Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.2050
Shelley Gammon, R. Shipsey, Charlie Tomlin, Josie Plachta
In early 2020 there was intense media speculation that ethnicity and Covid-19 deaths were correlated. However, the existing method of adding ethnicity to death records resulted in low linkage rates for very recent deaths. We designed and implemented a bespoke linkage in three days enabling accurate reporting to the nation. We linked the 2011 England and Wales Census to death records using a range of personal identifiers. Due to time pressure, we focused on executing a single linkage method well. Deterministic linkage was chosen, using a variety of matchkeys which were tested via clerical review. To overcome the issue of addresses changing since 2011, we also linked 2020 death record residuals to the 2019 Patient Register (PR) and then made use of the 2011 PR address where it existed. This additionally provided an indication of whether unmatched death records might be attributable to migration into England and Wales post-2011. The prior linking method used NHS Number only. Although the overall linkage rate was approximately 90%, the rate for recent deaths (2nd March 2020 to 10th April 2020 in the first iteration of the linkage) was closer to 30% due to an administrative lag in adding NHS Numbers to death records. Our novel bespoke linkage method linked over 39,000 extra death records. Whilst this had minimal impact on the overall linkage rate, it improved the linkage rate for recent deaths to approximately 90%. This was without an impact on accuracy: clerical review demonstrated that the false positive rate was approximately 0.2%. A report was published using this data showing that the risk of death involving Covid-19 among some ethnic groups was significantly higher than others. Determining whether Covid-19 disproportionally affected certain ethnicities was of crucial importance in the early phase of the pandemic to enable appropriate government strategies to be developed. We delivered a bespoke linkage under an exceptional time-limit without compromising on accuracy, enabling this impactful analysis with nation-wide interest and impact.
{"title":"Bespoke automated linkage to enable analysis of covid deaths by ethnicity.","authors":"Shelley Gammon, R. Shipsey, Charlie Tomlin, Josie Plachta","doi":"10.23889/ijpds.v7i3.2050","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.2050","url":null,"abstract":"In early 2020 there was intense media speculation that ethnicity and Covid-19 deaths were correlated. However, the existing method of adding ethnicity to death records resulted in low linkage rates for very recent deaths. We designed and implemented a bespoke linkage in three days enabling accurate reporting to the nation. \u0000We linked the 2011 England and Wales Census to death records using a range of personal identifiers. Due to time pressure, we focused on executing a single linkage method well. Deterministic linkage was chosen, using a variety of matchkeys which were tested via clerical review. To overcome the issue of addresses changing since 2011, we also linked 2020 death record residuals to the 2019 Patient Register (PR) and then made use of the 2011 PR address where it existed. This additionally provided an indication of whether unmatched death records might be attributable to migration into England and Wales post-2011. \u0000The prior linking method used NHS Number only. Although the overall linkage rate was approximately 90%, the rate for recent deaths (2nd March 2020 to 10th April 2020 in the first iteration of the linkage) was closer to 30% due to an administrative lag in adding NHS Numbers to death records. Our novel bespoke linkage method linked over 39,000 extra death records. Whilst this had minimal impact on the overall linkage rate, it improved the linkage rate for recent deaths to approximately 90%. This was without an impact on accuracy: clerical review demonstrated that the false positive rate was approximately 0.2%. A report was published using this data showing that the risk of death involving Covid-19 among some ethnic groups was significantly higher than others. \u0000Determining whether Covid-19 disproportionally affected certain ethnicities was of crucial importance in the early phase of the pandemic to enable appropriate government strategies to be developed. We delivered a bespoke linkage under an exceptional time-limit without compromising on accuracy, enabling this impactful analysis with nation-wide interest and impact.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46706686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.1792
E. Jefferson, Aziz Sheik, S. Hopkins, P. Quinlan
ObjectivesCO-CONNECT is making UK COVID-19 data Findable, Accessible, Interoperable and Reusable (FAIR) through a federated platform, which supports secure, anonymised research at scale and pace. This interdisciplinary project, spanning 22 organisations, is connecting data from >50 large research cohorts and data collected through routine healthcare provision across the UK. ApproachAcross the UK, data has been collected that can help us answer key questions about COVID-19. As the data are in many places with many different processes it is difficult and complex for public health groups, researchers, policymakers, and government to find and access lots of high-quality data quickly and efficiently to make decisions. In collaboration with Health Data Research UK, CO-CONNECT is streamlining processes of accessing data for research. Results1) Discovering data and meta-analysis: CO-CONNECT enables researchers to determine how many people meet their research criteria within the various datasets across the UK through the Health Data Research Innovation Gateway Cohort Discovery tool e.g. “How many people in each dataset have had a PCR test which was positive and were under the age of 40?” Only summary level, anonymous data are provided so researchers can answer such questions rapidly without requiring multiple data governance permissions and directly contacting each data source. The tool also supports aggregate level meta-analysis of the data. 2) Detailed analysis: With data governance approvals, researchers can analyse detailed level, standardised, linked, pseudonymised data in a Trusted Research Environment. The common format reduces the effort on each research project, supporting rapid research. ConclusionProviding data in this de-identifiable, safe way enables rapid, robust research e.g., COVID-19 results from a test centre can be linked to hospital records along with prescriptions from pharmacies enabling researchers to understand whether people with different existing health conditions are more or less susceptible to COVID-19. If you want to know more visit https://co-connect.ac.uk.
