Using cross-sectoral data linkage to understand the health of people experiencing multiple exclusion

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
E Tweed ◽  
A Leyland ◽  
D Morrison ◽  
S V Katikireddi
Keyword(s):  
Administrative Data ◽  
Data Linkage ◽  
Support Service ◽  
Service Planning ◽  
Policy And Practice ◽  
Opioid Substitution Therapy ◽  
Case Register ◽  
Mortality And Morbidity ◽  
Individual Level ◽  
Future Policy

Abstract Background People affected by the intersection of homelessness, drug use, and/or serious mental illness have high rates of mortality and morbidity. However, they are often missed from routine information sources on population health, such as surveys and censuses. In many countries, administrative data are available which could help address this knowledge gap. We created a novel virtual cohort using cross-sectoral data linkage in order to inform policy and practice responses to these co-occurring issues. Methods Individual-level data from local authority homelessness services (HL), opioid substitution therapy dispensing (OST), and a psychosis case register (PSY) in Glasgow, Scotland between 2011-15 were confidentially linked to National Health Service records, using a mix of probabilistic and deterministic linkage. A de-identified dataset was made available to researchers through a secure analysis platform. Demographic characteristics associated with different exposure combinations were analysed using descriptive statistics. Results Linkage created a cohort of 24,767 unique individuals with any one of the experiences of interest between 2011-15. Preliminary results suggest that 89.2% of the cohort had one experience; 10.6% two; and 0.2% all three. The most common combination was HL & OST (n = 2,150; 8.7%), with other combinations much less frequent (HL & PSY, n = 279, 1.1%; OST & PSY, n = 188, 0.8%; HL & OST & PSY, n = 51, 0.2%). The odds of male gender increased with number of exposures (2 exposures, OR 2.1, 95% CI 1.9-2.2; 3 exposures, OR 4.1, 95% CI 2.3-7.2), but there was little difference in age. Work is ongoing to incorporate into the cohort additional datasets on criminal justice involvement. Lessons Administrative data linkage is a feasible approach to understanding the health of people affected by multiple exclusionary processes, but requires robust and timely governance. Our initiative can support service planning and evaluation of future policy or service changes. Key messages We describe the creation and characteristics of a novel virtual cohort of people affected by multiple exclusionary processes, using record linkage of administrative datasets. Cross-sectoral linkage has international potential for enhancing public health intelligence, especially for population groups who may be missed from surveys and censuses.

scholarly journals Green-Blue Spaces and Mental Health: A Longitudinal Data Linkage Study

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Daniel A Thompson ◽  
Mark Nieuwenhuijsen ◽  
James White ◽  
Rebecca Lovell ◽  
Mathew White ◽  
...  
Keyword(s):  
Mental Health ◽  
Administrative Data ◽  
Data Linkage ◽  
Well Being ◽  
Data Sources ◽  
Household Level ◽  
Individual Level ◽  
The Impact ◽  
Over Time ◽  
Sector Data

IntroductionA growing evidence base indicates health benefits are associated with access to green-blue spaces (GBS), such as beaches and parks. However, few studies have examined associations with changes in access to GBS over time. Objectives and ApproachWe have linked cross-sector data collected within Wales, United Kingdom, quarterly from 2008 to 2019, to examine the impact of GBS access on individual-level well-being and common mental health disorders (CMD). We created a longitudinal dataset of GBS access metrics, derived from satellite and administrative data sources, for 1.4 million homes in Wales. These household-level metrics were linked to individuals using the Welsh Demographic Service Dataset within the Secure Anonymised Information Linkage (SAIL) Databank. Linkage to Welsh Longitudinal General Practice data within SAIL enabled us to identify individual-level CMD over time. We also linked individual-level self-reported GBS use and well-being data from the National Survey for Wales (NSW) to routine data for cross-sectional survey participants. ResultsWe created a longitudinal cohort panel capturing all 2.84 million adults aged 16+ living in Wales between 2008 and 2019 and with a general practitioner (GP) registration. Individual-level health data and household-level environmental metrics were linked for each quarter an individual is in the study. Household addresses were linked to 97% of the cohort, creating 110+ million rows of anonymously linked cross-sector data. The cohort provides an average follow-up period of 8 years, during which 565,168 (20%) adults received at least one CMD diagnosis or symptom. Conclusion / ImplicationsThis example of multi-sectoral data linkage across multiple environmental and administrative data sources has created a rich data source, which we will use toquantify the impact of changes in GBS access on individual–level CMD and well-being. This evidence will inform policy in the areas of health, planning and the environment.

