bluuebunny/crossref_metadata_2025 huggingface dataset:
Hubungan Kebiasaan Belajar Dan Motivasi Berprestasi Dengan Prestasi Belajar PKn
Authors: Gunawan I.M.E , Murda I.N. , Margunayasa I.G.
Published: November 2019

Penelitian ini bertujuan untuk mengetahui hubungan yang signifikan antarakebiasaan belajar dan motivasi berprestasi dengan prestasi belajar PKn siswakelas V SD Gugus I Kecamatan Pupuan Tahun Pelajaran 2018/2019. Jenispenelitian ini adalah penelitian ex post facto dengan analisis regresi sederhanadan regresi ganda. Populasi penelitian ini adalah seluruh siswa kelas V SDGugus I Kecamatan Pupuan yang berjumlah 118 siswa dengan jumlah sampel91 siswa. Data penelitian dikumpulkan dengan kuesioner kebiasaan belajar,kuisioner motivasi berprestasi dan pencatatan dokumen untuk data prestasibelajar PKn. Hasil penelitian menunjukkan bahwa: 1) terdapat hubungan yangpositif dan signifikan antara kebiasaan belajar dengan prestasi belajar PKn,dengan koefisien korelasi sebesar 0,671; 2) terdapat hubungan yang postif dansignifikan motivasi berprestasi dengan prestasi belajar PKn, dengan koefisienkorelasi sebesar 0,660; dan 3) secara bersama-sama terdapat hubungan yangpositif dan signifikan antara kebiasaan belajar dan motivasi berprestasi denganprestasi belajar PKn, dengan koefisien korelasi sebesar 0,658. Berdasarkanhasil penelitian, disimpulkan bahwa kebiasaan belajar dan motivasiberprestasi berhubungan dengan prestasi belajar PKn siswa.
Estimates of age-specific death rates and mortality risk using administrative pharmaceutical data
Authors: Purkiss Shaun , Keegel Tessa , Vally Hassan , Wollersheim Dennis
Published: November 2019

BackgroundEstimates of age-specific mortality rates and relative mortality risks are useful for a variety of health, actuarial and life insurance purposes. Mortality risk may also be associated with individual health service utilisation.

Main AimWe aimed to identify mortality events using pharmaceutical administrative data and quantify mortality rates and their relationship to levels of pharmaceutical health utilisation.

ApproachA publicly available Australian Pharmaceutical Benefits Scheme (PBS) database was employed for this study. For all individuals listed in the dataset the last recorded prescription exchange was used to define a proxy mortality event and health utilisation was quantified by the average number of prescriptions exchanged per year (ppy). Age-specific mortality rates were calculated from PBS data for a range of heath utilisation levels and used with Australian Bureau of Statistics (ABS) death rate data to estimate relative mortality risk.

ResultsThe age-specific population profile of 256 190 persons utilising PBS services closely correlated with Australian census data (r=0.97). Age specific PBS mortality rates calculated using proxy mortality events correlated well with ABS death rates for persons aged >45 years but correlated poorly in younger age groups. In these younger age cohorts PBS utilisation was associated with a high relative mortality risk, whereas for older persons aged mortality rates approached equivalence with ABS data.

Mortality rates were associated with use of the PBS. High PBS use (>20 ppy) was associated with poorer mortality rates whereas moderate PBS use (5-19 ppy) was associated with improved mortality as compared to persons using PBS minimally (<5 ppy) (p<.05).

ConclusionPharmaceutical administrative data can identify mortality events and provide estimates of mortality rates and relative mortality risks associated with health care use.
Incidence of drug-treated chronic diseases using administrative pharmaceutical data
Authors: Purkiss Shaun , Keegel Tessa , Vally Hassan , Wollersheim Dennis
Published: November 2019

Background Pharmaceutical data can be used to identify the presence of drug-treated chronic diseases (CD) in individuals using assigned World Health Organization Anatomic Therapeutic Chemical (ATC) classifications of medicines prescribed. ATC codes define treatment domains and provides a method to case define CD that has previously been used to estimate CD prevalence within populations.

Main Aim We determined selected CD incidence from an administrative pharmaceutical dataset, and compared them with published CD incidence results.

Approach An Australian Pharmaceutical Benefits Scheme (PBS) database covering the period 2003-14 was used for this study. The earliest prescriptions exchanged by individuals for an ATC defined CD were identified and the annual count recorded. These values were combined with Australian population census data to calculate the annual incidence of ATC defined CD. Australian PBS derived incidence estimates (PDI) were compared with published Australian and world incidence data.

