Population Data Linkage Research Articles

Clomiphene Citrate Medication for Infertility and Risk of Stillbirth or Neonatal Death: A Population-based Cohort Study

Abstract Objective To assess associations between clomiphene citrate (CC) use and perinatal death. Design Whole of population data linkage cohort. Setting South Australia. Participants All women giving birth between July 2003 and December 2015 (n = 242,077). Methods All births of at least 20 weeks were linked to government records of dispensed medications. A pregnancy was considered exposed to CC if a prescription was dispensed from 90 days before through to the end of a conception window. Descriptive statistics for stillbirths and neonatal deaths were stratified by multiplicity. For singletons, multivariable logistic regression models were used to examine the association of CC exposure with the combined outcome of perinatal death. Main outcome measures Stillbirths and neonatal deaths (with 28 days of birth) combined as perinatal deaths. Results Among singletons, the prevalence of stillbirth was 6.6 per 1000 births, with neonatal deaths of 2.1 per 1000 live births. Among singletons conceived with CC, stillbirth and neonatal death had a prevalence of 10.2 and 3.1 per 1000, respectively. For the combined outcome of perinatal death, the odds ratio was 1.54 (95% confidence interval 1.15, 2.07), stable upon adjustment for factors conveying biological (eg, obesity, pregestational diabetes) and social (eg, disadvantage) risks for perinatal death. Conclusion Risk of perinatal death may be increased in pregnancies that follow use of CC. While established confounding factors related to infertility were taken into account, there may be some residual contribution of underlying infertility.

Potential for advances in data linkage and data science to support injury prevention research

The recent COVID-19 pandemic stimulated unprecedented linkage of datasets worldwide, and while injury is endemic rather than pandemic, there is much to be learned by the injury prevention community from...

Stimulant treatment for attention-deficit/hyperactivity disorder and risk of first and repeat criminal offending: a population data linkage cohort study

ObjectiveTo examine the effect of stimulant treatment on first and repeat criminal offending among children and young adults with attention deficit-hyperactivity disorder (ADHD). ApproachA population data linkage cohort study of individuals born in New South Wales (NSW), Australia in 1990-2005 and followed until May 2016. Individuals linked to stimulant treatment authorizations for ADHD in the NSW Ministry of Health controlled substance database were frequency matched (1:10) to controls without ADHD. Proven criminal offenses were linked from statewide court records. First and repeat offenses were examined separately using modified cox regression and Prentice, Williams, Peterson (PWP) models, respectively. ResultsThe cohort included 75,650 individuals with ADHD and 745,634 controls. A total of 59,658 individuals (7.3%) committed an offense and individuals with ADHD committed 3 times as many offenses. For all age and sex groups, the risk of a first offense was increased among individuals with ADHD but reduced by treatment (Males 10-17 years, untreated Hazard Ratio (HR) 2.02 95% confidence interval (CI) 1.95, 2.10, treated HR 1.52 95% CI 1.41, 1.62). The effect estimates were reduced for repeat offenses (Males 10-17 years, untreated HR 1.09 95% CI 1.05, 1.13, treated HR 0.97 95% CI 0.90, 1.04) with mixed results for the effect of treatment. ConclusionsIndividuals with ADHD had increased risk of offending, but stimulant treatment reduced the risk of first offenses. This association and benefit of treatment were reduced among prior offenders. ImplicationsAdequate treatment may help keep young people with ADHD out of the criminal justice system.

Factors impacting hospitalisation and related health service costs in cancer survivors in Australia: Results from a population data linkage study in Queensland (COS-Q).