{"title":"The COVID - Curated and Open aNalysis aNd rEsearCh plaTform (CO-CONNECT).","authors":"E. Jefferson, Aziz Sheik, S. Hopkins, P. Quinlan","doi":"10.23889/ijpds.v7i3.1792","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1792","url":null,"abstract":"ObjectivesCO-CONNECT is making UK COVID-19 data Findable, Accessible, Interoperable and Reusable (FAIR) through a federated platform, which supports secure, anonymised research at scale and pace. This interdisciplinary project, spanning 22 organisations, is connecting data from >50 large research cohorts and data collected through routine healthcare provision across the UK.\u0000ApproachAcross the UK, data has been collected that can help us answer key questions about COVID-19. As the data are in many places with many different processes it is difficult and complex for public health groups, researchers, policymakers, and government to find and access lots of high-quality data quickly and efficiently to make decisions. In collaboration with Health Data Research UK, CO-CONNECT is streamlining processes of accessing data for research.\u0000Results1) Discovering data and meta-analysis: CO-CONNECT enables researchers to determine how many people meet their research criteria within the various datasets across the UK through the Health Data Research Innovation Gateway Cohort Discovery tool e.g. “How many people in each dataset have had a PCR test which was positive and were under the age of 40?” Only summary level, anonymous data are provided so researchers can answer such questions rapidly without requiring multiple data governance permissions and directly contacting each data source. The tool also supports aggregate level meta-analysis of the data.\u00002) Detailed analysis: With data governance approvals, researchers can analyse detailed level, standardised, linked, pseudonymised data in a Trusted Research Environment. The common format reduces the effort on each research project, supporting rapid research.\u0000ConclusionProviding data in this de-identifiable, safe way enables rapid, robust research e.g., COVID-19 results from a test centre can be linked to hospital records along with prescriptions from pharmacies enabling researchers to understand whether people with different existing health conditions are more or less susceptible to COVID-19. If you want to know more visit https://co-connect.ac.uk.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47588335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.2005
E. Jefferson, Christian Cole, Alba Crespi i Boixader, Simon Rogers, Maeve Malone, F. Ritchie, Jim Q. Smith, Francesco Tava, A. Daly, J. Beggs, Antony Chuter
ObjectivesTo assess a range of tools and methods to support Trusted Research Environments (TREs) to assess output from AI methods for potentially identifiable information, investigate the legal and ethical implications and controls, and produce a set of guidelines and recommendations to support all TREs with export controls of AI algorithms. ApproachTREs provide secure facilities to analyse confidential personal data, with staff checking outputs for disclosure risk before publication. Artificial intelligence (AI) has high potential to improve the linking and analysis of population data, and TREs are well suited to supporting AI modelling. However, TRE governance focuses on classical statistical data analysis. The size and complexity of AI models presents significant challenges for the disclosure-checking process. Models may be susceptible to external hacking: complicated methods to reverse engineer the learning process to find out about the data used for training, with more potential to lead to re-identification than conventional statistical methods. ResultsGRAIMatter is: Quantitatively assessing the risk of disclosure from different AI models exploring different models, hyper-parameter settings and training algorithms over common data types Evaluating a range of tools to determine effectiveness for disclosure control Assessing the legal and ethical implications of TREs supporting AI development and identifying aspects of existing legal and regulatory frameworks requiring reform. Running 4 PPIE workshops to understand their priorities and beliefs around safeguarding and securing data Developing a set of recommendations including suggested open-source toolsets for TREs to use to measure and reduce disclosure risk descriptions of the technical and legal controls and policies TREs should implement across the 5 Safes to support AI algorithm disclosure control training implications for both TRE staff and how they validate researchers ConclusionGRAIMatter is developing a set of usable recommendations for TREs to use to guard against the additional risks when disclosing trained AI models from TREs.