Results The PDI of 16 chronic diseases were compared with incidence estimates using self-report surveys from the literature. Mean percentage differences between PDI estimates varied greatly when compared to survey data (mean 33% (SD ±79%). Diabetes (-29%), gout (4%), glaucoma (69%) and tuberculosis (14%) showed closer associations. In contrast, PDI estimates (n/1000/year) showed particularly high incidence levels as compared with self-report data for dyspepsia (16.9 v 4.5), dyslipidaemia (11.6 v 5.6) and respiratory illness (17.6 v 2.6).

Conclusion Incidence estimates of drug treated chronic disease can be obtained using pharmaceutical data and may be a useful source for a number of conditions. Some PDI differ considerably from survey data. The interpretation of PDI requires context on how a particular CD presents. Accuracy and relevance are likely to depend upon how drug treatments relate to the initial management of the chronic disease.
The New Brunswick COPD Health Information Platform
Authors: McDonald Ted
Published: November 2019

Background Chronic Obstructive Pulmonary Disease (COPD) afflicts one in five New Brunswick (NB), Canada residents aged 65+. The NB Institute for Research, Data and Training (NB-IRDT) has undertaken a project to develop an integrated COPD health information platform (CHIP) to study COPD in the NB population.

Aims The aims of the CHIP initiative are 1) identification and tracking of population level diagnoses of COPD in NB, and 2) advancement in the management of COPD at the system planning, research, clinical practice and patient levels.

Approach Unique in Canada, CHIP combines clinical and administrative data from multiple sources including all NB pulmonary function test laboratories (PFT). Clinics collect lung function test results, sociodemographic information, smoking and cessation, height, weight and other fields on everyone tested at a PFT. Since PFT data are not part of the NB electronic health record, data had to be assembled at each clinic. Data transfer required data sharing agreements, privacy impact assessments and disclosure schedules among Provincial Health Authorities, Department of Health and the University of New Brunswick.

Results Clinical data from 2007-2017 have been standardized and transferred to NB-IRDT from all PFT clinics in NB. More than 100,000 tests have been linked to patient data on hospitalizations, physician visits, vital statistics, and prescriptions. A research working group of researchers, clinicians, administrators and patients has identified key questions that are being analyzed using the CHIP data platform, including the extent to which individuals with COPD tested at a PFT are receiving appropriate treatment, and whether individuals treated for COPD have been tested.

Conclusion CHIP is a valuable tool to support research on COPD. Through identification of predictors and outcomes of COPD, CHIP will lead to improved prevention and treatment for NB residents and will generate valuable information transferrable to other jurisdictions.
Association between continuity of provider-adjusted regularity of general practitioner (GP) contact and diabetes-related hospitalisation: A data linkage study combining survey and administrative data
Authors: Moorin Rachael , Youens David , Preen David , Harris Mark , Wright Cameron
Published: November 2019

Background and rationale We have previously reported decreased rates and costs of diabetes-related hospitalisations with increasing regularity of general practitioner (GP) contact. However previous work has not adjusted for continuity of provider. Thus, despite the relevance for policy development, whether increased regularity is actually a proxy for, or a consequence of, increasing continuity of provider, or is a discrete facet of continuity of care is unknown.

Main Aim To assess the association between continuity of provider-adjusted regularity of GP contact and unplanned diabetes-related hospitalisation or emergency department (ED) presentation.

Methods/Approach This retrospective, cross-sectional study used linked administrative (from the Centre for Health Record Linkage & the Department of Human Services) and survey data from the baseline 45 and Up Study (2006-09 n=267,153) with a history of diabetes and at least two GP contacts (n=27,409). Multivariable zero-inflated negative binomial and two part generalised linear models were used to asses unplanned diabetes-related hospitalisations or ED presentations, associated costs and cumulative bed days.

Results Highest regularity of GP contact was associated with a lower probability (-0.28) of diabetes-related hospitalisation or ED presentations. For those with a previous hospitalisation or ED presentation, higher regularity was associated with a reduction in the number of hospitalisations or ED presentations (6 to 8%); bed days (30 to 44%); and average cost (23 to 41%). Importantly, continuity of provider did not significantly modify the effect of GP regularity for any outcome.

Conclusion Higher regularity of GP contact – that is more evenly dispersed, not necessarily more frequent care – has the potential to reduce health care costs and, for those with a previous hospitalisation, the time spent in hospital, irrespective of continuity of provider. These findings argue for the advocacy of regular care, as distinct from solely continuity of provider, when designing policy and financial incentives for GP-led primary care.
Linked government administrative data: Public or Private?
Authors: Stafford Joel
Published: November 2019

Background with rationaleIt is commonplace in policy discussions concerning administrative data linkage to presuppose that the data referred to is government services data. But this is not always the case. Much of the data public services hold is now collected via intermediaries, such as Non-Government Organisations, operating under service contracts with one or multiple government departments. Nor are these the only administrative data holdings applicable to clients of government services. There are also vast private administrative data holdings – including utility data, and consumer behaviour data.

