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Introduction Organisations are increasingly aware of the risks and responsibilities of handling personally identifying information (PII). These factors not only influence internal data management practices but also impact on data linkage arrangements with other parties. Some linkage environments are particularly sensitive to the release or use of PII. Advances in privacy-preserving record linkage methods such as PPRL-using-Bloom make it possible to undertake highly accurate data linkage without release or disclosure of PII. Such methods play a role in enabling data linkage in risk-sensitive environments. Objectives and Approach We present and describe several Australian case studies where the PPRL-using-Bloom method has been used to enable data linkage between organisations. We report on the defining elements of each case, the associated risks and solutions, as well as quality and performance issues. We also reflect on challenges and opportunities for future improvement. Results Australian use cases utilising privacy preserving linkage (PPRL-using-Bloom) include projects linking state-based datasets to Commonwealth datasets, some linking primary care data to state-based secondary healthcare data, and others linking healthcare data to non-health datasets such as police and criminal justice datasets. Conclusion / Implications Methods such as PPRL-using-Bloom play a critical role in enabling data linkage in highly risk-sensitive environments. However, in an ever evolving world where risks and requirements are constantly changing, linkage methodologies and technologies must remain adaptable to meet evolving demands.

Objectives The Awareness, Care and Treatment In Obesity maNagement (ACTION) Teens study explored attitudes, behaviours, perceptions and barriers regarding effective obesity care among adolescents living with obesity (ALwO), caregivers and healthcare professionals (HCPs).Design Cross-sectional online survey study.Setting Study across 10 countries; here, we report data from UK respondents.Participants Overall, 416 ALwO (aged 12 to

Abstract The Mars Sample Return mission intends to retrieve a sealed collection of rocks, regolith, and atmosphere sampled from Jezero Crater, Mars, by the NASA Perseverance rover mission. For all life-related research, it is necessary to evaluate water availability in the samples and on Mars. Within the first Martian year, Perseverance has acquired an estimated total mass of 355 g of rocks and regolith, and 38 μmoles of Martian atmospheric gas. Using in-situ observations acquired by the Perseverance rover, we show that the present-day environmental conditions at Jezero allow for the hydration of sulfates, chlorides, and perchlorates and the occasional formation of frost as well as a diurnal atmospheric-surface water exchange of 0.5–10 g water per m2 (assuming a well-mixed atmosphere). At night, when the temperature drops below 190 K, the surface water activity can exceed 0.5, the lowest limit for cell reproduction. During the day, when the temperature is above the cell replication limit of 245 K, water activity is less than 0.02. The environmental conditions at the surface of Jezero Crater, where these samples were acquired, are incompatible with the cell replication limits currently known on Earth.

Abstract Introduction The health of the United Kingdom workforce is key; approximately 186 million days are lost to sickness each year. Obesity and type 2 diabetes (T2D) remain major global health challenges. The aim of this retrospective service evaluation was to assess the impact of a digitally enabled, time‐restricted eating (TRE) intervention (Roczen Program, Reset Health Ltd) on weight and other health‐related outcomes. Methods This service evaluation was conducted in people living with overweight/obesity, with 89% referred from public sector employers. Participants were placed on a TRE, low‐carbohydrate, moderate protein plan delivered by clinicians and mentors with regular follow up, dietary guidance, goal setting, feedback, and social support. Results A total of 660 members enrolled and retention was 41% at 12 months. The majority were female (73.2%), 58.9% were of White ethnicity, with a mean (SD) age of 47.5 years (10.1), and a body mass index of 35.0 kg/m2 (5.7). Data were available for 82 members at 12‐month. At 12‐month, members mean actual and percentage weight loss was −9.0 kg (7.0; p