scholarly journals Assembly of the LongSHOT cohort: public record linkage on a grand scale

2019 ◽  
Vol 26 (2) ◽  
pp. 153-158 ◽  
Author(s):  
Yifan Zhang ◽  
Erin E Holsinger ◽  
Lea Prince ◽  
Jonathan A Rodden ◽  
Sonja A Swanson ◽  
...  
Keyword(s):  
Large Scale ◽  
Data Linkage ◽  
Careful Consideration ◽  
Mortality Data ◽  
Data Sets ◽  
Case Control Studies ◽  
Mortality And Morbidity ◽  
Individual Level ◽  
Large Scale Data ◽  
Matching Techniques

BackgroundVirtually all existing evidence linking access to firearms to elevated risks of mortality and morbidity comes from ecological and case–control studies. To improve understanding of the health risks and benefits of firearm ownership, we launched a cohort study: the Longitudinal Study of Handgun Ownership and Transfer (LongSHOT).MethodsUsing probabilistic matching techniques we linked three sources of individual-level, state-wide data in California: official voter registration records, an archive of lawful handgun transactions and all-cause mortality data. There were nearly 28.8 million unique voter registrants, 5.5 million handgun transfers and 3.1 million deaths during the study period (18 October 2004 to 31 December 2016). The linkage relied on several identifying variables (first, middle and last names; date of birth; sex; residential address) that were available in all three data sets, deploying them in a series of bespoke algorithms.ResultsAssembly of the LongSHOT cohort commenced in January 2016 and was completed in March 2019. Approximately three-quarters of matches identified were exact matches on all link variables. The cohort consists of 28.8 million adult residents of California followed for up to 12.2 years. A total of 1.2 million cohort members purchased at least one handgun during the study period, and 1.6 million died.ConclusionsThree steps taken early may be particularly useful in enhancing the efficiency of large-scale data linkage: thorough data cleaning; assessment of the suitability of off-the-shelf data linkage packages relative to bespoke coding; and careful consideration of the minimum sample size and matching precision needed to support rigorous investigation of the study questions.

scholarly journals Challenges and Principles to guide the linkage of government administrative data: Experiences from the Tassie Kids project

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Joel Stafford
Keyword(s):  
Administrative Data ◽  
Data Linkage ◽  
Design Principles ◽  
Data Sets ◽  
Personal Privacy ◽  
Policy And Practice ◽  
Key Policy ◽  
Linked Administrative Data ◽  
Data Design

Background with rationale An overarching concern influencing models of data linkage for public good is the maintenance of personal privacy. This concern is at times so strong that it prevents or slows the progress of achieving worthwhile linked administrative datasets across allied government departments, and even between distinct units within a single department. Where linkage has succeeded it has generally produced data sets that, by design, are difficult or impossible to re-identify, therefore meeting the requirement to guard privacy at the costs of the resulting data’s value to government decision makers. Main Aim The main aim of this paper is to convey criteria to inform data linkage policy and practice in government that maintains a central role for privacy, but which can better deliver on the promise of high value data for policy. Methods/Approach This paper is informed by the Tassie Kids project, a longitudinal linked administrative data study using an embedded researcher model underway in Tasmania, Australia. Among other outcomes, the project was designed to assist allied government agencies to identify key policy leverage points across multiple services. Using the Tassie Kids project as a case study this paper asks why allied departments don’t routinely link administrative data. Several important linked administrative data design principles are drawn from discussion of this question. Results The paper explains the practice implications of these design principles relevant to policy analysis and information management units in government. Conclusion The paper concludes with the suggestion that high value linked administrative data is data that maximises its representation of the dynamic mechanisms that affect the outcomes desired by government, while simultaneously minimising the data’s distance from its point of origin.

scholarly journals A Multi-level Review of Engineering Ethics Education: Towards a Socio-technical Orientation of Engineering Education for Ethics

2021 ◽  
Vol 27 (5) ◽  
Author(s):  
Diana Adela Martin ◽  
Eddie Conlon ◽  
Brian Bowe
Keyword(s):  
Engineering Education ◽  
Ethics Education ◽  
Engineering Ethics ◽  
Theoretical Research ◽  
Policy And Practice ◽  
Individual Level ◽  
Multi Level ◽  
Engineering Ethics Education ◽  
Four Levels ◽  
The Individual