Creating and amending legislation that governs public service practices in this domain is increasingly made complex when private companies partner with governments agencies on policy development and evaluation work.

Understanding the concept of public data for public good in light of this expanded sense of administrative data opens the door to deeper questions about the role linked data can play in government decision making.

Main aimThe paper problematizes how legislation governing the linking of government administrative data is scoped and discusses how public service work can be affected by the opaque communication networks that increasingly span the public-private sector divide.

Methods/ApproachAfter contextualising the challenge of legislating for administrative data linkage in the current work of the Office of the National Data Commissioner (ONDC) in Australia, this paper tests aspects of the proposed legislation against the extent to which it permits the possibility of ‘data laundering’.

ResultsThe presentation demonstrates the need for greater sophistication in the specification of data linkage and sharing legislation in service of the public good.

Conclusions This paper indicates that contemporary practices governing the linkage of government administrative data holdings is porous to the aims of extra-governmental organisations and may benefit by better incorporating legislative structures that govern private analytical services entities.
LINKAGE: Factors in selecting a data linkage approach
Authors: Jones Kerina , Ford David
Published: November 2019

Background The great benefits of linking health datasets for research in the public interest have long been demonstrated. More recently, we are seeing an increase in the availability of wider administrative data, such as employment, education and housing, to add new opportunities for population data science. However, there are challenges to be overcome in selecting a data linkage approach.

Main Aim We set out to examine various data linkage approaches, and to formulate some high level questions to inform decision-making.

Methods We used published literature to review various data linkage methods in theory and in practical settings. The study was commissioned by the UK Government Statistical Service and a key focus was privacy and confidentiality in data linkage.

Results The questions we formulated are based on: Legislative position; Information systems; Nature of datasets; Knowledge-base; Aims and purposes; Ground truth; and Environment.

Conclusion There are many factors influencing the selection of a data linkage approach. While not exhaustive, our set of questions covers some of the major ones. The findings of the study are being taken forward by UK Government Statistical Service and government departments to inform decision-making on options for data linkage research and the greater availability of their datasets.
iCoverT: A rich data source on the incidence of child maltreatment over time in England and Wales
Authors: Degli Esposti Michelle , Humphreys David K , Bowes Lucy
Published: November 2019

Background Child maltreatment is a major public health problem affecting one quarter of children in England and Wales. Good epidemiological data are needed to establish how many and which children are most at risk, and to evaluate the impact of policies and interventions. However, a comprehensive data source on child maltreatment is currently lacking.

Aim We aimed to create a rich data source on the incidence of Child maltreatment over Time (iCoverT) in England and Wales.

Methods We developed systematic methods to search and identify administrative data sources that regularly measured child maltreatment. Data sources were investigated and assessed against pre-specified eligibility criteria and a bespoke quality assessment tool. Relevant data were extracted, digitalised, and harmonised over time. All data and their accompanying documentation were prepared to form an open access data source: the iCoverT (osf.io/cf7mv).

Results We identified 13 unique sources of administrative data, six of which met our eligibility criteria: Child protection statistics, Children in care, Criminal statistics, Homicide index, Mortality statistics and NSPCC statistics. Data and documentation were prepared and combined to form the iCoverT, including 272 variables, over 43,500 data points, and spanning over 150 years. A subsequent time series analysis demonstrated the utility of the iCoverT; identifying large overall decreases in child maltreatment from 1858 to 2016 (e.g. 90% decrease in child homicides (2.7 per fewer per 100,000 children)) but worrying recent increases from 2000 to 2016.

Conclusion We systematically developed a rich data source on child maltreatment in England and Wales. Our methodology overcomes practical obstacles and offers a new approach for harnessing administrative data for research. Our resulting data source is a valuable public health surveillance tool, which can be used to monitor national levels of child maltreatment and to evaluate the effectiveness of child protection initiatives.
What happens after self-harm? An exploration of self-harm and suicide using the Northern Ireland Registry of Self-Harm
Authors: Maguire Aideen , Ross Emma , Tseliou Foteini , O'Hagan Denise , O'Reilly Dermot
Published: November 2019

Background Suicide is a major public health concern and Northern Ireland (NI) has the highest rate of both self-harm and suicide in the UK and Ireland. In order to target prevention strategies effectively, it is vital to understand who is most at risk.

Aim To explore the risk factors for completed suicide following presentation with self-harm.

Methods The Northern Ireland Registry of Self-Harm (NIRSH) collects information on all self-harm and suicide ideation presentations to all Emergency Departments in NI. NIRSH data from 2012-2015 was linked to centralised electronic data relating to primary care, prescribed medication and mortality records. Logistic regression was employed to quantify the likelihood of mortality with adjustment for factors associated with mental ill health and suicide risk, and Cox regression was used to explore which characteristics of those who self-harm are most associated with risk of suicide.

