bluuebunny/crossref_metadata_2025_split huggingface dataset:
Household Matching for the 2021 Census
Authors: Plachta Josie , Tomlin Charlie 
Published: November 2019

Matching households between the UK census and census coverage survey is an essential requisite to estimating census overcount and undercount. Census quality requirements are extremely high. In 2021, we will aim to produce outputs within a year of census day (previously this has been within 16 months). Clerical searching is very time-consuming, and so to meet these challenging timelines, we need to increase the automatic match-rate.
Matching is done at the household as well as person level. In 2011, automatic household linkage primarily used a derived ‘head of household’ alongside other household variables but issues with assigning the same HOH to a household on the census and CCS reduced the effectiveness of the method. To combat this, we have designed a method that combines the variables from the household itself with sets of individual person data and runs deterministic match-keys to match households. Following this, associative matching was applied to find some of the remaining households. The method used the households of matched people to produce candidate household matches for clerical review, a process substantially quicker than clerical searching.
Using the 2011 census as our test data where 264,882 matches were found (60% automatically), our new methods matched 94% of households through deterministic match-keys with a precision of 99.99%. An additional 3% were linked through association, 5% were sent for clerical matching, leaving only 1,600 (<0.001%) matches to be found through resource-heavy clerical searching.
Using match keys made up of sets of person data in addition to household variables, and associative matching from person data, we have been able to successfully increase the number of matches made automatically on test data from Census 2011. This will decrease the resources needed for clerical matching and searching in 2021 enabling us to meet shorter timelines and maintain higher quality.
What happens without population data? – The case of Ukraine
Authors: Molnár-Kovács Dorottya 
Published: November 2019

According to the recommendation of the United Nations, national censuses should be taken at least every 10 years, and countries across Africa, Asia, the Americas and Europe are usually fairly disciplined in following this instruction. True, some European countries, including Denmark, Finland, the Netherlands or Iceland have in the last 30 years replaced traditional census enumerations with maintaining precise administrative registers, Ukraine however, is not one of these countries. With its last census carried out in 2001, the largest entirely European country is similar in this regard to countries such as Uzbekistan, Iraq or Sri Lanka.
Because there is no reliable source of population data in Ukraine, estimations from different organizations and individuals vary considerably. In 2019 the UN estimates Ukraine’s population to be 43.8 M (the 2001 census result was 48.7 M), while according to the State Statistics Service of Ukraine (Grosstat), the number is 42.1 M (1.7 Million difference). The picture gets more complicated when we look at non-official estimates by politicians, non-governmental organizations, foreign press and further, otherwise serious sources: calculations that consider the proto-states of the Donbass region and Crimea to be part of Ukraine get results of 30-35 M people, while without these regions, Ukraine’s population is calculated to be somewhere between 20-26 million. Looking at these numbers the only apparent conclusion one can arrive at is the incredible degree of uncertainty.
In a country where most families are in one way or another affected by permanent emigration, forced migration due to the war, seasonal work migration and the emigration of military-age men to avoid getting drafted, the population changes quickly. In my poster presentation I aim to showcase a number of different “creative” methods that official institutions in Ukraine use to get a picture of the actual population of the country and its regions, focusing mainly in Transcarpathia. These resourceful but often highly unreliable calculations include measuring bread consumption regionally and keeping count of the active mobile service users.
Pros and cons of using anonymised linked routine data to improve efficiency of randomised controlled trials in healthcare: experience in primary and emergency care
Authors: Snooks Helen , Watkins Alan , Jones Matthew , Khanom Ashrafunessa , Jones Jenna , Lyons Ronan A 
Published: November 2019