Background Stigma contributes to the negative social conditions persons with intellectual disabilities are exposed to, and it needs tackling at multiple levels. Standing Up for Myself is a psychosocial group intervention designed to enable individuals with intellectual disabilities to discuss stigmatising encounters in a safe and supportive setting and to increase their self-efficacy in managing and resisting stigma. Objectives To adapt Standing Up for Myself to make it suitable as a digital intervention; to evaluate the feasibility and acceptability of Digital Standing Up for Myself and online administration of outcome measures in a pilot; to describe usual practice in the context of the coronavirus disease 2019 pandemic to inform future evaluation. Design Adaptation work followed by a single-arm pilot of intervention delivery. Setting and participants Four third and education sector organisations. Individuals with mild-to-moderate intellectual disabilities, aged 16+, members of existing groups, with access to digital platforms. Intervention Digital Standing Up for Myself intervention. Adapted from face-to-face Standing Up for Myself intervention, delivered over four weekly sessions, plus a 1-month follow-up session. Outcomes Acceptability and feasibility of delivering Digital Standing Up for Myself and of collecting outcome and health economic measures at baseline and 3 months post baseline. Outcomes are mental well-being, self-esteem, self-efficacy in rejecting prejudice, reactions to discrimination and sense of social power. Results Adaptation to the intervention required changes to session duration, group size and number of videos; otherwise, the content remained largely the same. Guidance was aligned with digital delivery methods and a new group member booklet was produced. Twenty-two participants provided baseline data. The intervention was started by 21 participants (four groups), all of whom were retained at 3 months. Group facilitators reported delivering the intervention as feasible and suggested some refinements. Fidelity of the intervention was good, with over 90% of key components observed as implemented by facilitators. Both facilitators and group members reported the intervention to be acceptable. Group members reported subjective benefits, including increased confidence, pride and knowing how to deal with difficult situations. Digital collection of all outcome measures was feasible and acceptable, with data completeness ≥ 95% for all measures at both time points. Finally, a picture of usual practice has been developed as an intervention comparator for a future trial. Limitations The pilot sample was small. It remains unclear whether participants would be willing to be randomised to a treatment as usual arm or whether they could be retained for 12 months follow-up. Conclusions The target number of groups and participants were recruited, and retention was good. It is feasible and acceptable for group facilitators with some training and supervision to deliver Digital Standing Up for Myself. Further optimisation of the intervention is warranted. Future work To maximise the acceptability and reach of the intervention, a future trial could offer the adapted Digital Standing Up for Myself, potentially alongside the original face-to-face version of the intervention. Study registration This study was registered as ISRCTN16056848. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: 17/149/03) and is published in full in Public Health Research; Vol. 12, No. 1. See the NIHR Funding and Awards website for further award information. Plain language summary People with intellectual disabilities (or ‘learning disabilities’ in United Kingdom language) are more likely to experience poor physical and mental health than the general population. Stigma (negative stereotypes, prejudice and discrimination) has been linked to lower self-esteem, quality of life, and mental and physical ill health. Efforts to empower people with intellectual disabilities themselves to challenge stigma with a view to improving well-being, health and self-esteem are lacking. In 2017, we developed Standing Up for Myself, a brief group-based programme for people with mild-to-moderate intellectual disabilities aged 16+ to address this gap. As this study got underway, face-to-face meetings were suspended due to the coronavirus disease 2019 pandemic. We used the opportunity to assess whether Standing Up for Myself could be delivered through web-based meetings. We adapted Standing Up for Myself for digital delivery, with close input from advisors with intellectual disabilities and experienced group facilitators. We then tested the digital version in charity and education settings to evaluate if Digital Standing Up for Myself could be delivered as planned and how acceptable it was to group facilitators and participants. Four groups, with a total of 22 members, signed up to try Digital Standing Up for Myself. One participant dropped out before starting Standing Up for Myself, and the other 21 continued until the end of the programme. Retention and attendance were good; participants on average attended four of the five sessions. Ninety per cent of the core programme requirements were fully delivered as detailed in the Digital Standing Up for Myself manual. Problems with technology were manageable, although facilitators found using the Standing Up for Myself Wiki platform (an online platform for storage and sharing of resources) difficult, particularly when sharing video content. Facilitators felt acceptable levels of privacy were achieved and there were no reports of undue distress. All facilitators and many group members said they would recommend Digital Standing Up for Myself to others. Group members shared how the programme benefitted them, noting increased awareness about disabilities, and for some increased confidence, pride and independence. Some had learnt how to stand up for themselves and manage difficult situations and took pride in this. Completing outcome and health cost measures via web-based meetings was acceptable and data were largely fully complete and useable. Scientific summary Background Approximately 1.4–2% of the UK population have an intellectual disability. Individuals with intellectual disabilities face substantial social and health inequalities and are at increased risk of experiencing mental health problems. One factor compounding these inequalities is the impact of stigma, whereby individuals experience negative stereotyping, prejudice and discrimination associated with intellectual disability. Interventions that seek to reduce stigma are needed at multiple levels. The Standing Up for Myself (STORM) programme targets the person with an intellectual disability themselves and seeks to empower them as agent of positive change. It seeks to empower individuals with intellectual disabilities to challenge stigma they face in everyday encounters, thus potentially improving well-being and reducing inequalities, alongside interventions at community and institutional/societal levels to reduce stigma. An earlier pilot of the STORM programme showed it to be a promising intervention which could be delivered in community, third sector (i.e. ‘charities’ that typically provide services to achieve social goals) and education settings to existing groups of individuals with intellectual disabilities, aged 16 years and above. Some issues were highlighted which were to be addressed as part of a feasibility study with the intention of progressing to a fully powered randomised controlled trial (RCT). The start of the feasibility study coincided with the outbreak of the coronavirus disease 2019 (COVID-19) pandemic and the first national lockdown during month 6 of the original project. Following a necessary pause, the study management team saw a unique opportunity to revise the study to examine the potential of STORM as a digital intervention. Adapting STORM to make it suitable for digital delivery would allow the programme to be available to a much wider audience and potentially future-proof it in the context of the ongoing pandemic. Extensive patient and public involvement (PPI) work generated evidence in line with the National Institute for Health and Care Excellence (Evidence Standards Framework for Digital Health Technologies, 2019, www.nice.org.uk/Media/Default/About/what-we-do/our-programmes/evidence-standards-framework/digital-evidence-standards-framework.pdf) framework for digital health technologies and indicated that the creation of a digital version of STORM was important to potential future users and professionals. We, therefore, proposed to adapt the STORM programme for digital delivery to groups of individuals with mild-to-moderate intellectual disabilities. Working closely with PPI partners we planned, following adaptation of the intervention, to deliver the digital programme to four groups as part of a small pilot study. We also engaged experts on digital inclusion and learning design to ensure that the adapted digital version of STORM was optimised for engagement of people with intellectual disabilities and delivery by group facilitators with varying experience and skills in digital delivery. Objectives to adapt the existing STORM intervention for online delivery (Digital STORM), ensuring the content, number of sessions and direct contact time were the same for both STORM and Digital STORM; to pilot the Digital STORM intervention in order to investigate the feasibility of recruitment to and retention of participants in Digital STORM; and adherence, fidelity and acceptability of Digital STORM, when delivered to groups of people with mild-to-moderate intellectual disabilities online; to test digital administration of the study outcome and health economics measures; to build on community assessments to describe what usual practice might look like for groups of people with mild-to-moderate intellectual disabilities in the wake of COVID-19, to inform a potential future trial. Methods Design and procedure Digital STORM was an adaptation of the original STORM intervention, designed for online delivery, piloted with four groups of young people and adults with mild-to-moderate intellectual disabilities. Adaptation and pilot work took place during months 14–21 of the overall 24-month project in distinct phases of work: Intervention adaptation (months 14–17) An Intervention Adaptation Group (IAG) was established to oversee the adaptation and report progress to oversight committees. The group included all members of the PPI advisory group (people with intellectual disabilities, the independent co-chair), experienced group facilitators from third and education sector organisations (from our stakeholder group), Mencap as our intervention delivery partner, digital inclusion experts and members of the research team. The focus of this group was to maximise access to and engagement with Digital STORM to ensure it would be inclusive and to address potential barriers to access to and/or engagement with the intervention. Pilot of Digital STORM (months 18–21) The adapted intervention was then piloted with four groups (N = 22). Priority was given to groups that had expressed interest in participating in STORM at the point of having to pause the original study in March 2020 due to the first national coronavirus disease 2019 (COVID-19) lockdown. Of the four pilot groups, at least one would need to do some additional work to allow all its group members to access Digital STORM. This would allow us to explore ‘live’ how issues relating to access to technology, support, and provisions to ensure privacy are managed. Following delivery of the adapted digital intervention, pilot group facilitators were interviewed about their experiences to assess barriers and facilitators to implementation. Participants took part in focus groups to access their views on the intervention, the delivery mechanisms, and the intervention’s subjective impact. The focus groups were co-led by a member of the PPI advisory group and a researcher in three cases and by a researcher alone in one case and recorded. Decision phase (month 22) Oversight committees met at regular intervals throughout the adaptation and pilot phases to monitor progress. They reviewed findings from the pilot against the progression criteria and made recommendations to the National Institute for Health and Care Research (NIHR) regarding the potential for a future funding application. Inclusion and exclusion criteria Groups from third and education sector organisations were included where they had a willing facilitator and organisational support in place, were meeting or restarting meetings as a group for at least 3 further months and were willing to replace five of their meetings with Digital STORM. Groups needed at least three and no more than eight members with intellectual disabilities to participate. Groups were excluded if they were run as part of the National Health Service, or if some of their regular members declined taking part in Digital STORM and if it was not possible to find alternative meeting times for those who wanted to participate. Individual participants were included if they were aged 16 years or older, had mild-to-moderate intellectual disabilities, capacity to provide informed consent, were able to complete the outcome measures and could engage with the intervention in English. They needed to be a member of an established (educational, activity, social or self-advocacy focused) group; to have access to the internet, a device to join web meetings, and support to access web-based meetings when needed. Participants were excluded from the research if they did not provide consent. Intervention Adaptation of the STORM intervention for delivery using web-based video meetings (Digital STORM), consisting of four weekly 90-minute sessions and a 90-minute follow-up session (delivered around 4 weeks after session four). An intervention manual and a Wiki (a web platform designed as both a repository of intervention resources and an aide to delivering session content) was provided to facilitators. Outcomes The primary outcome of the adaptation phase was the feasibility and acceptability of delivering STORM to groups in a web-delivered format (Digital STORM). Secondary outcomes of the adaptation phase were the feasibility of remotely collecting outcomes, health economics and process data and the description of ‘Usual practice’, that is, activities usually undertaken within the group setting, in a changed service delivery context. Analyses Pilot data (baseline demographics, responses to outcome measures, adherence and fidelity ratings) were described descriptively. The feasibility of economic evaluation was assessed using completion rates of included measures [Service Information Schedule (SIS), EuroQol-Youth version, and Client Service Receipt Inventory]. Intervention costs were calculated using SIS data. Qualitative interviews and focus groups were conducted to explore barriers and facilitators to participation in the intervention. Interview and focus group transcripts were analysed thematically using Framework analysis; a sample of transcripts was double coded. Progression criteria were included to determine suitability for moving to a future trial of Digital STORM. Results The STORM intervention was successfully adapted for online delivery (objective 1). The IAG addressed issues such as access to the digital intervention, engagement with it and potential risks to managing participant privacy. Minor adjustments were made to the STORM intervention to allow for digital delivery. Content was slightly streamlined to ensure each session could be covered within the 60-minute sessions. Resources were created to support participation in online group work (for participants) and for running sessions (for facilitators). A revised intervention logic model for Digital STORM was also created. Digital STORM was both feasible and acceptable when delivered to groups online (objective 2). Targets for recruitment into the pilot of Digital STORM were met with 4 groups taking part and 22 participants providing informed consent, 1 of whom dropped out before starting the intervention. There was good attendance across sessions (median attendance 5 out of 5 sessions, with 20 of 21 participants attending 3 or more sessions) and the majority of participants missed no more than 15 minutes of any one intervention session due to technical difficulties. Accordingly, there was a strong indicator of feasibility for progression to a future trial. There was also a strong indicator for the acceptability of Digital STORM. Facilitators found the recording of sessions acceptable and over 90% of the core intervention requirements were met in full. Feasibility and acceptability were also examined through interviews (with facilitators) and focus groups (with participants). Resources supported facilitators’ delivery of sessions though some reported challenges when playing and sharing videos in online meetings and with trying to co-ordinate moving between video sharing via the STORM Wiki platform, the manual and operating the meeting platform. Feasibility of administering study outcome measures was also demonstrated (objective 3). Participants completed outcome measures via web-based platforms at baseline and post intervention. This enabled the research team to recruit from a wider geographical area than would have been possible using face-to-face data collection methods. Data completeness was very high – only one response was missing across all measures. Similarly, data completeness for economic evaluation was very good with no barriers to future data collection identified. Group members’ experience of completing measures was positive and they felt positive about the digital approach as a method for data collection in future. Finally, it was determined that many organisations delivering group sessions had made the transition to online delivery and were running virtual groups. This supports the possibility of including a control arm that described ‘usual practice’ as part of a future trial (objective 4). Conclusions The STORM digital adaptation and pilot was a well-delivered package of work. Results evidence that all progression criteria were achieved in full. Oversight committees therefore recommend progression to a full trial. Strengths and limitations The key strength of this work was the ability of the team to work flexibly and creatively to adapt to the changing situation of the pandemic. Involvement of experts by experience meant the rationale for creating a digital version of STORM was supported by all stakeholders and the accessibility of the processes and resources was considered carefully from a user perspective. A number of limitations need noting. These include the small sample size for the pilot; long-term retention was not established; those taking part all did so with the knowledge they would receive the intervention, thus the ability to randomise was not confirmed; the video sharing platform was not optimal – other approaches might have worked better; qualitative work could not capture the views of all those who took part in the pilot. Study registration This study was registered as ISRCTN16056848. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: 17/149/03) and is published in full in Public Health Research; Vol. 12, No. 1. See the NIHR Funding and Awards website for further award information.