Results The cohort consisted of all 1,483,435 individuals born or resident in NI from 1st January 1970 until 31st December 2015 (maximum age in 2015, 45 years). During the follow-up period, 12,327 (0.8%) individuals presented with self-harm and 892 (0.1%) died by suicide. Rates of self-harm were equivalent for males and females with highest rates observed in the 18-24 years age group, and more common in deprived than affluent areas (OR=3.42, 95%CI 3,21, 3.65). Most individuals self-harmed via self-poisoning with psychotropic medications (71.5%), followed by self-injury with a sharp object (21.7%). Although only 162 (1.3%) of those who presented with self-harm went on to die by suicide, those who presented with self-harm were 24 times more likely to die by suicide compared to those who did not present with self-harm after adjustment for age and sex (HR=24.3, 95%CI 20.46,28.76).

Conclusion This constitutes the first population-wide study of self-harm in the UK and could be utilised to inform suicide prevention strategies.
The Secure Anonymised Information Linkage databank Dementia e-cohort (SAIL-DeC)
Authors: Schnier Christian , Wilkinson Tim , Orton Chris , North Laura , Rochford Ryan , Sudlow Cathie
Published: November 2019

Introduction Dementia Platform UK (DPUK) brings together over 50 different dementia-related cohorts. Most studies have restricted follow-up times and all are based on information from people who volunteer time and data for research. Participants are therefore often not representative of the 'wider population' and generalization of results is complicated. The Secure Anonymised Information Linkage databank (SAIL) holds long-time information on every person in Wales registered with the national health service, so generalization of study results is easier; however, data management and analysis of SAIL data is not trivial. We used data from SAIL to construct an easily accessible, well described dementia e-cohort.

Methods With some age restrictions, all Welsh residents for whom primary care data were available were included. Within SAIL, a table was created holding demographic information for every participant including follow-up times and several dementia indicators. Using validated diagnostic code lists, this table was linked to information on every dementia-related diagnostic event and several covariates and co-morbidites. SAIL-DeC can be modified according to varying study designs using annotated SQL-based scripts. Information on SAIL-DeC can easily be updated and linked to additional data on the SAIL database. Interactive visualisations effectively summarise cohort characteristics, aiding researchers to quickly determine cohort eligibility for dementia studies.

Results From 4.4 million participants in SAIL, 1.2 million met the cohort inclusion criteria, resulting in 18.8 million person-years of follow-up. Of these, 129,650 (10%) developed all-cause dementia during follow-up, with 77,978 (60%) having dementia subtype codes. Seventy-nine percent of participants who developed dementia died during follow-up. Median survival was 12.3 years for participants diagnosed with dementia when aged 50-60, 6.8 years when aged 60-70, 4.2 years when aged 70-80 and 2.4 years when aged 80-90.

Conclusions We have created a generalisable, national dementia e-cohort, aimed at facilitating epidemiological dementia research.
Examining the link between family health events and pupil performance in Wales
Authors: Murphy Phil , Brown Samuel
Published: November 2019

Background with rationale There is evidence of a strong relationship between health (and mother’s health) and early educational attainment. With access to administrative data this relationship can be explored to greater depth for the UK.

Main Aim To explore the effects of a pupil’s and their mother’s health (split into 22 categories) upon the pupil’s educational attainment through the use of administrative data.

Methods/Approach Health events were found through hospital admissions and then converted into the World Health Organisation’s ICD-10 health events. Two year lags were also created for these health events. Probit and ordered probit analyses were then used to explore the effects of these health events on a binary pass/fail core subject indicator and on a teacher assessed grade for Maths, Science and English. Analysis was split by gender and keystage.

Results Few of the health events affect the educational attainment of the pupil. The health of male pupils has little impact on education, with the mother’s health having a stronger impact. The mother’s past health events have the greatest impact upon the male pupil’s education. The male pupil’s past health effects keystage 2 pupils the most, with little effect for keystage 1 and 3 pupils. Female pupils’ health has little impact at keystage 1, with increasing importance at keystage 2 and 3. Mother’s health (including past health) seems to have the opposite effect, being more important at keystage 1 and less at keystage 2 and 3. The female pupil’s past health has a small but consistent impact across all keystages.