{"title":"GRAIMatter: Guidelines and Resources for AI Model Access from TrusTEd Research environments (GRAIMatter).","authors":"E. Jefferson, Christian Cole, Alba Crespi i Boixader, Simon Rogers, Maeve Malone, F. Ritchie, Jim Q. Smith, Francesco Tava, A. Daly, J. Beggs, Antony Chuter","doi":"10.23889/ijpds.v7i3.2005","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.2005","url":null,"abstract":"ObjectivesTo assess a range of tools and methods to support Trusted Research Environments (TREs) to assess output from AI methods for potentially identifiable information, investigate the legal and ethical implications and controls, and produce a set of guidelines and recommendations to support all TREs with export controls of AI algorithms. \u0000ApproachTREs provide secure facilities to analyse confidential personal data, with staff checking outputs for disclosure risk before publication. Artificial intelligence (AI) has high potential to improve the linking and analysis of population data, and TREs are well suited to supporting AI modelling. However, TRE governance focuses on classical statistical data analysis. The size and complexity of AI models presents significant challenges for the disclosure-checking process. Models may be susceptible to external hacking: complicated methods to reverse engineer the learning process to find out about the data used for training, with more potential to lead to re-identification than conventional statistical methods. \u0000ResultsGRAIMatter is: \u0000 \u0000Quantitatively assessing the risk of disclosure from different AI models exploring different models, hyper-parameter settings and training algorithms over common data types \u0000Evaluating a range of tools to determine effectiveness for disclosure control \u0000Assessing the legal and ethical implications of TREs supporting AI development and identifying aspects of existing legal and regulatory frameworks requiring reform. \u0000Running 4 PPIE workshops to understand their priorities and beliefs around safeguarding and securing data \u0000Developing a set of recommendations including \u0000 \u0000suggested open-source toolsets for TREs to use to measure and reduce disclosure risk \u0000descriptions of the technical and legal controls and policies TREs should implement across the 5 Safes to support AI algorithm disclosure control \u0000training implications for both TRE staff and how they validate researchers \u0000 \u0000 \u0000 \u0000ConclusionGRAIMatter is developing a set of usable recommendations for TREs to use to guard against the additional risks when disclosing trained AI models from TREs.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49346277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.1859
Tanya Ravipati, N. Andrew, V. Srikanth, R. Beare
ObjectivesPublic health service organisations use multiple patient administration and electronic health record systems. We describe the implementation of a data warehouse automation tool within the National Centre for Healthy Ageing (NCHA) data platform to operationalise a research data warehouse to optimise data quality and data provision for health services research. ApproachThe traditional data warehouse life cycle comprises repetitive manual tasks and dependency on specialist developers. Automation tools overcome most of these inefficiencies. We conducted an internal risk benefit analysis which was validated by published literature containing data warehouse optimisation and automation. Industry-based data warehouse automation tools were reviewed to align the NCHA requirements with the tool’s functionality. Tools were then shortlisted and evaluated over a six-week period: (1) automation of standard tasks; (2) data pipeline alignment with the World Health Organization’s (WHO) Data Quality Review Framework; and (3) resource dependency risk mitigation through a Proof of Concept (PoC). ResultsThe priority areas identified by the risk benefit analysis included: end-to-end data warehouse automation; auto scripting; connectivity/linkage with multiple sources, reverse/forward engineering, audit trail conformance, scalability, multiple data warehouse architectures support, automated documentation; data management including data quality; and post-subscription independence. Twenty scientific publications were included in the final literature review (10% within healthcare) and supported the majority of identified priority areas. The industry-based review identified 11 suitable data warehouse/Extract-Transform-Load (ETL) automation tools. Five tools demonstrated adequate performance for task automation, data quality management, reduced dependency on specialist developers and on-premise linkage compatibility. Two automation tools were tested each for 6 weeks through PoC development. One automation tool met 8 out of the 10 automation requirements and was selected for implementation. ConclusionData warehouse development processes are complex and time consuming. Tools that offer automation of repetitive tasks and scripting increase the consistency while reducing the dependency on specialist staff. Integrated data quality management minimises the time researchers spend in pre-processing patient level data sourced through a semi-automated data warehouse.