BackgroundThe use of anonymised routine linked data in designing and conducting randomised controlled trials (RCTs) has great potential. Sample sizes can be large, inclusion rates high and follow up periods prolonged, while the disruption to participants’ usual routines may be minimised. However, challenges and limitations in using routine linked data in RCTs remain.
Aims To describe, in primary and emergency settings, challenges and opportunities associated with designing and conducting RCTs using anonymised linked routine data to identify study participants and gather outcomes.
MethodsIn each of these trials we have used routine linked data as a key part of the research study design:
PRISMATIC (a stepped wedge trial of predictive risk stratification in primary care) utilised linked data outcomes related to emergency admissions to hospital, GP activity and outpatient appointments. Outcomes were included for 230,000 people registered to participating GP practices in the Swansea area
SAFER 2: a cluster randomised trial of referral to falls services by ambulance paramedics included linked data outcomes related to subsequent emergency episodes for 4,655 patients across three UK regions
TIME: feasibility trial of Take Home Naloxone randomised by city; routine linked data used to identify population for inclusion in follow up and outcomes
Regulatory processes - ethics, research and information governance permissions - have caused delay in each trial; inclusion rates have been much higher than is usual in RCTs (outcomes for >80% of eligible patients); large trials have been achievable at reasonable cost (each trial <£2,000,000). Questions remain about differences between self reported and routinely available outcomes; and between routine data outcomes collected prospectively and through the anonymised linked route.
ConclusionThere are clear benefits in using anonymised linked data outcomes in trials but further research is required to understand costs and limitations.
Defining Acute Kidney Injury Episodes
Authors: Davies Gareth , Scale Timothy , Akbari Ashley , Chess James , Lyons Ronan A 
Published: November 2019

BackgroundAcute Kidney Injury (AKI) is a common, serious condition effecting up to 20% of all hospital admissions in the UK. AKI has an agreed definition for its recognition, however there is no consensus for the duration of an AKI episode.
Main AimTo describe four different potential definitions of an AKI episode.
MethodWe identified AKI using an SQL (Structured Query Language) based algorithm (an implementation of the NHS England eAlert algorithm) applied to serum creatinine (SCr) results from a South Wales population of ~518,000 people, held in the Secure Anonymised Information Linkage (SAIL) Databank. Using a person’s index AKI case, we applied four different rules to define an episode of AKI. These definitions are: ALERTS - until they no longer trigger an AKI eAlert, 90 DAYS - until 90 days post first AKI test and <1.2/<1.5 until the SCr recovers to <1.2 or 1.5 times their baseline creatinine.
ResultsThere were 1,832,122 SCr tests in 340,908 people between 2011-2013, of which 93,843 were alerts (5.12%). This fell to 81,948 alerts in 21,979 patients when dialysis and transplant patients were excluded. Of these patients with AKI 7,792 (35.5%) were dead at 1 year after their first episode. There were 31,505, 33,759, 26,657, 34,904 episodes in patients by <1.2, <1.5, 90 Days and ALERTS definitions respectively.
ConclusionAKI episodes can be created in SAIL using SQL, and by adjusting the definition we see a variation in the number of episodes that a patient experiences. Once described, this cohort can be used to define a gold standard for AKI in future analysis.
Developing and evaluating national severity distributions for use in Burden of Disease studies: a case study of cancers in Scotland
Authors: Wyper Grant , Grant Ian , Fletcher Eilidh , McCartney Gerry , Stockton Diane 
Published: November 2019