Conclusion By splitting health into ICD-10 categories, the health events that affect education have been more clearly identified. Most importantly, however, is the contribution of administrative data, allowing for in-depth analysis of health on education.
The Impact of School Exclusion on Educational Achievement: Evidence from English Administrative Data
Authors: McGovern Mark , McVicar Duncan , O’Reilly Dermot , Rowland Neil
Published: November 2019

Around 800,000 children experience exclusion from school every year in England, which can have significant and long-lasting effects, especially on educational achievement. Existing papers on the impact of school exclusion on children's outcomes mainly investigate the correlational relationship using US data. There is a lack of empirical evidence from other countries examining whether this relationship is causal. Longitudinal administrative data provide the ideal opportunity to test the hypothesis that children who are excluded go on to have lower educational achievement as a result.

This paper aims to measure the effect of exclusion in school-aged children. We use individual-level administrative data: the National Pupil Database (NPD) from school year 2004/05 to 2016/17. The NPD is maintained by the UK Department of Education and contains information on all pupils in state-funded schools in England. Detailed characteristics about the pupils and the schools are recorded. Student outcomes include the pupils'test scores, prior attainment, and progression at each Key Stage. In terms of school exclusion, we have detailed information on the time, school term when the exclusion occurred, and the type, reason and number of sessions for each exclusion.

To estimate the impact of school exclusion on the educational achievement of pupils, fixed effect models at individual level will be applied using the longitudinal dataset. We will control for the socio-economic characteristics of pupils, households and schools, for example age, gender, ethnic group, cohort, special education needs, location, siblings, school type, and other aggregate level characteristics. Having already conducted a comprehensive literature review, and with data expected to be available in September, we anticipate preliminary results this autumn.
Exploratory Research on the Health and Social Outcomes of Public Housing
Authors: Smith Mark , Hinds Aynslie , Prior Heather , Chateau Dan
Published: November 2019

BackgroundUnder the National Housing Strategy, the Canadian government will make historic investments in housing over the next decade. The Canadian Mortgage and Housing Corporation is leading a research strategy to evaluate the impact of these investments. As part of this initiative, the Manitoba Center for Health Policy is conducting a pilot study to determine whether administrative data can be used to assess impacts, specifically looking at health, education and involvement in the justice system.

ApproachUsing administrative data we tested for changes in healthcare use and justice involvement in the two years before and after a cohort of individuals moved into public housing. Additionally, to determine if changes in the outcomes over time were unique to public housing, we included a matched comparison group of individuals who did not reside in public housing. GLM with generalized estimating equations tested for differences over time and between cohorts in the number of hospitalizations, inpatient days, emergency department visits, and contacts with the criminal justice system. The data were modeled using a Poisson distribution (rate ratio, RR).

Results Compared to the matched cohort, individuals accepted into public housing showed a significant decline in number of hospitalizations (pre RR=1.58 (1.53, 1.63), post RR=1.23 (1.19, 1.27), days in hospital (pre RR=1.66 (1.64, 1.68), post RR=1.24 (1.23, 1.26) and visits to the emergency department (pre RR=1.57 (1.52, 1.62), post RR=1.42 (1.38, 1.47). A trend towards fewer involvements with the criminal justice system was also observed (pre RR=1.37 (1.32, 1.43), post RR=1.28 (1.22, 1.34). No significant differences were noted for total respiratory morbidity or high school grades.

ConclusionAdministrative data show good potential to be used for the evaluation of public housing impacts on a wide range of health and social outcomes. Additional indicator comparisons will be reported at the conference.
Measuring and explaining the changing nature of work - The Linked Personnel Panel enriched with administrative employment data (LPP-ADIAB)
Authors: Grunau Philipp , Haepp Tobias , Mackeben Jan , Ruf Kevin , Wolter Stefanie
Published: November 2019

In a rapidly changing world of work, policy-makers have new questions for evidence-based policy advice that go beyond what administrative data can provide. For example, the focus is on flexible forms of work or the permeability of the boundary between work and leisure time. Survey data can provide a good basis for answering these questions. In many respects, however, they do not come close to the representativeness and measuring accuracy of administrative data.

Here the combination of survey data with administrative data can help to get the best out of two systems. On the one hand, objective information about the population is available and on the other hand, the survey data contain much more detailed information on a variety of topics.

With the Linked Personnel Panel (LPP), the administrative data are used both for drawing a sample that is as undistorted as possible and for adjusting weighting factors. The LPP is a linked operational and employee data set that collects information on personnel instruments, corporate culture and work quality. Supplemented with the administrative data as LPP-ADIAB, we have advised policy makers on the relevance of home office for companies and employees. We know from the data of the employees whether their activity is suitable for home office. In the first step, these data are linked with the job information of the same employees from the administrative data. In the second step, we can transfer these values to the employees in Germany and estimate an undepleted homeoffice potential.