The global economic cost of cancer and the costs of ongoing care for survivors are increasing. Little is known about factors affecting hospitalisations and related costs for the growing number of cancer survivors. Our aim was to identify associated factors of cancer survivors admitted to hospital in the public system and their costs from a health services perspective. A population-based, retrospective, data linkage study was conducted in Queensland (COS-Q), Australia, including individuals diagnosed with a first primary cancer who incurred healthcare costs between 2013 and 2016. Generalised linear models were fitted to explore associations between socio-demographic (age, sex, country of birth, marital status, occupation, geographic remoteness category and socio-economic index) and clinical (cancer type, year of/time since diagnosis, vital status and care type) factors with mean annual hospital costs and mean episode costs. Of the cohort (N = 230,380) 48.5% (n = 111,820) incurred hospitalisations in the public system (n = 682,483 admissions). Hospital costs were highest for individuals who died during the costing period (cost ratio 'CR': 1.79, p < 0.001) or living in very remote or remote location (CR: 1.71 and CR: 1.36, p < 0.001) or aged 0-24 years (CR: 1.63, p < 0.001). Episode costs were highest for individuals in rehabilitation or palliative care (CR: 2.94 and CR: 2.34, p < 0.001), or very remote location (CR: 2.10, p < 0.001). Higher contributors to overall hospital costs were 'diseases and disorders of the digestive system' (AU$661 m, 21% of admissions) and 'neoplastic disorders' (AU$554 m, 20% of admissions). We identified a range of factors associated with hospitalisation and higher hospital costs for cancer survivors, and our results clearly demonstrate very high public health costs of hospitalisation. There is a lack of obvious means to reduce these costs in the short or medium term which emphasises an increasing economic imperative to improving cancer prevention and investments in home- or community-based patient support services.

A protocol for neoWONDER: Neonatal whole population data linkage to improve long-term health and wellbeing of preterm and sick babies.

Early-life medical and surgical interventions in babies born preterm and/or with surgical conditions influence later life health and educational outcomes. Obtaining long-term outcomes post-discharge to evaluate the impact of interventions is complex, expensive, and burdensome to families. Linkage of routinely collected data offers a feasible and cost-effective solution. The NeoWONDER research programme aims to describe the short and long-term health and educational outcomes for babies born preterm and/or with surgical conditions and evaluate the impact of neonatal care and interventions on later health and educational outcomes. We will include babies who received care in neonatal units in England and Wales, born between 2007-2020 with a gestational age below 32 weeks (approximately 100,000), and/or born between 2012-2020 (all gestations) with any of six surgical conditions: necrotising enterocolitis, Hirschsprung's disease, gastroschisis, oesophageal atresia, congenital diaphragmatic hernia, and posterior urethral valves (approximately 8,000). A detailed list of surgical condition codes is shown in S3 File. We will obtain long-term health and education outcomes through linkage of the National Neonatal Research Database, which contains routine data for all babies admitted to NHS neonatal units, to other existing health and educational datasets. For England, these are: Hospital Episode Statistics, the Office for National Statistics, Mental Health Services Dataset, Paediatric Intensive Care Audit Network, National Pupil Database; and for Wales, the Secure Anonymised Information Linkage databank. Analysis will be undertaken on de-identified linked datasets. Outcomes of interest for health include mortality, hospital admissions, diagnoses indicative of neurodisability and/or chronic illness, health care utilisation; and for education are attainment (using national curriculum assessments), school absence and special educational needs status.

The effects of pre-eclampsia on social and emotional developmental vulnerability in children at age five in Western Australia: A population data linkage study

BackgroundIt is important to explore factors that may hinder early childhood development in AEDC Emotional Maturity and Social Competence domains as these underpin the foundation for health, well-being, and productivity over the life course. No previous study has examined whether, or to what extent, preeclampsia increases the risk of developmental vulnerability in social and emotional domains in early childhood. MethodsWe conducted a retrospective population-based cohort study on the association between preeclampsia and childhood developmental vulnerability in emotional maturity and social competence domains in children born in Western Australia in 2009, 2012 and 2015. We obtained records of births, developmental anomalies, midwives notifications and hospitalisations. These data were linked to the Australian Early Development Census (AEDC), from which developmental vulnerability in emotional maturity and social competence domains at a median age of 5 years was ascertained. Causal relative risks (RR) were estimated with doubly robust estimation. ResultsA total of 64,391 mother-offspring pairs were included in the final analysis. For the whole cohort, approximately 25 % and 23 % of children were classified as developmentally vulnerable or at-risk on AEDC emotional maturity and social competence domains, respectively. Approximately 2.8 % of children were exposed in utero to preeclampsia. Children exposed to preeclampsia were more likely to be classified as developmentally vulnerable or at-risk on the emotional maturity (RR = 1.19, 95%CI:1.11–1.28) and social competence domains (RR = 1.22, 95 % CI:1.13–1.31). ConclusionChildren exposed to pre-eclampsia in utero were more likely to be developmentally vulnerable in emotional maturity and social competence domains in this cohort. Our findings provide new insights into the harmful effect of preeclampsia on childhood developmental vulnerability.