AbstractThis paper aims to review the empirical and theoretical research on engineering ethics education, by focusing on the challenges reported in the literature. The analysis is conducted at four levels of the engineering education system. First, the individual level is dedicated to findings about teaching practices reported by instructors. Second, the institutional level brings together findings about the implementation and presence of ethics within engineering programmes. Third, the level of policy situates findings about engineering ethics education in the context of accreditation. Finally, there is the level of the culture of engineering education. The multi-level analysis allows us to address some of the limitations of higher education research which tends to focus on individual actors such as instructors or remains focused on the levels of policy and practice without examining the deeper levels of paradigm and purpose guiding them. Our approach links some of the challenges of engineering ethics education with wider debates about its guiding paradigms. The main contribution of the paper is to situate the analysis of the theoretical and empirical findings reported in the literature on engineering ethics education in the context of broader discussions about the purpose of engineering education and the aims of reform programmes. We conclude by putting forward a series of recommendations for a socio-technical oriented reform of engineering education for ethics.

scholarly journals A Bayesian approach to estimating the population prevalence of mood and anxiety disorders using multiple measures

2021 ◽  
Vol 30 ◽  
Author(s):  
Jordan Edwards ◽  
A. Demetri Pananos ◽  
Amardeep Thind ◽  
Saverio Stranges ◽  
Maria Chiu ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Anxiety Disorders ◽  
Administrative Data ◽  
Population Based ◽  
Accurate Estimate ◽  
Service Planning ◽  
Prevalence Estimate ◽  
Population Prevalence ◽  
Mood And Anxiety Disorders ◽  
Prevalence Estimates

Abstract Aims There is currently no universally accepted measure for population-based surveillance of mood and anxiety disorders. As such, the use of multiple linked measures could provide a more accurate estimate of population prevalence. Our primary objective was to apply Bayesian methods to two commonly employed population measures of mood and anxiety disorders to make inferences regarding the population prevalence and measurement properties of a combined measure. Methods We used data from the 2012 Canadian Community Health Survey – Mental Health linked to health administrative databases in Ontario, Canada. Structured interview diagnoses were obtained from the survey, and health administrative diagnoses were identified using a standardised algorithm. These two prevalence estimates, in addition to data on the concordance between these measures and prior estimates of their psychometric properties, were used to inform our combined estimate. The marginal posterior densities of all parameters were estimated using Hamiltonian Monte Carlo (HMC), a Markov Chain Monte Carlo technique. Summaries of posterior distributions, including the means and 95% equally tailed posterior credible intervals, were used for interpretation of the results. Results The combined prevalence mean was 8.6%, with a credible interval of 6.8–10.6%. This combined estimate sits between Bayesian-derived prevalence estimates from administrative data-derived diagnoses (mean = 7.4%) and the survey-derived diagnoses (mean = 13.9%). The results of our sensitivity analysis suggest that varying the specificity of the survey-derived measure has an appreciable impact on the combined posterior prevalence estimate. Our combined posterior prevalence estimate remained stable when varying other prior information. We detected no problematic HMC behaviour, and our posterior predictive checks suggest that our model can reliably recreate our data. Conclusions Accurate population-based estimates of disease are the cornerstone of health service planning and resource allocation. As a greater number of linked population data sources become available, so too does the opportunity for researchers to fully capitalise on the data. The true population prevalence of mood and anxiety disorders may reside between estimates obtained from survey data and health administrative data. We have demonstrated how the use of Bayesian approaches may provide a more informed and accurate estimate of mood and anxiety disorders in the population. This work provides a blueprint for future population-based estimates of disease using linked health data.

scholarly journals How to increase the value of self-reported health service data by using data linkage: a case study

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
W Peng ◽  
J Maguire ◽  
A Hayen ◽  
J Adams ◽  
D Sibbritt
Keyword(s):  
Data Collection ◽  
Health Service ◽  
Health Services ◽  
Stroke Prevention ◽  
Data Linkage ◽  
Recurrent Stroke ◽  
Service Planning ◽  
Stroke Survivors ◽  
Reported Data