BackgroundIncreasingly Burden of Disease (BOD) measures are being used to influence policy decisions because they summarise health loss in an equitable manner. An important part of producing non-fatal BOD estimates are severity distributions (SDs). The Global Burden of Disease (GBD) study use the same SDs across countries due to a lack of available data.
Aim To develop and assess the impact of national SDs compared with GBD worldwide severity distributions for 21 cancer types.
MethodsPatient-level records from the Scottish Cancer Registry for 21 cancers were obtained and linked to death registrations. We estimated prevalent cancer cases for 2016 and assigned each case to one of four phases (diagnosis and treatment; controlled; metastatic; and terminal) using GBD 2016 study definitions. SDs were calculated by considering relative proportions. The impact of choice of SDs was evaluated by comparing relative differences between weighted-average disability weights (DW) derived using GBD 2016 worldwide SDs with those derived from Scottish SDs.
ResultsFor the majority of cancers the most prevalent phase was the controlled phase, which contributed a higher proportion than the combined proportion from the other three phases across all cancers except mesothelioma. Differences in the composition of severity meant that most point-estimates of Scottish severity proportions were out-with the 95% uncertainty intervals. These differences resulted in overestimates of weighted-average DWs based on GBD 2016 worldwide SDs (17 out of 21 cancer types). The largest relative overestimates were for gallbladder and biliary tract cancer, oesophageal cancer and pancreatic cancer (71%, 32% and 31% higher respectively).
ConclusionThese findings illustrate a systematic bias introduced by using worldwide SDs. Current non-fatal BOD estimates should not be interpreted too precisely when comparing populations when they rely on data inputs from other countries. It is essential to ensure that any estimates are based upon country-specific data as far as possible.
Developing a training curriculum for researchers working with routine data: understanding professional and lay stakeholder priorities – The CENTRIC Study
Authors: Lugg-Widger Fiona , Munnery Kim , Townson Julia , Robling Mike 
Published: November 2019

BackgroundAnalysis of routine data makes an important contribution to service evaluation and research, providing cost-efficiencies, objective outcomes, burden reduction for patient and the public and is promoted by both policy and funders. Organisational, legal and ethical governance provide a framework for research but there is an onus on researchers to maintain their awareness of good practice when working with routine data.
Aim To co-produce with data provider, researcher and public stakeholders a training curriculum for researchers working with routine data.
Methods A curriculum for online and face-to-face training will be developed through consultations with three stakeholder groups. The first are researchers with existing interest /experience of using routine data. An online survey will be disseminated via UK research networks encompassing a range of disciplines and sectors. The non-probabilistic survey addresses current challenges, training experiences and learning preferences. Focus groups with three UK data provider organisations (SAIL, NHS Digital, National Pupil Database) will address provider’s experience of working with researchers, any training or support they either require, provide or sign-post to and opportunities to support best practice. Thirdly, a facilitated public consultation exercise using a deliberative enquiry process will be undertaken as a day’s workshop and include lay contributors identified via the HealthWise Wales cohort.
ResultsWe will present initial results from each stakeholder engagement activity and show how this has informed the draft training curriculum and our understanding of potential benefits that the training will deliver.
ConclusionsThe public may remain largely unaware of data captured when using public services, how it may contribute to research and the protections that apply. Involving the public in the development of researcher training informs this process and enables researchers to more effectively engage with patients and participants. Training will be promoted through data provider and research networks across sectors in the UK.
The potential of linking cohort participants to official criminal records: a pilot study using the Avon Longitudinal Study of Parents and Children (ALSPAC)
Authors: Teyhan Alison , Cornish Rosie , Boyd Andy , Macleod John 
Published: November 2019

BackgroundPolicing in the UK is increasingly taking a public health approach to tackling crime. Birth cohort studies are potentially well-placed to provide evidence on the most important risk and preventative factors. Linking official police records to cohort data offers considerable potential for future research, but data privacy concerns mean achieving such linkage is challenging. As a pilot, the Ministry of Justice provided ALSPAC with an anonymous extract (cannot be linked to study data) detailing consenting participants’ criminal convictions and cautions held within the Police National Computer (PNC).
Main AimTo use anonymised PNC data to inform the potential for future research using ALSPAC and individual-level linked crime data.
MethodsWe examine criminality (type, when and where committed) in the cohort participants who were sent for linkage to the PNC in 2013 when they were aged approximately 21 years (n=7358). We consider the representativeness of these participants by comparing their self-reported crime-related behaviours during adolescence to those of participants who did not consent to linkage (n=7604). Finally, we consider these self-reported measures by present-day crime linkage consent status.
ResultsOf those sent for PNC linkage, 885 were linked to a criminal record(s) comprising 2635 convictions and 1365 cautions. A third related to serious crimes, and >90% were committed in Avon and Somerset constabulary. Those sent for linkage self-reported fewer criminal behaviours than those not sent for linkage. Regarding present-day consent status, those who have explicitly opted-in generally self-report fewer criminal behaviours and have less missing data than those who have not responded to the consent campaign.
ConclusionIf future linkage to individual police records was only achieved for explicit consenters, this would under-estimate criminality in the cohort. The geographical clustering of the crimes means local police records, which are more detailed than those of the PNC, could also be used.
One-year readmission and Emergency department presentation after an epilepsy admission in people with intellectual disability: a registry-linkage study
Authors: Liao Peiwen , Reppermund Simone , Vajdic Claire , Trollor Julian N , Srasuebkul Preeyaporn 
Published: November 2019