With the help of the LPP-ADIAB, we were able to show the limited effect of a right to homeoffice and thus provided a comprehensive picture in a discussion led by a small group of supporters.
A public health approach to reducing violence: Can data linkage help to reduce demand on blue light services?
Authors: McVie Susan , King Josiah
Published: November 2019

Scotland has witnessed a remarkable reduction in violent crime in recent years. In part, the success of this reduction has been attributed to a ‘public health’ approach, which includes improvements in partnership working across multiple agencies – especially law enforcement and public health. Nevertheless, the emergency services continue to deal with a high volume of violent incidents, an increasing number of which involve some aspect of underlying vulnerability. Policy makers are keen to understand more about how aspects of vulnerability impact on violent crime, especially as this is a primary driver for policies like the public health approach to reducing violence.

In a project that brings together stakeholders from the Scottish Government, Police Scotland and the Scottish Ambulance Service, the Scottish Centre for Administrative Data Research aims to examine patterns of ambulance callouts and/or hospital admissions involving people who experience violence. The study, which will link together a range of health datasets, will bring together data about violence-related incidents with wider information about an individual’s history of drug misuse, alcohol-related conditions and mental health problems. The study will also examine the extent to which violence and vulnerability contribute to increasing risk of premature death.

This paper will focus on the development of the research proposal and the opportunities and challenges of trying to bring together data from different emergency service organisations. If possible, it will present preliminary findings from the research. It is anticipated that this study will support the development of further violence prevention policies in Scotland, especially in terms of helping to identify opportunities for better partnership working and points of intervention that could reduce demand on blue light services to deal with violent incidents.
Strategies for centering equity and public engagement in the ethical use of integrated administrative data
Authors: Jenkins Adelia , Hawn Nelson Amy
Published: November 2019

Background with rationaleData integration is undertaken for the public good, yet institutions rarely address structural bias in their history, or the ways data are biased due to systemic inequities in the administration of policies and programs. Meanwhile, the public are rarely consulted in data use. Though data infrastructure can be a powerful tool to support equity-oriented reforms, equity is rarely a stated goal for data integration. This raises fundamental concerns, as integrated data increasingly provide the raw materials for evaluation, research, and risk modeling that inform policy, practice, and resource allocation.

Actionable Intelligence for Social Policy (AISP) is an initiative of the University of Pennsylvania that focuses on the development, use, and innovation of integrated data systems (IDS). We convene a network of IDS across the United States while supporting developing sites, and as such are uniquely situated to convene experts to develop guidance for centering equity within integrated data infrastructure.

Main AimThis project aims to generate guidance for agencies supporting data sharing infrastructure to ensure an emphasis on equity and public engagement for ethical use.

Methods/ApproachA variety of data collection methods are being used, including expert panel convenings and interviews with sites piloting or exemplifying strategies for public engagement and equitable data access and use. An extensive literature review is also in progress and will inform a suite of forthcoming products, including a white paper, communications and training materials.

ResultsThe results will provide strategies for centering equity across the spectrum of data integration activities, including inclusive governance, staffing considerations, decisions about data quality, and the ethical use of data models and algorithms. Initial findings indicate there are few exemplar sites that routinely center equity within data integration efforts, yet there are promising incremental steps that sites can take to ensure ethical use.

ConclusionWhile centering equity within data integration is an emerging focus, initial findings indicate the importance of such efforts, particularly in acknowledging and mitigating the risks of unacknowledged bias across use of administrative data for research and evaluation purposes.
Fuel Poverty Data Linking Project
Authors: Solomons Craiger , Lowe Sarah , Dixon Josh , Whiffen Tony , Bowen Rachel , Davies Matthew , Vine Hugo
Published: November 2019

Background with rationaleIn Wales, a household is considered to be in fuel poverty if it needs to spend more than 10% of its net income on maintaining a satisfactory heating regime. Addressing fuel poverty is particularly important to Wales with an estimated 29% of households in fuel poverty compared with 17% in the UK overall.

To tackle fuel poverty in Wales, the Welsh Government implemented two fuel poverty schemes. Warm Homes Nest is a demand-led scheme and Warm Homes Arbed an area-based scheme. Both schemes provide free home energy efficiency measures e.g. home insulation or boilers.

Main AimTo use linked administrative data to evaluate the impacts of Welsh Government home energy efficiency schemes for low income households. The findings will inform future fuel poverty schemes in Wales.

Methods/ApproachIndividual-level data from both schemes was anonymously linked to routine health records, using the SAIL (Secure Anonymised Information Linkage) Databank, to examine the health service use of recipients.

We used difference-in-difference estimations to compare any changes in the health of recipients before and after intervention with any concurrent change in health in those yet to receive an intervention.

ResultsResults published in 2017 indicated positive effects for the Nest scheme, including positive impacts on respiratory health and general health.