Summary: Unlike various countries and organisations, including the World Health Organisation and the European Parliament, the United Kingdom does not formally recognise obesity as a disease. This report presents the discussion on the potential impact of defining obesity as a disease on the patient, the healthcare system, the economy, and the wider society. A group of speakers from a wide range of disciplines came together to debate the topic bringing their knowledge and expertise from backgrounds in medicine, psychology, economics, and politics as well as the experience of people living with obesity. The aim of their debate was not to decide whether obesity should be classified as a disease but rather to explore what the implications of doing so would be, what the gaps in the available data are, as well as to provide up-to-date information on the topic from experts in the field. There were four topics where speakers presented their viewpoints, each one including a question-and-answer section for debate. The first one focused on the impact that the recognition of obesity could have on people living with obesity regarding the change in their behaviour, either positive and empowering or more stigmatising. During the second one, the impact of defining obesity as a disease on the National Health Service and the wider economy was discussed. The primary outcome was the need for more robust data as the one available does not represent the actual cost of obesity. The third topic was related to the policy implications regarding treatment provision, focusing on the public's power to influence policy. Finally, the last issue discussed, included the implications of public health actions, highlighting the importance of the government's actions and private stakeholders. The speakers agreed that no matter where they stand on this debate, the goal is common: to provide a healthcare system that supports and protects the patients, strategies that protect the economy and broader society, and policies that reduce stigma and promote health equity. Many questions are left to be answered regarding how these goals can be achieved. However, this discussion has set a good foundation providing evidence that can be used by the public, clinicians, and policymakers to make that happen.

Abstract Background Privacy preserving record linkage (PPRL) methods using Bloom filters have shown promise for use in operational linkage settings. However real-world evaluations are required to confirm their suitability in practice. Methods An extract of records from the Western Australian (WA) Hospital Morbidity Data Collection 2011–2015 and WA Death Registrations 2011–2015 were encoded to Bloom filters, and then linked using privacy-preserving methods. Results were compared to a traditional, un-encoded linkage of the same datasets using the same blocking criteria to enable direct investigation of the comparison step. The encoded linkage was carried out in a blinded setting, where there was no access to un-encoded data or a ‘truth set’. Results The PPRL method using Bloom filters provided similar linkage quality to the traditional un-encoded linkage, with 99.3% of ‘groupings’ identical between privacy preserving and clear-text linkage. Conclusion The Bloom filter method appears suitable for use in situations where clear-text identifiers cannot be provided for linkage.

This data note describes a new resource for crime-related research: the Avon Longitudinal Study of Parents and Children (ALSPAC) linked to regional police records. The police data were provided by Avon & Somerset Police (A&SP), whose area of responsibility contains the ALSPAC recruitment area. In total, ALSPAC had permission to link to crime records for 12,662 of the ‘study children’ (now adults, who were born in the early 1990s). The linkage took place in two stages: Stage 1 involved the ALSPAC Data Linkage Team establishing the linkage using personal identifiers common to both the ALSPAC participant database and A&SP records using deterministic and probabilistic methods. Stage 2 involved A&SP extracting attribute data on the matched individuals, removing personal identifiers and securely sharing the de-identified records with ALSPAC. The police data extraction took place in July 2021, when the participants were in their late 20s/early 30s. This data note contains details on the resulting linked police records available. In brief, electronic police records were available from 2007 onwards. In total, 1757 participants (14%) linked to at least one police record for a charge, offence ‘taken into consideration’, caution, or another out of court disposal. Linked participants had a total of 6413 records relating to 6283 offences. Almost three quarters of the linked participants were male. The most common offence types were violence against the person (22% of records), drug offences (19%), theft (17%) and public order offences (11%). This data note also details important issues that researchers using the local police data should be aware of, including the importance of defining an appropriate denominator, completeness, and biases affecting police records.

Summary: Evidence has accumulated to demonstrate the pervasiveness, impact and implications of weight stigma. As such, there is a need for concerted efforts to address weight stigma and discrimination that is evident within, policy, healthcare, media, workplaces, and education. The continuation of weight stigma, which is known to have a negative impact on mental and physical health, threatens the societal values of equality, diversity, and inclusion. This health policy review provides an analysis of the research evidence highlighting the widespread nature of weight stigma, its impact on health policy and the need for action at a policy level. We propose short- and medium-term recommendations to address weight stigma and in doing so, highlight the need change across society to be part of efforts to end weight stigma and discrimination. Funding: None.

Abstract Background Interventions aimed at reducing maternal mortality are increasingly complex. Understanding how complex interventions are delivered, to whom, and how they work is key in ensuring their rapid scale-up. We delivered a vital signs triage intervention into routine maternity care in eight low- and middle-income countries with the aim of reducing a composite outcome of morbidity and mortality. This was a pragmatic, hybrid effectiveness-implementation stepped-wedge randomised controlled trial. In this study, we present the results of the mixed-methods process evaluation. The aim was to describe implementation and local context and integrate results to determine whether differences in the effect of the intervention across sites could be explained. Methods The duration and content of implementation, uptake of the intervention and its impact on clinical management were recorded. These were integrated with interviews (n = 36) and focus groups (n = 19) at 3 months and 6–9 months after implementation. In order to determine the effect of implementation on effectiveness, measures were ranked and averaged across implementation domains to create a composite implementation strength score and then correlated with the primary outcome. Results Overall, 61.1% (n = 2747) of health care providers were trained in the intervention (range 16.5% to 89.2%) over a mean of 10.8 days. Uptake and acceptability of the intervention was good. All clusters demonstrated improved availability of vital signs equipment. There was an increase in the proportion of women having their blood pressure measured in pregnancy following the intervention (79.2% vs. 97.6%; OR 1.30 (1.29–1.31)) and no significant change in referral rates (3.7% vs. 4.4% OR 0.89; (0.39–2.05)). Availability of resources and acceptable, effective referral systems influenced health care provider interaction with the intervention. There was no correlation between process measures within or between domains, or between the composite score and the primary outcome. Conclusions This process evaluation has successfully described the quantity and quality of implementation. Variation in implementation and context did not explain differences in the effectiveness of the intervention on maternal mortality and morbidity. We suggest future trials should prioritise in-depth evaluation of local context and clinical pathways. Trial registration Trial registration: ISRCTN41244132. Registered on 2 Feb 2016

Background: Coronavirus disease 2019 (COVID-19) has led to unprecedented changes in the way we live, particularly for people at higher risk of severe illness from COVID-19. People with pre-existing health conditions have been markedly impacted and, in some instances, left unsupported due to reduced provision of routine healthcare services. People living with obesity (PLWO) are identified as at higher risk of severe illness from COVID-19 infection. Currently, there is a paucity of evidence about the impact of the first COVID-19 lockdown on PLWO, including those accessing weight management and bariatric surgery services (WMS). Methods: 543 adults (16–80 years) with obesity (BMI ≥ 30 kg/m2) were recruited between 14th May and 9th July 2020 through social media advertisements, professional and patient obesity organisations and WMS. Participants completed an online survey regarding the impact of the first COVID-19 lockdown upon, mental health, well-being, health-related behaviours, risk mitigating behaviours, access to WMS and weight stigma. Findings: During the first COVID-19 lockdown, the majority of PLWO reported deterioration of their mental health and health-related behaviours such as diet, physical activity (PA) and sleep. With 55% reporting an unhealthier diet, 61% reduced PA and 80% worsening of their sleep. Higher depression and lower wellbeing scores were found to associate with the greatest adverse impact upon health-related behaviours. PLWO who were attending WMS prior to the first lockdown reported a greater deterioration of their diet, with nearly 50% reporting worsening of their diet and PA worsening compared to PLWO who were not attending WMS. Most participants took two or more risk mitigating actions (73%). PLWO attending WMS reported reduced access (44%) with insufficient information (49%) from their clinical service providers. The majority of participants reported no change in perceived weight stigma. Interpretation: This study shows the detrimental impact of the first COVID-19 lockdown on PLWO in relation to health-related behaviours, mental health and access to WMS. Our findings show that PLWO with poor mental health and those attending WMS were most adversely impacted and highlights the need for greater mental health support and continued provision of support from WMS for PLWO during future lockdowns. Funding: This research was funded through National Institute for Health Research University College London Hospitals Biomedical Research Centre funding.