Health of unpaid carers in Wales, UK: a population data linkage study.

The population of unpaid carers in Wales increased to record. There is no systematic approach to record unpaid caring status, resulting in limited quantitative evidence on unpaid carers' health. The aim of this study is to: (i) create an e-cohort of unpaid carers by linking routinely collected health and administrative datasets in Wales, UK. (ii) investigate whether long-term health conditions and multimorbidity are more prevalent amongst unpaid carers than non-carers. Unpaid carers were identified by linking primary care dataset, National Survey for Wales data with demographic characteristics in the Secure Anonymise Information Linkage Databank. The clinical codes identified in Cambridge Multimorbidity Score were used to explore the prevalence of long-term health conditions. A total of 91220 unpaid carers in Wales were identified between 1 January 2010 and 1 March 2022. Unpaid carers were found at higher risk of managing 35 of 37 long-term health conditions and multimorbidity than non-carers, exacerbated amongst younger age groups and deprived communities. The creation of the first e-cohort of unpaid carers in Wales provides opportunities to perform rapid analysis to systematically understand health needs and evaluate initiatives in future. To better support unpaid carers, flexible approaches focusing on early identification and prevention is crucial.

The impact of COVID-19 on opioid toxicity deaths for people who experience incarceration compared to the general population in Ontario: A whole population data linkage study

The impact of COVID-19 on opioid toxicity deaths for people who experience incarceration compared to the general population in Ontario: A whole population data linkage study

The impact of COVID-19 on opioid toxicity deaths for people who experience incarceration compared to the general population in Ontario: A whole population data linkage study.

To inform preparedness and population health action, we need to understand the effects of COVID-19 on health inequities. In this study, we assess the impact of COVID-19 on opioid toxicity deaths among people who experience incarceration compared to others in the general population in Ontario, Canada. We conducted a retrospective cohort study for the period of January 1, 2015 to December 31, 2020. We accessed and linked coronial data on all opioid toxicity deaths in Ontario with correctional data for people aged 18 years and older who were incarcerated in a provincial correctional facility. We used data from the Statistics Canada Census to calculate whole population rates. We used an interrupted time series design and segmented regression to assess for change in the level or rate of increase in deaths due to opioid toxicity coinciding with the COVID-19 pandemic. We compared the impact of COVID-19 on the opioid toxicity death rates for people exposed and not exposed to incarceration. Rates of opioid toxicity death increased with a linear positive slope in both persons exposed to incarceration and those not exposed over the study period. The start of COVID-19 measures coincided with a marked upward shift in the trend lines with modification of the effect of COVID-19 by both sex and exposure to incarceration. For persons exposed to incarceration, the risk ratio (RR) was 1.50 (95%CI 1.35-1.69) for males and 1.21 (95%CI 1.06-1.42) for females, and for persons not exposed to incarceration, the RR was 1.25 (95%CI 1.13-1.38) for males and not significant for females. COVID-19 substantially exacerbated the risk of opioid toxicity death, impacting males and females who experienced incarceration more than those who had not, with an immediate stepwise increase in risk but no change in the rate of increase of risk over time. Public health work, including pandemic preparedness, should consider the specific needs and circumstances of people who experience incarceration.

Social inequalities and long-term health impact of COVID-19 in Belgium: protocol of the HELICON population data linkage

IntroductionData linkage systems have proven to be a powerful tool in support of combating and managing the COVID-19 pandemic. However, the interoperability and the reuse of different data sources may...

Why and how we can use data linkage in oral health research: a narrative review.

Poor oral health, impacting health and wellbeing across the life-course, is a costly and wicked problem. Data (or record) linkage is the linking of different sets of data (often administrative data gathered for non-research purposes) that are matched to an individual and may include records such as medical data, housing information and sociodemographic information. It often uses population-level data or 'big data'. Data linkage provides the opportunity to analyse complex associations from different sources for total populations. The aim of the paper is to explore data linkage, how itis important for oral health research and what promise it holds for the future. This is a narrative review of an approach (data linkage) in oral health research. Data linkage may be a powerful method for bringing together various population datasets. It has been used to explore a wide variety of topics with many varied datasets. It has substantial current and potential application in oral health research. Use of population data linkage is increasing in oral health research where the approach has been very useful in exploring the complexity of oral health. It offers promise for exploring many new areas in the field.