Background with rationaleAlthough hospital admissions for epilepsy are common in people with intellectual disability (ID), little is known about the quality of inpatient care and outcomes after admission. To fill this gap, this project examines readmission, an important indicator for the quality of hospital care, and emergency department (ED) presentation after epilepsy admissions in people with ID compared to those without ID.
Main AimTo examine whether people with ID have a higher risk of all-cause readmissions and ED presentations after discharge from the index admission (i.e. first admission within the study period) for epilepsy than people without ID.
MethodsIn this retrospective data-linkage study, several linked administrative health datasets including but not restricted to hospital admissions, emergency department presentations, disability services and mental health ambulatory care are used to define the cohort, exposure and outcome. The cohort includes patients with and without ID who were admitted to hospital for epilepsy between 2002 and 2014 in New South Wales, Australia. The readmission rates and ED presentations within 28 days, 2-3 months, 4-6 months, and 7-12 months respectively will be compared between patients with and without ID. The effect of a diagnosis of ID on the risk of readmission and ED presentation within a year following the separation from the index admission will be estimated by Poisson regression.
Results and conclusionsThe demographics and comorbidity profile of participants at the index epilepsy admission will be presented. Readmission and ED presentation rates within each chunk of follow-up will be calculated by the status of ID and the incidence rate ratio will be provided to estimate the impact of ID on these outcomes. Findings will provide insight into how patients with ID and epilepsy fare in hospital care and help to guide future management of epilepsy in people with ID.
Overcoming the misrepresentation of disease burden associated with single aggregation choropleth maps through combining information from many aggregations
Authors: Tuson Matthew , Yap Matthew , Kok Mei Ruu , Boruff Bryan , Murray Kevin , Vickery Alistair , Turlach Berwin , Whyatt David 
Published: November 2019

BackgroundAccurate disease mapping based on spatiotemporal data is an important aspect of public health surveillance, targeting interventions, and health service planning. This is achieved by public health surveillance organisations around the world through the construction of choropleth maps based on single spatiotemporal aggregations of finer resolution data. However, such maps are undermined by their dependence on the spatiotemporal units used. This dependence is described by the related modifiable areal and temporal unit problems (MAUP; MTUP), also known as change of support problems (COSPs).
AimTo accurately map disease.
MethodsUsing ischaemic stroke admissions and mental health-related ED presentations in metropolitan Perth between 2013 and 2016 as exemplars, we present a novel zonation overlay approach for disease mapping. This method involves aggregating fine resolution spatial data numerous times instead of just once, using the automated zonation construction software AZTool.
Results Through implementing the zonation overlay method in combination with a rolling window of time, both the MAUP and the MTUP may be overcome in the context of disease mapping. Furthermore, the AZTool zonations act as a geographical encryption key, allowing fine resolution, precise maps to be constructed while protecting the privacy of individuals.
ConclusionHealth surveillance organisations continue to produce single aggregation choropleth maps of disease, without acknowledging their limitations except in rare cases. Producing such maps and suggesting they should guide policy makers, while being aware of but not acknowledging the impact of COSPs, could be described as scientific malfeasance. However, assuming that most researchers producing such maps are not intending to mislead, we must conclude that COSPs are poorly understood and their impact underestimated. The zonation overlay method we describe can help alleviate the consequences of this continued practice.
Development of an Injury Indicator Tool to Support Policy and Practice across Wales.
Authors: Turner Samantha L , Lyons Jane , Lyons Ronan A 
Published: November 2019