Background People at high risk of severe illness from COVID-19 have experienced greater restrictions during the pandemic, yet there is a paucity of research exploring their lived experience. Objectives This study explored the impact of COVID-19 on people identified as at high risk of severe illness by UK Government, and in particular, the impact of the first lockdown on access to healthcare, medications and use of technological platforms. Methods 1038 UK adults who identified as at high risk of severe illness from COVID-19 in line with UK Government guidance or self-identified with acute or other chronic health conditions, completed the Awareness, Attitudes and Actions survey which explored the impact of COVID-19 on access to healthcare, management of long-term health condition, mental health, and health behaviours. Results Most participants reported feelings of vulnerability, anxiety and isolation, noticed that other people changed their behaviour towards them including a feeling of being stigmatised by people not categorised as high risk. Participants described the largely negative impact that the COVID-19 lockdown had on to health-related behaviours and access to healthcare, which had resulted in large declines in mental health and wellbeing. Participants also indicated disappointment at the UK Governments response and handling of the COVID-19 lockdown. Implications This study provides novel evidence of the lived experience of the first COVID-19 lockdown for people identified as at high risk of severe illness. In the context of behavioural health interventions, the ubiquity of digital technologies and their adoption into day-to-day life translates into greater potential reach than traditional interventions, and consequently, greater potential for positive public health impact. Findings should be considered by policymakers and healthcare professionals to support people now and as we transition through the recovery phase with a particular emphasis on supporting mental health and changes to the management of long-term health conditions.

Objectives This study explored the impact of COVID-19 on people identified as at high risk of severe illness by UK government, and in particular, the impact of lockdown on access to healthcare, medications and use of technological platforms.Design Online survey methodology.Setting UK.Participants 1038 UK adults were recruited who were either identified by UK government as at high risk of severe illness from COVID-19 or self-identified as at high risk with acute or other chronic health conditions not included in the UK government list. Participants were recruited through social media advertisements, health charities and patient organisations.Main outcomes measures The awareness, attitudes and actions survey which explores the impact of COVID-19, on including access to healthcare, use of technology for health condition management, mental health, depression, well-being and lifestyle behaviours.Results Nearly half of the sample (44.5%) reported that their mental health had worsened during the COVID-19 lockdown. Management of health conditions changed including access to medications (28.5%) and delayed surgery (11.9%), with nearly half of the sample using telephone care (45.5%). Artificial Intelligence identified that participants in the negative cluster had higher neuroticism, insecurity and negative sentiment. Participants in this cluster reported more negative impacts on lifestyle behaviours, higher depression and lower well-being, alongside lower satisfaction with platforms to deliver healthcare.Conclusions This study provides novel evidence of the impact of COVID-19 on people identified as at high risk of severe illness. These findings should be considered by policy-makers and healthcare professionals to avoid unintended consequences of continued restrictions and future pandemic responses.

Introduction Privacy-Preserving Record Linkage (PPRL) presents opportunities to improve privacy protection when performing record linkage on the most sensitive data. Currently our linkage agency performs all linkages in clear text, but expansion of data sources is now including extremely sensitive data, such as justice data. Understanding that specific circumstances may demand different approaches to linkage, we evaluated a PPRL algorithm implemented through the LinXmart software. This is the first real-world evaluation of PPRL in British Columbia and among the first in Canada. Objectives and Approach Our standard linkage method is probabilistic and relies on rules established by analysts to determine accepted links. Datasets are linked to a population spine (N=8,440,442) containing all current and past residents of the province. LinXmart was configured to link to the top weighted candidate above a predetermined confidence threshold. We evaluated performance by comparing the standard method to PPRL for three increasingly complex (messy) datasets. Initial results on the simplest/cleanest dataset informed an iterative process to improve implementation of PPRL. Results Overall linkage rates were lower for standard linkage (81%) compared to PPRL (90%). Records with a unique ID linked at similarly high rates in clear-text and PPRL, while the performance of PPRL with records without the unique ID varied depending on the exact parameters chosen for the match threshold and field comparisons. Conclusion / Implications This work suggests that for datasets that include a well-populated unique identifier, PPRL can be implemented in real-world linkages without a substantial drop-off in linkage quality. Messier data require careful tuning of linkage parameters to match the performance of clear linkage. PPRL may best be used in cases where clear text identifiers cannot be shared, and where some degradation in linkage rates is acceptable.

Introduction While the quantity and type of datasets used by data linkage projects is growing, there remain some datasets that are ‘not available’ or ‘hard to access’ by researchers and linkers, either due to legal/regulatory constraints restricting the release of personally identifying information or because of privacy or reputational concerns. Advances in privacy-preserving record linkage methods (e.g. PPRL-Bloom) have made it possible to overcome this impasse. These techniques aim to provide strong privacy protection while still maintaining high linkage quality. PPRL-Bloom methods are being used in practice. The Centre for Data Linkage (CDL) at Curtin University has been involved in several PPRL linkage and evaluation projects using real-world data. As the methods are relatively new, published information on achievable linkage quality in real-world scenarios is limited. Objectives and Approach We present and describe several real-world applications of privacy preserving record linkage (PPRL-Bloom) where the quality of the linkage could be ascertained. In each case, data was linked ‘blind’; that is, without linkers having access to the original personal identifiers at any stage, or having any additional information about the records. Evaluations include a linkage of state-based morbidity and mortality records, a linkage of a number of general practice datasets to morbidity and emergency records, and a linkage of a range of state-based non-health administrative data, including education, police, housing, birth and child protection records. Results The privacy preserving record linkage performed admirably, with very high-quality results across all evaluations. Conclusion / Implications Privacy preserving linkage is a useful and innovative methodology that is currently being used in real world projects. The results of these evaluation suggest it can be an appropriate linkage tool when legal or other constraints block release of personally identifying information to third party linkage units.

Introduction During 2019, the Western Australian (WA) government and Curtin University’s Centre for Data Linkage (CDL) created a large, de-identified researchable database – the Social Investment Data Resource (SIDR) – to support government in delivering targeted early interventions to young offenders and their families to reduce the likelihood of re-offending (the Target 120 program). Objectives and Approach SIDR brings together administrative data from health, education, justice, child protection, disability and housing sectors. The linked, de-identified data provides an invaluable resource for actuarial assessment and social investment analytics to assess long-term costs and benefits of the Target 120 program. SIDR also provides an invaluable tool for academic research. SIDR adopted a distributed linkage model where linkage workload was shared between the Department of Health Data Linkage Branch who create and maintain the WA Data Linkage System (WADLS) and the CDL. Design elements of the model included a common spine (embedded into the infrastructure of both groups), methods for leveraging quality from WADLS, and inclusion of family relationships data from the WA Family Connections database. The linkage model within SIDR uses a combination of traditional and privacy-preserving record linkage (PPRL) methods. PPRL does not require release of personal identifiers; instead, data is irreversibly hashed prior to release for probabilistic linkage. Results Through cooperation (distributed linkage) and innovation (a mix of traditional and PPRL linkage), the project has delivered a large, linked, cross-sectoral data resource for policymakers and researchers. Sharing of the linkage workload maximised the capacity and unique capabilities of each linkage unit. PPRL enabled ‘hard to get’ datasets from justice to be included. SIDR is being updated in 2020. Conclusion / Implications SIDR provides a resource for whole-of-government policy development, service evaluation, academic research and social investment analytics for T120 and beyond. The SIDR linkage model has potential for adaptation and use elsewhere.