Effect of the COVID-19 pandemic on incidence of long-term conditions in Welsh residents: a population linkage study

BackgroundThe COVID-19 pandemic had direct and indirect effects on health. Indirect effects on long term medical conditions (LTCs) are unclear. We examined trends in recorded incidences of LTCs and quantified differences between expected rates and observed rates from 2020 onwards. MethodsThis is a population data linkage study using primary and secondary care data within the Secure Anonymised Information Linkage Databank. We included data of Welsh residents diagnosed with any of 17 identified LTCs for the first time between Jan 1, 2000, and Dec 31, 2021. LTC's include mental health conditions, respiratory diseases, and heart conditions among others, generally chosen in line with the Quality and Outcomes Framework. The primary outcome was incidence rates (monthly number of new cases per 100 000 population). For each LTC, we did interrupted time series analysis of incidence rates from 2015 to 2021. Expected rates from between Jan 1, 2020, to Dec 31, 2021, were predicted using overall trends and seasonal patterns from the preceding 5 years and compared with observed rates. FindingsWe included 5 476 012 diagnoses from 2 257 992 individuals diagnosed with at least one LTC between Jan 1, 2000, to Dec 31, 2021. Across multiple long-term conditions, there was an abrupt reduction in observed incidence of new diagnoses from March to April 2020, followed by a general increase in incidence towards prepandemic rates. The conditions with the largest percentage difference between the observed and expected incidence rates in 2020 and 2021 were chronic obstructive pulmonary disease (38·4% lower than expected), depression (28·3% lower), hypertension (25·5% lower), and anxiety disorders (24·9% lower). The condition with the largest absolute difference between observed and expected incidence rates was anxiety disorders, with 830 per 100 000 less in 2020 and 2021 compared with observed rates. InterpretationThe reduction in incidence rates of LTCs suggests an underreporting of LTCs, especially during 2020 and early 2021. The emergence of these yet undiagnosed cases could result in a surge of new patients in the near future. FundingThis work was supported by the Wales COVID-19 Evidence Centre, funded by Health and Care Research Wales.

The impact of COVID-19 pandemic on trends in the recorded incidence of Long-Term Conditions identified from routine electronic health records between 2000 and 2021 in Wales: a population data linkage study.

BackgroundThe COVID-19 pandemic has resulted in delayed diagnosis and treatment for cancer patients and increases in elective surgery waiting lists. The impact on other ‘long-term’ conditions (LTCs) is unclear. We examined the effects of the pandemic on the recorded incidence of 20 LTCs to inform decisions on treatment pathways and resource allocation. ApproachWe included Welsh residents diagnosed with any of 20 LTCs for the first time between 2000-2021. Data were accessed and analysed within the Secure Anonymised Information Linkage (SAIL) Databank. The primary aim was to assess the impact of the COVID-19 pandemic on trends in recorded incidence. Secondarily we examined incidence by socio-demographic and clinical subgroups: age, sex, deprivation quintile, ethnicity, frailty score and learning disability. Incidence were presented as monthly rates for each LTC. We performed interrupted time series analyses to estimate; the immediate and long-term change in rates following the pandemic; and the size of the undiagnosed population. ResultsWe included 2,206,070 individuals diagnosed with at least one LTC. An immediate reduction in recording of new diagnoses was observed in April 2020 across all 20 LTCs, followed by a gradual recovery towards pre-pandemic levels over the next 18 months, though at different rates across conditions. The largest difference between observed and expected (as predicted using pre-pandemic trends) incidence between January 2020 and June 2021 were in the diagnoses of COPD (-43%, 95% CI (-50%, -34%)), Asthma, Hypertension and Depression and the smallest difference was in Type 1 diabetes, dementia, stroke and TIA (-8%, 95% CI (-19% ,5%)). Differences in the proportions of incidence by socio-demographic and clinical subgroups in the years preceding and following the pandemic have also been analysed (results to be finalised). ConclusionThere was an abrupt reduction in the observed incidence of all 20 LTCs after March 2020 followed by a gradual recovery over consequent months towards pre-pandemic levels. Of 20 LTCs, 15 strongly indicate a reservoir of yet undiagnosed patients. The results from this study will have implications in resource allocation.