Abstract Background This is a case study for recurrent stroke prevention. Lifestyle factors account for about 80% of the risk of recurrent stroke. Most health services studies examining stroke prevention rely on stroke survivors' self-reported lifestyle behaviour data. How can researchers increase the value of collected self-reported data to provide additional information for more comprehensive assessments? Methods 45 and Up Study is the largest ongoing study in the Southern Hemisphere focusing on the health of people aged 45 years and older living in NSW, Australia. This case study linked self-reported longitudinal lifestyle data in the 45 and Up Study, with corresponding mortality data (i.e. NSW Registry of Births, Deaths and Marriages & NSW Cause of Death Unit Record File) and hospital data (i.e. NSW Admitted Patient Data Collection) via the Centre for Health Record Linkage (CHeReL). The main outcome measures are health services, clinical outcomes, and mortality rates for stroke care. The analyses will include descriptive analysis, multivariate regression analysis, and survival analysis. Results A total of 8410 stroke survivors who participated in the 45 and Up Study were included in this data linkage study. From January 2006 to December 2015, 99249 hospital claims (mean: 13 times admission to hospital per person) and 2656 death registration records have been linked to these participants. The mean age of the stroke survivors was 72 (SD = 11) years, with 56% being males. These results are preliminary and more analyses will be conducted by using quality of life status, clinical diagnosis, comorbidities, and procedures. Conclusions Data linkage enables researchers to generate comprehensive findings on health services studies and gain a more holistic understanding of the determinants and outcomes of stroke prevention with lower data collection costs and less burden on participants. Key messages Data linkage brings about a new opportunity for self-reported data on health services utilisation. It is a cost-effective way to enhance existing self-reported data via the data linkage approach to increase its usefulness for informing health service planning.

Against evidence-based oppression: Marginalized youth and the politics of risk-based assessment and intervention

2016 ◽  
Vol 21 (2) ◽  
pp. 151-167 ◽  
Author(s):  
Tim Goddard ◽  
Randolph R Myers
Keyword(s):  
Lived Experience ◽  
Evidence Based ◽  
Marginalized Youth ◽  
Youth Justice ◽  
Policy And Practice ◽  
Individual Level ◽  
Needs Assessments ◽  
Actuarial Risk ◽  
The Individual ◽  
Causes Of Crime

Actuarial risk/needs assessments exert a formidable influence over the policy and practice of youth offender intervention. Risk-prediction instruments and the programming they inspire are thought not only to link scholarship to practice, but are deemed evidence-based. However, risk-based assessments and programs display a number of troubling characteristics: they reduce the lived experience of racialized inequality into an elevated risk score; they prioritize a very limited set of hyper-individualistic interventions, at the expense of others; and they privilege narrow individual-level outcomes as proof of overall success. As currently practiced, actuarial youth justice replicates earlier interventions that ask young people to navigate structural causes of crime at the individual level, while laundering various racialized inequalities at the root of violence and criminalization. This iteration of actuarial youth justice is not inevitable, and we discuss alternatives to actuarial youth justice as currently practiced.

scholarly journals A scoping review of considerations and practices for benefit sharing in biobanking

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Allan Sudoi ◽  
Jantina De Vries ◽  
Dorcas Kamuya
Keyword(s):  
Scoping Review ◽  
Health Research ◽  
Empirical Studies ◽  
Benefit Sharing ◽  
Cochrane Library ◽  
Policy And Practice ◽  
Online Databases ◽  
Expected Benefits ◽  
Future Policy ◽  
Distinct Features

Abstract Background Despite the rapid global growth of biobanking over the last few decades, and their potential for the advancement of health research, considerations specific to the sharing of benefits that accrue from biobanks have received little attention. Questions such as the types and range of benefits that can arise in biobanking, who should be entitled to those benefits, when they should be provided, by whom and in what form remain mostly unanswered. We conducted a scoping review to describe benefit sharing considerations and practices in biobanking in order to inform current and future policy and practice. Methods Drawing on the Arksey and O’Malley framework, we conducted a scoping review of the literature in three online databases (PubMed, Cochrane library, and Google Scholar). We extracted and charted data to capture general characteristics, definitions and examples of benefits and benefit sharing, justification for benefit sharing, challenges in benefit sharing, governance mechanisms as well as proposed benefit sharing mechanisms. Results 29 articles published between 1999 and 2020 met the inclusion criteria for the study. The articles included 5 empirical and 24 non-empirical studies. Only 12 articles discussed benefit sharing as a stand-alone subject, while the remaining 17 integrated a discussion of benefits as one issue amongst others. Major benefit sharing challenges in biobanking were found to be those associated with uncertainties around the future use of samples and in resultant benefits. Conclusion Most of the benefit sharing definitions and approaches currently in use for biobanking are similar to those used in health research. These approaches may not recognise the distinct features of biobanking, specifically relating to uncertainties associated with the sharing and re-use of samples. We therefore support approaches that allow decisions about benefit sharing to be made progressively once it is apparent who samples are to be shared with, the intended purpose and expected benefits. We also highlight gaps in key areas informing benefit sharing in biobanking and draw attention to the need for further empirical research.

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