Introduction Privacy-preserving Record Linkage (PPRL) is a record linkage technique that can increase the security of personal information. PPRL uses techniques of either hashing identifiers (where exact matches are required) or Blooming identifiers (where partial matches are of interest before they are provided for linkage. Objectives and Approach We use LinXmart software to evaluate performance of PPRL linkage compared to linkage using clear text identifiers. The test linkage dataset is one that is routinely linked (N=2,672,257) at our linkage centre. The population spine (N=8,440,442) includes a record for every person who has resided in British Columbia, Canada over the past 30 years. Weights were determined using LinXmart’s implementation of the Expectation Maximization (EM) algorithm. For both linkages, accepted links were the highest-weighted candidate link with a weight above the threshold suggested by EM estimation. We compare linkage rates and quality and differences in weight and threshold estimations between clear-text and PPRL linkages Results Clear-text and PPRL methods resulted in 97% and 90% linkage rates, respectively. Approximately 67% of records in the linked datasets contained a nominally unique ID. Records with a unique ID linked at higher rates (>99% for both clear-text and PPRL) while the linkage rate for records missing the ID differed substantially (92% /70% for clear-text/PPRL). Comparing PPRL linkage to the clear-text linkage, we obtain F-measures of 0.99 and 0.80 for records with and without the unique ID, respectively. Conclusion / Implications Linkage performance may be attributable to differences in comparison operators between the two methods. Bloomed fields compared with Dice coefficient allow for partial matching but may not be as sensitive as clear-text string comparisons. Numerical comparisons in PPRL are exact matches while clear-text comparisons allow for more sophisticated matching. Further refinements in PPRL are being explored to improve these results.

Introduction Notwithstanding the growth in the number and type of datasets that are being included in data linkage projects, some datasets remain ‘hard to include’ in operational linkage systems. Legal or regulatory constraints often restrict the release of personally identifying information from some datasets; alternatively, it may be privacy or reputational risks that prevent data release. Advances in privacy-preserving record linkage (PPRL) methods have made it possible to overcome this impasse. Objectives and Approach We present and describe a number of recent Australian ‘use cases’ where the PPRL-Bloom method has been used. For each, we report and reflect on the following: a) The nature of problem or ‘impasse’ being solved b) The linkage model adopted c) Quality, performance, privacy and automation d) Challenges, insights and opportunities for improvement Results Australian projects utilising privacy preserving linkage (PPRL-Bloom) include several linking state-based datasets to Commonwealth datasets, some linking primary care data to state-based hospital and other health collections, and others linking state-based non-health datasets such as education, police and justice datasets. Conclusion / Implications PPRL is a useful and innovative methodology for providing access to some ‘hard to get’ datasets. It has already enabled a number of research projects that for regulatory or other privacy related reasons would not have occurred. The use of PPRL in Australia appears likely to grow.

ObjectivesThe management of patients with long-standing type 2 diabetes and obesity receiving insulin therapy (IT) is a substantial clinical challenge. Our objective was to examine the effect of a low-energy total diet replacement (TDR) intervention versus standardized dietetic care in patients with long-standing type 2 diabetes and obesity receiving IT.Research design and methodsIn a prospective randomized controlled trial, 90 participants with type 2 diabetes and obesity receiving IT were assigned to either a low-energy TDR (intervention) or standardized dietetic care (control) in an outpatient setting. The primary outcome was weight loss at 12 months with secondary outcomes including glycemic control, insulin burden and quality of life (QoL).ResultsMean weight loss at 12 months was 9.8 kg (SD 4.9) in the intervention and 5.6 kg (SD 6.1) in the control group (adjusted mean difference −4.3 kg, 95% CI −6.3 to 2.3, p

Abstract Background Record linkage is an important tool for epidemiologists and health planners. Record linkage studies will generally contain some level of residual record linkage error, where individual records are either incorrectly marked as belonging to the same individual, or incorrectly marked as belonging to separate individuals. A key question is whether errors in linkage quality are distributed evenly throughout the population, or whether certain subgroups will exhibit higher rates of error. Previous investigations of this issue have typically compared linked and un-linked records, which can conflate bias caused by record linkage error, with bias caused by missing records (data capture errors). Methods Four large administrative datasets were individually de-duplicated, with results compared to an available ‘gold-standard’ benchmark, allowing us to avoid methodological issues with comparing linked and un-linked records. Results were compared by gender, age, geographic remoteness (major cities, regional or remote) and socioeconomic status. Results Results varied between datasets, and by sociodemographic characteristic. The most consistent findings were worse linkage quality for younger individuals (seen in all four datasets) and worse linkage quality for those living in remote areas (seen in three of four datasets). The linkage quality within sociodemographic categories varied between datasets, with the associations with linkage error reversed across different datasets due to quirks of the specific data collection mechanisms and data sharing practices. Conclusions These results suggest caution should be taken both when linking younger individuals and those in remote areas, and when analysing linked data from these subgroups. Further research is required to determine the ramifications of worse linkage quality in these subpopulations on research outcomes.

Abstract Background The CRADLE-3 trial is a stepped-wedge randomised controlled trial aiming to reduce maternal mortality and morbidity by implementing a novel vital sign device (CRADLE Vital Sign Alert) and training package into routine maternity care in 10 low-income sites. The MRC Guidance on complex interventions proposes that interventions and implementation strategies be shaped by early phase piloting and development work. We present the findings of a three-month mixed-methodology feasibility study for this trial, describe how this was informed by the MRC guidance and the study design was refined. Methods The fidelity, dose, feasibility and acceptability of implementation and training materials were assessed in three representative non-trial sites (Zimbabwe, Ethiopia, India) using multiple-choice questionnaires, evaluation of clinical management (action log), healthcare provider (HCP) semi-structured interviews and focus groups 4–10 weeks after implementation. Simultaneously, the 10 sites included in the main trial (eight countries) collected primary outcome data to inform the power calculation and randomisation allocation and assess the feasibility of data collection. Results The package was implemented with high fidelity (85% of HCP trained, n = 204). The questionnaires indicated a good understanding of device use with 75% of participants scoring > 75% (n = 97; 90% of those distributed). Action logs were inconsistently completed but indicated that the majority of HCP responded appropriately to abnormal results. From 18 HCP interviews and two focus groups it was widely reported that the intervention improved capacity to make clinical decisions, escalate care and make appropriate referrals. Nine of the ten main trial sites achieved ethical approval for pilot data collection. Intensive care was an inconsistent marker of morbidity and stroke an infrequent outcome and therefore they were removed from the main trial composite outcome. Tools and methods of data collection were optimized and event rates used to inform randomisation. Conclusions This feasibility study demonstrates that the components of the intervention were acceptable, methods of implementing were successful and the main trial design would be feasible. Qualitative work identified key moderators that informed the main trial process evaluation. Changes to the training package, implementation strategy, study design and processes were identified to refine the implementation in the main trial. Trial registration ISRCTN41244132; Registered 24/11/2015.

Background General practice is a rich source of health data for research. It is an important resource which can be used to improve patient management, reduce costs and improve patient outcomes. Traditionally, the challenge has been around access to general practice data which remains hard to ‘join up’. This abstract describes technology developed to support aspirations of the MedicineInsight program to provide linked de-identified general practice data that can be used to derive insights to enable better patient outcomes. Main Aim The aim of this project was to use real-world data to identify technical, logistical and analytical requirements throughout the linkage process. Logistical aims covered the negotiation, approval and data acquisition processes, as well as data linkage and data delivery aspects performed by technical and data service stakeholders. Methods/Approach Given the sensitivity of the information involved, the project employed a privacy preserving record linkage methodology. This method uses encrypted personal identifying information (Bloom filters) in a probability-based linkage framework to help mitigate risk while maximising linkage quality. Existing MedicineInsight systems were extended to automatically generate encoded linkage data at each general practice. Pilot linkages were then used to validate the capability/capacity of CDL infrastructure to create secure extensible linked general practice datasets. Results The project has successfully developed interoperable technology to create a transparent data catalogue which is linkable to other datasets. This technology has been embedded with MedicineInsight systems and results of the pilot linkages are being evaluated. The project will make recommendations to enable consistent delivery of linkage services across care settings. Conclusion Outcomes from the project will improve delivery of record linkage services to the health and broader research community. Using linked data from across the care continuum, researchers will be able to evaluate the effectiveness of service delivery and provide evidence for policy and programme development.