We will report results comparing the health impacts of the Arbed and Nest schemes. The study will be the first to directly compare the health impacts of a demand-led and an area-based energy efficiency scheme.

Conclusion Providing home energy efficiency interventions has the potential to benefit population health; however, there is a scarcity of evidence comparing different methods of implementing schemes. Our findings will inform more effectively focussed home energy efficiency schemes and potentially improve the health of people living in Wales.
The Nuffield Family Justice Observatory Data Partnership
Authors: Griffiths Lucy , Johnson Rhodri , Cusworth Linda , Akbari Ashley , Alrouh Bachar , Bedston Stuart , Harwin Judith , Jones Kerina , Smart Jonathan , Thompson Simon , Ford David , Broadhurst Karen
Published: November 2019

Background

Not enough is known about how the family justice system is working, the children and families using these services, and their wider outcomes beyond their involvement with the family court. The Nuffield Family Justice Observatory (FJO) Data Partnership, comprising a bespoke analysis platform hosted within the Secure Anonymised Information Linkage (SAIL) Databank and analytical teams at Lancaster and Swansea Universities, has been established to address this knowledge deficit.

MethodsFamily justice data is being deposited in the SAIL Databank. Data are acquired using a standardised split-file approach, stored in an anonymised format and made available to projects as linked data using a unique encrypted project anonymised linkage field. These data can be augmented with a wealth of available health, education and other governmental/social routinely collected datasets, and future data acquired from other sources, for a range of research projects.

ResultsChildren and Family Court Advisory and Support Service (Cafcass) Cymru data has been transferred to the SAIL Databank, and agreements to transfer the Cafcass England data are being finalised. Applications are now welcomed to use these data to enhance understanding of the family justice system and children and families involved with the family courts in public and private law. Access will be facilitated through the SAIL Databank, subject to relevant governance procedures.

ConclusionWe will discuss the rationale of the Nuffield FJO Data Partnership, and how it aims to a) increase capacity and capability of researchers and data scientists utilising family justice and other relevant administrative datasets, b) improve understanding about the family justice system using data from the Cafcass in England and Wales, c) demonstrate the complexities and value of data linkage, and d) assist future policy and practice development. We will discuss matching rates for the Cafcass Cymru data and linkages that have been made to other datasets within the SAIL Databank. We will also set out the support available from the partnership to those wishing to access and utilise family justice data.
Risk factors for young people not in education, employment or training (NEET) using the Scottish Longitudinal Study
Authors: Everington Dawn , Feng Zhiqiang , Ralston Kevin , Dibben Chris
Published: November 2019

BackgroundThe high level of young people not in education, employment or training (NEET) has been an important long-standing issue in Scotland. The experience of being NEET has long term detrimental effects.

Main AimIdentify risk factors that could inform interventions aimed at reducing the number of NEETs.

MethodsWe use the Scottish Longitudinal Study (SLS) which provides a 5.3% representative sample of Scotland’s population based around the Censuses of 1991, 2001 and 2011. The SLS includes Vital Event data, Census data for the SLS sample and also those living in the same household and, since 2007, school census data.

This allows us to study two cohorts of 16-19 year olds (the ages used in Scotland when considering NEET status) over a period of 10 years:

those 6-9 years old at the time of the 1991 Census to the 2001 Census when they were 16-19 years old

those 6-9 years old at the time of the 2001 Census to the 2011 Census when they were 16-19 years old

We used logistic regression to investigate whether NEET status is associated with individual, family and household characteristics measured 10 years previously and later data including school qualification, school behaviour, areal characteristics and teenage pregnancy.

ResultsThese analyses found several factors were associated with the likelihood of being NEET for both cohorts, including having no qualifications, teenage pregnancy and living in an area where there was a relatively high level of NEETs (100% census data). For the later cohort, school census data were available and school behaviour were important factors, whereas household characteristics at childhood were important factors for the earlier cohort.

ConclusionA number of factors are associated with NEET but those closer in time to the NEET ages of 16-19 appear to be more important than childhood factors.
U.S. Decennial Census Digitization and Linkage Project
Authors: Alexander Trent , Genadek Katie
Published: November 2019

The U.S. Census Bureau maintains a large longitudinal research infrastructure that currently includes linked data from the 1940 census, the 2000-2010 censuses, major national surveys going back to 1973, and administrative records dating back to the 1990s. These restricted data are accessible to researchers around the U.S. via the Federal Statistical Research Data Centers (FSRDC) network. The major shortcoming of this infrastructure is that it lacks linkable files from the decennial censuses of 1950 through 1990. Full-count microdata from these censuses are available for research, but datasets from these years do not include respondent names and therefore have not been linked over time. Respondent names for these censuses are available only via the original census returns, which are stored on 258,000 reels of microfilm.