{"title":"Challenges in public healthcare research data warehouse integration and operationalisation.","authors":"Tanya Ravipati, N. Andrew, V. Srikanth, R. Beare","doi":"10.23889/ijpds.v7i3.1859","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1859","url":null,"abstract":"ObjectivesPublic health service organisations use multiple patient administration and electronic health record systems. We describe the implementation of a data warehouse automation tool within the National Centre for Healthy Ageing (NCHA) data platform to operationalise a research data warehouse to optimise data quality and data provision for health services research. \u0000ApproachThe traditional data warehouse life cycle comprises repetitive manual tasks and dependency on specialist developers. Automation tools overcome most of these inefficiencies. We conducted an internal risk benefit analysis which was validated by published literature containing data warehouse optimisation and automation. Industry-based data warehouse automation tools were reviewed to align the NCHA requirements with the tool’s functionality. Tools were then shortlisted and evaluated over a six-week period: (1) automation of standard tasks; (2) data pipeline alignment with the World Health Organization’s (WHO) Data Quality Review Framework; and (3) resource dependency risk mitigation through a Proof of Concept (PoC). \u0000ResultsThe priority areas identified by the risk benefit analysis included: end-to-end data warehouse automation; auto scripting; connectivity/linkage with multiple sources, reverse/forward engineering, audit trail conformance, scalability, multiple data warehouse architectures support, automated documentation; data management including data quality; and post-subscription independence. Twenty scientific publications were included in the final literature review (10% within healthcare) and supported the majority of identified priority areas. The industry-based review identified 11 suitable data warehouse/Extract-Transform-Load (ETL) automation tools. Five tools demonstrated adequate performance for task automation, data quality management, reduced dependency on specialist developers and on-premise linkage compatibility. Two automation tools were tested each for 6 weeks through PoC development. One automation tool met 8 out of the 10 automation requirements and was selected for implementation. \u0000ConclusionData warehouse development processes are complex and time consuming. Tools that offer automation of repetitive tasks and scripting increase the consistency while reducing the dependency on specialist staff. Integrated data quality management minimises the time researchers spend in pre-processing patient level data sourced through a semi-automated data warehouse.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41317681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.1957
M. Chartier, G. Munro, D. Jiang, Scott C McCulloch, Wendy Au, M. Brownell, Rob Santos, F. Turner, Leanne Boyd, Nora Murdock, J. Bolton, J. Sareen
ObjectivesPAX, a mental health promotion approach, has been shown to decrease negative mental health outcomes and improve academic achievement. These effects have yet to be shown among Indigenous children. We evaluated PAX for improving First Nations children’s outcomes following a research process wherein community members and researchers work more collaboratively. ApproachBuilding on a long-term relationship with Swampy Cree Tribal Council, community members, First Nations leaders and researchers worked together through all phases of the project. This cluster randomized controlled trial used population-based health, social services, and education administrative data that allowed de-identified individual-level linkages across all databases through a scrambled health number. Our cohort of 725 children from 20 First Nations schools were randomized to PAX (n=469, 11 schools) or wait-list control (n=256, 9 schools). We used propensity score weighting and multi-level modeling to estimate the differences over time (2011 up to 2020) between children exposed to PAX and those who were not. ResultsDifferences in baseline characteristics were found between the two groups of children, despite the cluster randomization. After applying propensity score weights, children in the PAX group had significantly greater decreases in conduct problems (β:-1.08, standard error(se):0.2505, p<.0001), hyperactivity (β:-1.13, se:0.3617, p=.0018 ), and peer problems (β:-1.10, se:0.3043, p=.0003) and a greater increase in prosocial scores (β:2.68, se:0.4139, p<.0001) than control group children. The percentage of children in the PAX group who met academic expectations was higher than those in the control group, however, only grade 3 numeracy (odds ratio (OR):4.30, confidence interval (CI):1.34 – 13.77) and grade 8 reading and writing (OR:2.78, CI:1.01 – 7.67) met statistical significance. We found no evidence that PAX was associated with less emotional problems, diagnosed mental disorders or better student engagement. ConclusionThese findings suggest that PAX was effective in improving First Nations children’s mental health and academic outcomes in First Nations communities. Examining what works in Indigenous communities is crucial because approaches that are effective in some populations may not necessarily be culturally appropriate for remote Indigenous communities.