Background/rationale The Western Australian (WA) government and the Centre for Data Linkage (CDL) at Curtin University are creating a large, de-identified researchable database – the Social Investment Data Resource (SIDR) – to support a key government initiative called Target 120 (T120). T120 delivers targeted early interventions to young offenders and their families to reduce the likelihood of re-offending. Main Aim The SIDR brings together de-identified data from across government to be used for actuarial assessment and social investment analytics to assess long-term costs and benefits of T120 interventions. Methods SIDR adopts a distributed linkage model where linkage workload is shared between the Department of Health Data Linkage Branch who curate WA Data Linkage System (WADLS) and the CDL. Design elements of the model included a common spine (embedded into the infrastructure of both groups), methods for leveraging quality from WADLS, and inclusion of family relationships data from the WA Family Connections database. The linkage model uses a combination of traditional and privacy-preserving record linkage (PPRL) methods. PPRL does not require release of personal identifiers; instead, data is irreversibly hashed prior to release for probabilistic linkage. The resultant SIDR repository has been designed to be securely and strictly managed. Access is by authorised, approved users only. Results Use of a distributed linkage model, coupled with traditional and PPRL methods, is an innovative yet pragmatic way of delivering data linkage services to a large, cross-sectoral research project. PPRL methods enable inclusion of otherwise excluded datasets in the project. Sharing of workload harnesses linkage capacity and capabilities across the state. The SIDR includes health data, education records, justice, child protection, disability and housing data. Conclusion SIDR provides a resource for whole-of-government policy development, service evaluation, academic research and social investment analytics for T120 and beyond. The SIDR distributed linkage model has potential for adaptation and use elsewhere.

Summary: Background: In 2015, an estimated 303 000 women died in pregnancy and childbirth. Obstetric haemorrhage, sepsis, and hypertensive disorders of pregnancy account for more than 50% of maternal deaths worldwide. There are effective treatments for these pregnancy complications, but they require early detection by measurement of vital signs and timely administration to save lives. The primary aim of this trial was to determine whether implementation of the CRADLE Vital Sign Alert and an education package into community and facility maternity care in low-resource settings could reduce a composite of all-cause maternal mortality or major morbidity (eclampsia and hysterectomy). Methods: We did a pragmatic, stepped-wedge, cluster-randomised controlled trial in ten clusters across Africa, India, and Haiti, introducing the device into routine maternity care. Each cluster contained at least one secondary or tertiary hospital and their main referral facilities. Clusters crossed over from existing routine care to the CRADLE intervention in one of nine steps at 2-monthly intervals, with CRADLE devices replacing existing equipment at the randomly allocated timepoint. A computer-generated randomly allocated sequence determined the order in which the clusters received the intervention. Because of the nature of the intervention, this trial was not masked. Data were gathered monthly, with 20 time periods of 1 month. The primary composite outcome was at least one of eclampsia, emergency hysterectomy, and maternal death. This study is registered with the ISRCTN registry, number ISRCTN41244132. Findings: Between April 1, 2016, and Nov 30, 2017, among 536 223 deliveries, the primary outcome occurred in 4067 women, with 998 maternal deaths, 2692 eclampsia cases, and 681 hysterectomies. There was an 8% decrease in the primary outcome from 79·4 per 10 000 deliveries pre-intervention to 72·8 per 10 000 deliveries post-intervention (odds ratio [OR] 0·92, 95% CI 0·86–0·97; p=0·0056). After planned adjustments for variation in event rates between and within clusters over time, the unexpected degree of variability meant we were unable to judge the benefit or harms of the intervention (OR 1·22, 95% CI 0·73–2·06; p=0·45). Interpretation: There was an absolute 8% reduction in primary outcome during the trial, with no change in resources or staffing, but this reduction could not be directly attributed to the intervention due to variability. We encountered unanticipated methodological challenges with this trial design, which can provide valuable learning for future research and inform the trial design of future international stepped-wedge trials. Funding: Newton Fund Global Research Programme: UK Medical Research Council; Department of Biotechnology, Ministry of Science & Technology, Government of India; and UK Department of International Development.

Introduction Businesses worldwide are increasingly adopting the storage, compute and analytical services provided by cloud computing. Yet, few operational linkage units are keeping pace with this world of technological change - most use legacy systems approaching their limits with the rapidly increasing size and range of datasets now required for linkage. Objectives and Approach To meet the demands of linkage for the near future, it is important that new solutions for linkage consider the services provided by public cloud infrastructure for compute, storage and analytics. We examined Platform as a Service (PaaS) offerings for use in the development of a cost-effective cloud model for scalable, privacy-preserving record linkage (PPRL). PPRL techniques were adapted to maximise the quality of linkage and to automate as much of the process as possible. Finally, a prototype was created to demonstrate the capabilities and potential of the model. Results We present our cloud model for PPRL, a platform for record linkage that provides rapid scaling of resources to meet demand, and the results of how our prototype performed on massive datasets. Conclusion/Implications The application of record linkage using relatively inexpensive cloud infrastructure represents a significant step towards providing an efficient and scalable record linkage service to researchers and government. Larger datasets can be linked efficiently, including national or cross-jurisdictional datasets, with little investment in private infrastructure, and improved turnaround times for researchers.

Introduction Privacy preserving record linkage (PPRL) using encoded or hashed data has potential to enable large-scale record linkage of previously inaccessible data. With limited real-world evaluation and implementation of PPRL at scale it is challenging for linkage practitioners to judiciously balance data protection with the accuracy and usability of linked datasets. Objectives and Approach We evaluated the performance of PPRL techniques using Bloom filters for linkage of data across primary and secondary care settings. This technique limits the need to disclose personal information for linkage activities. Primary care data included 272,202 records from 16 general practices in NSW. This was linked to 42.8 million records from a 7 year series of emergency presentations, hospitalisations and death registrations. For the purpose of evaluation, personal information was encoded within the data linkage centre. The quality of PPRL linkage was assessed against the true match status based on a gold standard probabilistic linkage using full personal identifiers. Results Compared to the gold standard probabilistic linkage using full personal identifiers, the PPRL techniques produced quality metrics of precision, recall and F measure in excess of 0.90. When configured to leverage pre-existing links between emergency department, hospital and mortality data, quality metrics around 0.98-0.99 were achieved. Lower rates of linkage quality were associated with missing demographic information and some residual variation in linkage quality across practices was observed. Conclusion/Implications PPRL using Bloom filters is a promising technique for achieving high quality linkage across primary and secondary care in Australia. Further evaluation will assess scalability and quality in Australia but international collaborations are encouraged to more rapidly develop the evidence base and tactical approaches to support real world implementations.

Introduction Record linkage units around the world use probabilistic linkage techniques for routine linkage of large datasets. It is widely known how probabilities are converted to agreement and disagreement weights for each field, yet there has been little exploration of the methodology to optimally convert field similarity scores into partial weights. Objectives and Approach String similarity comparators such as Jaro-Winkler are commonly used in traditional linkage, other comparators such as the Sorenson Dice coefficient, Jaccard similarity and Hamming distance are used in alternative privacy-preserving record linkage techniques. Determining partial weights to apply at each level of similarity is a non-trivial task. However, both types of linkages would greatly benefit from similarity to weight functions for each field that maximises the accuracy of the linkage. We evaluated several methods for computing partial agreement weights and applied these to synthetic datasets with varying levels of corruption. We then evaluated the methods on real administrative datasets. Results Exact comparisons can miss matches where typographical errors or misspellings produce small changes in value. Similarity comparisons can reduce the number of missed matches, but may also increase the number of incorrect matches. Various results of the partial agreement methods on Jaro-Winkler, Sorenson Dice coefficient, Jaccard similarity and Hamming distance comparators will be presented. A generic function to convert similarity values to weights, created from synthetic data, can be used on most datasets with a greatly improved result in linkage quality. However, maximising the linkage quality requires the creation of similarity-to-weight functions that are optimised for each dataset. Conclusion/Implications Accuracy in record linkage is vital for the correct analysis of linked data. It is even more critical in privacy-preserving record linkage where the ability for clerical review is limited. Optimised functions for converting similarities to partial weights can significantly improve the quality of linkage and should not be overlooked.