The Decennial Census Digitization and Linkage project (DCDL) is an initiative to recover names from the 1960-1990 censuses and to produce linked restricted microdata files for research use. We describe the results of a pilot project we completed on the 1990 census. For that pilot, we created digital images from census microfilm, hand-keyed "truth data" from those images, supported two teams' attempts to conduct Handwriting Recognition on the images, appended recovered names to already-existing microdata files, and linked the new 1990 census microdata records to previous and subsequent censuses. We describe our processes, the accuracy of the Handwriting Recognition, and the accuracy of the record linkage with the recovered names. We conclude by providing an update on the recently-initiated project to carry out these processes on a production scale for the 1960 through 1990 censuses.

When combined with existing linkages between the censuses of 1940, 2000, 2010, the soon-to-be public 1950 census, and the future 2020 census, DCDL will provide the final component in a massive longitudinal data infrastructure that covers most of the U.S. population since 1940. As a multi-purpose statistical tool, the DCDL will further the U.S. Census Bureau's mission to provide high quality data on the U.S. population and support cutting-edge research in the FSRDC network. The resulting data resource will expand our understanding of population dynamics in the U.S. far beyond what is currently possible, providing transformational opportunities for research, education, and evidence-building across the social, behavioral, and economic sciences.
An outline framework for the efficient onward-sharing of linked Longitudinal Population Study and NHS Digital records.
Authors: Boyd Andy , Coleman Garry , Spence Estelle , Park Alison , Hardy Rebecca
Published: November 2019

BackgroundLongitudinal Population Studies (LPS) typically operate as data resources for global bona-fide research, and therefore routinely share data to inform new research investigations. Current data sharing agreements between LPS and NHS Digital generally do not permit the onward-sharing of linked health records beyond the LPS’s host institution or provide mechanisms to dynamically add new research hypotheses.

AimTo develop a framework of standardised onward-sharing models which control for risk and legal requirements and fit the context of different LPS.

ApproachThe CLOSER longitudinal consortium and NHS Digital held consultation meetings with 13 UK longitudinal studies, consortia studies and infrastructure providers to identify requirements and potential solutions.

ResultsFive onward-sharing models were identified. Two rely on the principle that anonymised data can be shared in a light-touch regulatory framework, and that this principle extends to ‘effectively anonymised’ data processed in line with the Information Commissioner’s Office (ICO) anonymisation code of practice. Three methods utilise differing permutations of contractual agreements in order to control for risk and enforce NHS Digital’s legal obligations. Establishing and maintaining these contractual arrangements will involve close working arrangements between the LPS and NHS Digital and further work is needed to clarify requirements for international data sharing. All models rely on the use of socio-technical controls used by LPS and infrastructure providers operating ‘Data Safe Haven’ approaches. Secure research facilities offered by national infrastructure providers – such as UK Secure eResearch Platform and UK Data Service – provide powerful risk control tools.

ConclusionThe identified models provide varied and flexible options for the onward-sharing of linked LPS and NHS Digital data. Greater clarity is needed in order to share effectively anonymised data and to share data internationally. There are opportunities for the LPS community to facilitate elements of these processes through partnership approaches.
Strengthening the use of administrative data to provide gender statistics
Authors: Pandolfelli Lauren , Carter Karen
Published: November 2019

The 2030 Agenda for Sustainable Development explicitly recognizes the critical role of gender data in monitoring progress toward all 17 Sustainable Development Goals (SDGs). Yet, gaps in gender data vis-à-vis availability, granularity, timeliness and adherence to international standards, compromise the ability of countries to design gender-responsive policies and meet the commitment enshrined in the SDGs to leave no one behind. Administrative data systems are increasingly recognized as an important source for filling gender data gaps, but there has been limited unpacking of what this means at a system level in terms of 1) prioritization, 2) restructuring data flows to ensure data can be appropriately disaggregated, 3) how data needs can be best supported within current systems structures, and 4) key opportunities for national statistical offices and gender specialists to engage administrative data systems.

The work aims to identify the specific opportunities, challenges and value of using administrative data more effectively to improve gender-equitable development outcomes; and translate this into practical guidance for national statistical offices and line ministries. While focused primarily on developing countries, the intent is to understand these elements across contexts and levels of system maturity.

Issues will be explored through literature review, key informant interviews from government and stakeholder groups, and detailed case studies for three countries at different levels of data system maturity. Work will be undertaken by UNICEF with support of the Inter-Agency and Expert Group on Gender Statistics (IAEG-GS). This body, comprising national statistical systems and international agencies, is the coordinating body of the United Nations Global Gender Statistics Programme.

Guidance developed through this work is anticipated to build on existing initiatives to improve cross-sectoral data for development and ensure we “leave no one behind” as we move forward to achieving the SDGs.