Birthweight, gestational age and familial confounding in sex differences in infant mortality: a matched co-twin control study of Brazilian male-female twin pairs identified by population data linkage.

BackgroundIn infancy, males are at higher risk of dying than females. Birthweight and gestational age are potential confounders or mediators but are also familial and correlated, posing epidemiological challenges that can be addressed by studying male-female twin pairs.MethodsWe studied 28 558 male-female twin pairs born in Brazil between 2012 and 2016, by linking their birth and death records. Using a co-twin control study matched for gestational age and familial factors, we applied logistic regression with random effects (to account for paired data) to study the association between male sex and infant death, adjusting for: birthweight, within- and between-pair effects of birthweight, birth order and gestational age, including interactions. The main outcome was infant mortality (0–365 days) stratified by neonatal (early and late) and postneonatal deaths.ResultsMales were 100 g heavier and more at risk of infant death than their female co-twins before [odds ratio (OR) = 1.28, 95% confidence interval (CI): 1.11–1.49, P = 0.001] and after (OR = 1.60, 95% CI: 1.39–1.83, P <0.001) adjusting for birthweight and birth order. When adjusting for birthweight within-pair difference and mean separately, the OR attenuated to 1.40 (95% CI: 1.21–1.61, P <0.001), with evidence of familial confounding (likelihood ratio test, P <0.001). We found evidence of interaction (P = 0.001) between male sex and gestational age for early neonatal death.ConclusionsAfter matching for gestational age and familial factors by design and controlling for birthweight and birth order, males remain at greater risk of infant death than their female co-twins. Birthweight’s role as a confounder can be partially explained by familial factors.

The SEEDS of Indigenous population health data linkage.

IntroductionGlobally, the ways that Indigenous data are collected, used, stored, shared, and analyzed are advancing through Indigenous data governance movements. However, these discussions do not always include the increasingly sensitive nature of linking Indigenous population health (IPH) data. During the International Population Data Linkage Network Conference in September of 2018, Indigenous people from three countries (Canada, New Zealand, and the United States) gathered and set the tone for discussions around Indigenous-driven IPH data linkage.ObjectivesCentering IPH data linkage and research priorities at the conference led to budding discussions from diverse Indigenous populations to share and build on current IPH data linkage themes. This paper provides a braided summary of those discussions which resulted in the SEEDS principles for use when linking IPH data.MethodsDuring the Conference, two sessions and a keynote were Indigenous-led and hosted by international collaborators that focused on regional perspectives on IPH data linkage. A retrospective document analysis of notes, discussions, and artistic contributions gathered from the conference resulted in a summary of shared common approaches to the linkage of IPH data.ResultsThe SEEDS Principles emerge as collective report that outlines a living and expanding set of guiding principles that: 1) prioritizes Indigenous Peoples’ right to Self-determination; 2) makes space for Indigenous Peoples to Exercise sovereignty; 3) adheres to Ethical protocols; 4) acknowledges and respects Data stewardship and governance, and; 5) works to Support reconciliation between Indigenous nations and settler states.ConclusionEach of the elements of SEEDS need to be enacted together to create a positive data linkage environment. When implemented together, the SEEDS Principles can lead to more meaningful research and improved Indigenous data governance. The mindful implementation of SEEDS could lead to better measurements of health progress through linkages that are critical to enhancing health care policy and improving health and wellness outcomes for Indigenous nations.

Interpregnancy intervals and child development at age 5: a population data linkage study

ObjectiveTo investigate the associations between interpregnancy intervals (IPIs) and developmental vulnerability in children’s first year of full-time school (age 5).DesignRetrospective cohort study using logistic regression. ORs were estimated for associations...

Healthcare use and costs in the last year of life: a national population data linkage study

BackgroundPeople who are nearing the end of life are high users of healthcare. The cost to providers is high and the value of care is uncertain.ObjectivesTo describe the pattern, trajectory...