Introduction Record linkage is inherently uncertain, with all linkages containing some amount of false positive and false negative errors. Previous results have suggested that linkage error may not be evenly distributed throughout the population, with particular subgroups exhibiting higher rates of linkage error. Record linkage is inherently uncertain, with all linkages containing Objectives and Approach This study investigated the distribution of linkage error using four large-scale Australian administrative datasets; hospital admissions datasets from Western Australia and New South Wales, and emergency presentation datasets from New South Wales and South Australia. Each dataset had been previously de-duplicated to a very high standard, with large scale manual review taking place; these results were used as our truth set. Each dataset was linked using probabilistic record linkage with results (precision and recall) compared by gender, age, geographic indices of remoteness and socioeconomic status. Results Results were highly dataset dependent. Consistent findings were lower linkage quality found for individuals living in remote locations, and lower linkage quality in those in the youngest category (those born after 1980). Some datasets showed lower linkage quality for females, for those in middle age as compared to the elderly, and for those with lower socioeconomic status. The differences in linkage quality found were typically small. Changes in threshold settings had generally no effect on the relationship between sociodemographic characteristics and linkage quality. Conclusion/Implications Linkage studies focussing on younger individuals and those in remote areas may have greater uncertainty regarding their results. Targeting efforts by linkage units may be required to ensure even distribution of linkage errors. Further research is required into investigating how linkage errors effect research outcomes.

ABSTRACT Objectives Linkage of “big data” can provide the answers to a variety of health questions that benefit the delivery of patient care, impact of policies, system planning and evaluation. In some jurisdictions, legal and operational barriers may prevent data linkage for research and system evaluation. Collaboration between international research institutions in Canada, Australia and Wales was formed at the Farr Institute International Conference in 2015. This partnership will test privacy-preserving record linkage (PPRL) techniques for linkage accuracy on real datasets held in a Canadian data repository. Approach Bloom filter PPRL techniques have been incorporated into a prototype linkage system. Evaluations on probabilistic linkage using Bloom filters method have shown potential for large-scale record linkage, performing both accurately and efficiently under experimental conditions. The prototype will be used to evaluate the Bloom filter PPRL techniques in 3 phases. Phase 1: 3 tests using simulated data relating to 20 million individuals will be matched to a sub-cohort of 1 million individuals. Phase 2: 100,000 people from hospital inpatient records will be matched to 18 million people in a health system registration file. These tests will inform whether the method can achieve high levels of privacy protection without negatively impacting performance and linkage quality. Performance indicators include match rate and processing efficiency based on record volumes. Results Linkage quality will be assessed by the number of true matches and non matches identified as links and non-links. This method will be evaluated using synthetic and real-world datasets, where the true match status is known. Initial performance testing linked a file of 3,000 records to 30,000 with a 100% match result. Subsequent test phases as above will continue to be evaluated and these results will be presented. Conclusion Completion of the phased tests will confirm the ability to link datasets while preserving privacy. This international collaboration will expand the utility of this prototype linkage system and expand the global knowledge bank focusing on PPRL methods in general. It will also inform how to adapt to local requirements by providing a solution to many common legal and administrative challenges.

ABSTRACT Objectives The grouping of record-pairs to determine which administrative records belong to the same individual is an important process in record linkage. A variety of grouping methods are used but the relative benefits of each are unknown. We evaluate a number of grouping methods against the traditional merge based clustering approach using large scale administrative data. Approach The research aimed to both describe current grouping techniques used for record linkage, and to evaluate the most appropriate grouping method for specific circumstances. A range of grouping strategies were applied to three datasets with known truth sets. Conditions were simulated to appropriately investigate one-to-one, many-to-one and ongoing linkage scenarios. Results Results suggest alternate grouping methods will yield large benefits in linkage quality, especially when the quality of the underlying repository is high. Stepwise grouping methods were clearly superior for one-to-one linkage. There appeared little difference in linkage quality between many-to-one grouping approaches. The most appropriate techniques for ongoing linkage depended on the quality of the population spine and the underlying dataset. Conclusions These results demonstrate the large effect that the choice of grouping strategy can have on overall linkage quality. Ongoing linkages to high quality population spines provide large improvements in linkage quality compared to merge based linkages. Procuring or developing such a population spine will provide high linkage quality at far lower cost than current methods for improving linkage quality. By improving linkage quality at low cost, this resource can be further utilised by health researchers.

ABSTRACT Objectives While record linkage has become a strategic research priority within Australia and internationally, legal and administrative issues prevent data linkage in some situations due to privacy concerns. Even current best practices in record linkage carry some privacy risk as they require the release of personally identifying information to trusted third parties. Application of record linkage systems that do not require the release of personal information can overcome legal and privacy issues surrounding data integration. Current conceptual and experimental privacy-preserving record linkage (PPRL) models show promise in addressing data integration challenges but do not yet address all of the requirements for real-world operations. This paper aims to identify and address some of the challenges of operationalising PPRL frameworks. Approach Traditional linkage processes involve comparing personally identifying information (name, address, date of birth) on pairs of records to determine whether the records belong to the same person. Designing appropriate linkage strategies is an important part of the process. These are typically based on the analysis of data attributes (metadata) such as data completeness, consistency, constancy and field discriminating power. Under a PPRL model, however, these factors cannot be discerned from the encrypted data, so an alternative approach is required. This paper explores methods for data profiling, blocking, weight/threshold estimation and error detection within a PPRL framework. Results Probabilistic record linkage typically involves the estimation of weights and thresholds to optimise the linkage and ensure highly accurate results. The paper outlines the metadata requirements and automated methods necessary to collect data without compromising privacy. We present work undertaken to develop parameter estimation methods which can help optimise a linkage strategy without the release of personally identifiable information. These are required in all parts of the privacy preserving record linkage process (pre-processing, standardising activities, linkage, grouping and extracting). Conclusions PPRL techniques that operate on encrypted data have the potential for large-scale record linkage, performing both accurately and efficiently under experimental conditions. Our research has advanced the current state of PPRL with a framework for secure record linkage that can be implemented to improve and expand linkage service delivery while protecting an individual’s privacy. However, more research is required to supplement this technique with additional elements to ensure the end-to-end method is practical and can be incorporated into real-world models.

ABSTRACT Objectives As privacy-preserving record linkage (PPRL) emerges as a method for linking sensitive data, efficient blocking techniques that help maintain high levels of linkage quality are required. This research looks at the use of a Q-gram Fingerprinting blocking technique, with Multibit Trees, and applies this method to real-world datasets. Approach Data comprised ten years of hospital and mortality records from several Australian states, totalling over 25 million records. Each record contained a linkage key, as defined by the jurisdiction, which was used to assess quality (i.e. used as a ‘gold standard’). Different parameter sets were defined for the linkage tests with a privacy-preserved file created for each parameter set. The files contained jurisdictional linkage key and a Cryptographic Long-term Key (the CLK is a Bloom filter comprising all fields in the parameter set). Each file was run through an implementation of the Q-gram Fingerprinting blocking algorithm as a deduplication technique, using different similarity thresholds. The quality metrics of precision, recall and f-measure were calculated. Results Resultant quality varied for each parameter set. Adding suburb and postcode reduced the linkage quality. The best parameter set returned an F-measure of 0.951. In general, precision was high in all settings, but recall fell as more fields were added to the CLK. We will report details for all parameter settings and their corresponding results. Conclusion The Q-gram Fingerprinting blocking technique shows promise for maintaining high quality linkage in reasonable time. Determining which fields to include in the CLK for the linkage of specific datasets is important to maximise linkage quality, as well as selecting optimal similarity thresholds. Developing new technology is important for progressing the implementation of PPRL in real-world settings.

