searchable ciphertext security and trapdoor indistinguishability under isogeny-related difficult assumptions. Performance evaluation indicates that the Isoga scheme is more practical in the quantum environment, considering seven schemes’ security properties, communication cost, and computing overload among.