Association of peripheral artery disease and chronic limb-threatening ischemia with socioeconomic deprivation in people with diabetes: A population data-linkage and geospatial analysis.

The association between the prevalence and geographical distribution of peripheral artery disease (PAD) and chronic limb-threatening ischemia (CLTI) in patients with diabetes in the context of socioeconomic deprivation is not well understood. We undertook a retrospective cohort study of 76,307 people with diabetes admitted as a hospital inpatient in a large Scottish health administrative area. Utilising linked health records, we identified diagnoses of PAD and/or CLTI and their distribution using small area cartography techniques according to multiple deprivation maps. Spatial autocorrelation techniques were applied to examine PAD and CLTI patterning. Association between crude inpatient prevalence-adjusted outcome rates and exposure to social deprivation were determined. We found crude prevalence-adjusted rates of 8.05% for PAD and 1.10% for CLTI with a five- to sevenfold difference from the least to most deprived regions. Statistically significant hot spots were found for PAD (p < 0.001) and CLTI (p < 0.001) in the most deprived areas, and cold spots for PAD (p < 0.001) but not CLTI (p = 0.72) in the least deprived areas. Major health disparities in PAD/CLTI diagnoses in people with diabetes is driven by socioeconomic deprivation.

Planting the S.E.E.D.S of Indigenous Population Health Data Linkage

IntroductionThe increasing accessibility of data through digitization and linkage has resulted in Indigenous and allied individuals, scholars, practitioners, and data users recognizing a need to advance ways that assert Indigenous sovereignty and governance within data environments. Advances are being talked about around the world for how Indigenous data is collected, used, stored, shared, linked, and analysed.&#x0D; Objectives and ApproachDuring the International Population Data Linkage Network Conference in September of 2018, two sessions were hosted and led by international collaborators that focused on regional Indigenous health data linkage. Notes, discussions, and artistic contributions gathered from the conference led to collaborative efforts to highlight the common approaches to Indigenous data linkage, as discussed internationally. This presentation will share the braided culmination of these discussions and offer S.E.E.D.S as a set of guiding Indigenous data linkage principles.&#x0D; ResultsS.E.E.D.S emerges as a living and expanding set of guiding principles that: 1) prioritizes Indigenous Peoples’ right to Self-determination; 2) makes space for Indigenous Peoples to Exercise sovereignty; 3) adheres to Ethical protocols; 4) acknowledges and respects Data stewardship and governance, and; 5) works to Support reconciliation between Indigenous Peoples and settler states. S.E.E.D.S aims to centre and advance Indigenous-driven population data linkage and research while weaving together common global approaches to Indigenous data linkage.&#x0D; Conclusion / ImplicationsEach of the five elements of S.E.E.D.S interweave and need to be enacted together to create a positive Indigenous data linkage environment. When implemented together, the primary goals of the S.E.E.D.S Principles is to guide positive Indigenous population health data linkage in an effort to create more meaningful research approaches through improved Indigenous-based research processes. The implementation of these principles can, in turn, lead to better measurements of health progress that are critical to enhancing health care policy and improving health and wellness outcomes for Indigenous populations.

Enablers of Cross-Sectoral Data Linkage

IntroductionLinkage of cross-sectoral data can add value to health research but it can also present unique challenges and sensitivities. Objectives and ApproachA case series of cross-sectoral data linkage projects supported by a population data linkage centre from 2009 to 2019 were assessed for factors that may impede or delay data sharing and linkage. Each project was assessed against these factors - classified as technical, motivational, economic, political, legal, or ethical following a systematic review by Van Panhuis et al, 2019 and jurisdictional solutions over time were documented. A multivariable regression analysis was conducted to identify predictors of overall project timeframes. ResultsThe use of linked cross-sectoral data has increasing substantially over time. A progressive decrease in identified barriers to cross-sectoral data linkage was observed. Projects early in the case series were more likely to be accompanied by ethical, political or motivational barriers and in some cases significant delay. Later projects have tended to have shorter timeframes, be characterised by more extensive longitudinal cross-sectoral linked data from a larger number of datasets, and encounter, fewer delays associated with these barriers. Conclusion / ImplicationsBased on the findings of the qualitative analysis we have mapped the improvements and changes which are enablers of successful cross sectoral data linkages.