Background with rationaleInjury is a leading cause of premature mortality, morbidity and disability worldwide. In Wales, injuries result in approximately 3 deaths, 107 hospital admissions and 868 emergency department (ED) attendances every day. Health indicators are quantifiable measures designed to summarise a population’s health, and ultimately inform policy and practice. In 2017, several experts identified a need for injury indicators in Wales, to support injury surveillance and prevention efforts.
Main AimTo develop a suite of injury indicators, accessible to the public via an online tool, to inform policy and practice across Wales.
Methods/ApproachInjury specialists in the All Wales Injury Surveillance System (AWISS) proposed a list of measurable injury indicators, based on: data availability, major areas of interest from a Welsh Government strategy perspective, injuries contributing the greatest burden, and injuries for which effective interventions existed. A consultation process with experts and stakeholders resulted in 25 agreed indicators covering all-cause injuries, falls in older adults, hip fractures, road traffic injuries, injuries in the home and at leisure, burns and scalds, poisonings and intentional injuries. Anonymised, routinely collected ED data, inpatient and mortality data in the Secure Anonymised Information Linkage (SAIL) databank at Swansea University were used to generate indicator estimates. Estimates will be updated annually and are accessible via an online interactive tool.
ResultsThe development of a free, online injury indicator tool provides practitioners and policy makers across Wales, with the information required to make informed decisions. However, data quality issues hamper the extent to which conclusions can be made.
ConclusionsInjury indicators have the potential to inform policy and practice across Wales. The adoption of a simplified, standardised data collection system in EDs across Wales is recommended to improve data validity and reliability.
Prevalence three ways: Comparison of linked data from a patient register and electronic health records with allowance for linkage error
Authors: Doidge James , Morris Joan , Harron Katie , Stevens Sarah , Gilbert Ruth 
Published: November 2019

Background with rationalePatient registers and electronic health records are both valuable resources for disease surveillance but can be limited by variation in data quality over time. Variation may stem from changes in data collection methods, in the accuracy or completeness of clinical information, or in the quality of patient identifiers and the linkage that relies on these.
Main AimBy linking the National Down Syndrome Cytogenetic Register (NDSCR) to Hospital Episode Statistics for England (HES), we aimed to assess the quality of each and establish a consistent approach for analysis of trends in prevalence of Down’s syndrome among live births in England.
Methods/ApproachProbabilistic record linkage of NDSCR to HES for the period 1998–2013, supported by linkage of babies to mothers within HES. Comparison of prevalence estimates in England using NDSCR only, HES data only, and linked data. Capture-recapture analysis and quantitative bias analysis were used to account for potential errors, including false positive diagnostic codes, unrecorded diagnoses, and linkage error.
ResultsAnalyses of single-source data indicated increasing live birth prevalence of Down’s syndrome, particularly steep in analysis of HES. Linked data indicated a contrastingly stable prevalence of 12.3 cases per 10,000 live births, with a plausible range of 11.6–12.7 cases per 10,000 live births allowing for potential errors.
Conclusion Case ascertainment in NDSCR improved slightly over time, creating a picture of slowly increasing prevalence. The emerging epidemic suggested by HES primarily reflects improving linkage within HES (assignment of unique patient identifiers to hospital episodes). Administrative data are valuable but trends should be interpreted with caution, and with assessment of data quality over time. Linked data with quantitative bias analysis can provide more robust estimation and, in this case, reassurance that prevalence of Down’s syndrome is not increasing. Routine linkage of administrative and register data can enhance the value of each.