ABSTRACT Objectives Record linkage is a powerful technique which transforms discrete episode data into longitudinal person-based records. These records enable the construction and analysis of complex pathways of health and disease progression, and service use. Achieving high linkage quality is essential for ensuring the quality and integrity of research based on linked data. The methods used to assess linkage quality will depend on the volume and characteristics of the datasets involved, the processes used for linkage and the additional information available for quality assessment. This paper proposes and evaluates two methods to routinely assess linkage quality. Approach Linkage units currently use a range of methods to measure, monitor and improve linkage quality; however, no common approach or standards exist. There is an urgent need to develop “best practices” in evaluating, reporting and benchmarking linkage quality. In assessing linkage quality, of primary interest is in knowing the number of true matches and non-matches identified as links and non-links. Any misclassification of matches within these groups introduces linkage errors. We present efforts to develop sharable methods to measure linkage quality in Australia. This includes a sampling-based method to estimate both precision (accuracy) and recall (sensitivity) following record linkage and a benchmarking method - a transparent and transportable methodology to benchmark the quality of linkages across different operational environments. Results The sampling-based method achieved estimates of linkage quality that were very close to actual linkage quality metrics. This method presents as a feasible means of accurately estimating matching quality and refining linkages in population level linkage studies. The benchmarking method provides a systematic approach to estimating linkage quality with a set of open and shareable datasets and a set of well-defined, established performance metrics. The method provides an opportunity to benchmark the linkage quality of different record linkage operations. Both methods have the potential to assess the inter-rater reliability of clerical reviews. Conclusions Both methods produce reliable estimates of linkage quality enabling the exchange of information within and between linkage communities. It is important that researchers can assess risk in studies using record linkage techniques. Understanding the impact of linkage quality on research outputs highlights a need for standard methods to routinely measure linkage quality. These two methods provide a good start to the quality process, but it is important to identify standards and good practices in all parts of the linkage process (pre-processing, standardising activities, linkage, grouping and extracting).

Background: The UK national diabetic eye screening (DES) programme invites diabetic patients aged > 12 years annually. Simple and cost-effective methods are needed to increase screening uptake. This trial tests the impact on uptake of two financial incentive schemes, based on behavioural economic principles. Objectives: To test whether or not financial incentives encourage screening attendance. Secondarily to understand if the type of financial incentive scheme used affects screening uptake or attracts patients with a different sociodemographic status to regular attenders. If financial incentives were found to improve attendance, then a final objective was to test cost-effectiveness. Design: Three-armed randomised controlled trial. Setting: DES clinic within St Mary’s Hospital, London, covering patients from the areas of Kensington, Chelsea and Westminster. Participants: Patients aged ≥ 16 years, who had not attended their DES appointment for ≥ 2 years. Interventions: (1) Fixed incentive – invitation letter and £10 for attending screening; (2) probabilistic (lottery) incentive – invitation letter and 1% chance of winning £1000 for attending screening; and (3) control – invitation letter only. Main outcome measures: The primary outcome was screening attendance. Rates for control versus fixed and lottery incentive groups were compared using relative risk (RR) and risk difference with corresponding 95% confidence intervals (CIs). Results: A total of 1274 patients were eligible and randomised; 223 patients became ineligible before invite and 1051 participants were invited (control, n = 435; fixed group, n = 312; lottery group, n = 304). Thirty-four (7.8%, 95% CI 5.29% to 10.34%) control, 17 (5.5%, 95% CI 2.93% to 7.97%) fixed group and 10 (3.3%, 95% CI 1.28% to 5.29%) lottery group participants attended. Participants offered incentives were 44% less likely to attend screening than controls (RR 0.56, 95% CI 0.34 to 0.92). Examining incentive groups separately, the lottery group were 58% less likely to attend screening than controls (RR 0.42, 95% CI 0.18 to 0.98). No significant differences were found between fixed incentive and control groups (RR 0.70, 95% CI 0.35 to 1.39) or between fixed and lottery incentive groups (RR 1.66, 95% CI 0.65 to 4.21). Subgroup analyses showed no significant associations between attendance and sociodemographic factors, including gender (female vs. male, RR 1.25, 95% CI 0.77 to 2.03), age (≤ 65 years vs. > 65 years, RR 1.26, 95% CI 0.77 to 2.08), deprivation [0–20 Index of Multiple Deprivation (IMD) decile vs. 30–100 IMD decile, RR 1.12, 95% CI 0.69 to 1.83], years registered [mean difference (MD) –0.13, 95% CI –0.69 to 0.43], and distance from screening location (MD –0.18, 95% CI –0.65 to 0.29). Limitations: Despite verification, some address details may have been outdated, and high ethnic diversity may have resulted in language barriers for participants. Conclusions: Those receiving incentives were not more likely to attend a DES than those receiving a usual invitation letter in patients who are regular non-attenders. Both fixed and lottery incentives appeared to reduce attendance. Overall, there is no evidence to support the use of financial incentives to promote diabetic retinopathy screening. Testing interventions in context, even if they appear to be supported by theory, is important. Future work: Future research, specifically in this area, should focus on identifying barriers to screening and other non-financial methods to overcome them. Trial registration: Current Controlled Trials ISRCTN14896403. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 5, No. 15. See the NIHR Journals Library website for further project information.

The move to digital is being accompanied by a huge rise in volumes of (born-digital) content and data. As a result the curation lifecycle has to be redrawn. Processes such as selection and evaluation for preservation have to be driven by automation. Manual processes will not scale, and the traditional signifiers and selection criteria in older formats, such as print publication, are changing. The paper will examine at a conceptual and practical level how preservation intelligence can be built into software-based digital preservation tools and services on the Web and across the network ‘cloud’ to create ‘smart’ storage for long-term, continuous data monitoring and management. Some early examples will be presented, focussing on storage management and format risk assessment.

To date many institutional repository (IR) software suppliers have pushed the IR as a digital preservation solution. We argue that the digital preservation of objects in IRs may better be achieved through the use of light-weight, add-on services. We present such a service – PRONOM-ROAR – that generates file format profiles for IRs. This demonstrates the potential of using third- party services to provide preservation expertise to IR managers by making use of existing machine interfaces to IRs.

The National Archives is developing a range of practical solutions to the active preservation of electronic records, using an extensible service-oriented architecture and a central technical registry (PRONOM). This paper describes TNA’s methodologies for characterisation, preservation planning, and preservation action, the technologies being adopted to implement them, and the role of PRONOM in supporting these services. It describes how this approach fits with international research programmes, and the types of preservation service which TNA may be able to provide externally in the future.

Introduction: The NeLH-PC (Primary Care National electronic Library for Health) was created as part of the NHS information strategy. It is designed to deliver knowledge to primary care. The rationale for developing this library as a knowledge management tool and where it sits within the science of knowledge management are described. Method: Focus groups were used to define the questions that arise in primary care that the NeLHPC should be seeking to answer. The Primary Care Library is subject to a cyclical programme of continuous improvement. Results: A site has been developed to meet users' needs and levels of expertise.NeLH-PC attracts from 500 000 to in excess of 800 000 hits per month. Conclusions: NeLH-PC provides an exemplar of how a limited range of knowledge management tools is utilised. More investment is needed if a broader range of tools is to be provided. Greater integration is required with educationalists and other information and knowledge services if the library's full potential is to be realised.

To explore the cross-sectional association between adiposity, mental well-being, and quality of life in extreme obese individuals entering a UK specialist weight management service prior to treatment commencement.The sample comprised 263 extreme obese individuals who were referred to the service as a result of having a body mass index (BMI) ≥40 kg/m2 or ≥35 kg/m2 with a co-morbid health condition. In a retrospective analysis, routinely collected baseline clinical examination data and self-report questionnaires (Impact of Weight on Quality of Life: IWQOL-Lite, EQ5D-3L, and Hospital Anxiety and Depression Scale: HADS) were analysed to examine the cross-sectional association between adiposity and quality of life.The sample was predominantly female (74.8%) with mean BMI 47.0±7.9 kg/m2. Increasing adiposity was significantly negatively associated with quality of life, with an increase of 1 BMI unit associated with decreases of 1.93 in physical function (95% CI -2.86 - -1.00, p

To date many institutional repository (IR) software suppliers have pushed the IR as a digital preservation solution. We argue that the digital preservation of objects in IRs may better be achieved through the use of light-weight, add-on services. We present such a service – PRONOM-ROAR – that generates file format profiles for IRs. This demonstrates the potential of using third- party services to provide preservation expertise to IR managers by making use of existing machine interfaces to IRs.

The National Archives is developing a range of practical solutions to the active preservation of electronic records, using an extensible service-oriented architecture and a central technical registry (PRONOM). This paper describes TNA’s methodologies for characterisation, preservation planning, and preservation action, the technologies being adopted to implement them, and the role of PRONOM in supporting these services. It describes how this approach fits with international research programmes, and the types of preservation service which TNA may be able to provide externally in the future.