{"title":"Is PAX-Good Behaviour Game (PAX) Associated with Better Mental Health and Educational Outcomes for First Nations Children?","authors":"M. Chartier, G. Munro, D. Jiang, Scott C McCulloch, Wendy Au, M. Brownell, Rob Santos, F. Turner, Leanne Boyd, Nora Murdock, J. Bolton, J. Sareen","doi":"10.23889/ijpds.v7i3.1957","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1957","url":null,"abstract":"ObjectivesPAX, a mental health promotion approach, has been shown to decrease negative mental health outcomes and improve academic achievement. These effects have yet to be shown among Indigenous children. We evaluated PAX for improving First Nations children’s outcomes following a research process wherein community members and researchers work more collaboratively. \u0000ApproachBuilding on a long-term relationship with Swampy Cree Tribal Council, community members, First Nations leaders and researchers worked together through all phases of the project. This cluster randomized controlled trial used population-based health, social services, and education administrative data that allowed de-identified individual-level linkages across all databases through a scrambled health number. Our cohort of 725 children from 20 First Nations schools were randomized to PAX (n=469, 11 schools) or wait-list control (n=256, 9 schools). We used propensity score weighting and multi-level modeling to estimate the differences over time (2011 up to 2020) between children exposed to PAX and those who were not. \u0000ResultsDifferences in baseline characteristics were found between the two groups of children, despite the cluster randomization. After applying propensity score weights, children in the PAX group had significantly greater decreases in conduct problems (β:-1.08, standard error(se):0.2505, p<.0001), hyperactivity (β:-1.13, se:0.3617, p=.0018 ), and peer problems (β:-1.10, se:0.3043, p=.0003) and a greater increase in prosocial scores (β:2.68, se:0.4139, p<.0001) than control group children. The percentage of children in the PAX group who met academic expectations was higher than those in the control group, however, only grade 3 numeracy (odds ratio (OR):4.30, confidence interval (CI):1.34 – 13.77) and grade 8 reading and writing (OR:2.78, CI:1.01 – 7.67) met statistical significance. We found no evidence that PAX was associated with less emotional problems, diagnosed mental disorders or better student engagement. \u0000ConclusionThese findings suggest that PAX was effective in improving First Nations children’s mental health and academic outcomes in First Nations communities. Examining what works in Indigenous communities is crucial because approaches that are effective in some populations may not necessarily be culturally appropriate for remote Indigenous communities.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46963793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.1861
J. Lee, M. Brownell, T. Afifi, L. Turnbull, Marcelo L. Urquia, Nathan C. Nickel
ObjectiveThe objective was to examine the relationship between maternal intimate partner violence (IPV) victimization and children’s developmental health using linked population-wide administrative datasets. We examined developmental vulnerability (DV) at kindergarten of children exposed to maternal IPV victimization aged 0 to 5 using provincial prosecution records compared to unexposed counterparts. ApproachThis retrospective cohort study linked administrative datasets (legal, health, education, social services) from the Population Research Data Repository at the Manitoba Centre for Health Policy. Exposed mother-child pairs with 1+ prosecution records of maternal IPV victimization during early childhood (child aged 0 to 5) between 2003-2018 in Manitoba (n = 5,728) were matched to unexposed pairs (1:3) based on sex/birthdate of child and neighbourhood income. DV at kindergarten was measured across 5 domains (physical, social, emotional, language/cognitive [LC], communication/general knowledge) using the Early Developmental Instrument (EDI). Children without eligible EDI scores were excluded. Multiple logistic regression models were conducted. ResultsThe cohort included 5321 children (exposed n=1365, unexposed n=3956). 32.98% of the cohort was developmentally vulnerable in one or more domains (1/+) and 19.60% was developmentally vulnerable in two or more domains (2/+). Unadjusted relationships between maternal IPV victimization from age 0 to 5 and developmental vulnerability at kindergarten were statistically significant across all 5 domains (e.g., LC OR=2.76 [2.36, 3.23]) and in 1/+ (OR=2.72 [2.39, 3.09]) as well as 2/+ (OR=2.89 [2.51, 3.34]) domains. After adjusting for covariates, children who were exposed to maternal IPV victimization from ages 0 to 5 had increased odds of being developmentally vulnerable in social competence (aOR=1.33 [1.07, 1.66]) and emotional maturity (aOR=1.29 [1.03, 1.62]), also in 2/+ domains (aOR=1.42 [1.15, 1.73]) at kindergarten, compared to unexposed counterparts. ConclusionThe study provided Canadian population-wide evidence of the association between maternal IPV victimization and early childhood development, specifically later socio-emotional vulnerability. Interventions and support systems for this population of families should be developed and implemented, with an emphasis on mitigating long-term socio-emotional developmental risks in children exposed to IPV.
{"title":"Early Childhood Exposure to Intimate Partner Violence and Developmental Vulnerability at Kindergarten: Linking Canadian Population-Level Administrative Data.","authors":"J. Lee, M. Brownell, T. Afifi, L. Turnbull, Marcelo L. Urquia, Nathan C. Nickel","doi":"10.23889/ijpds.v7i3.1861","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1861","url":null,"abstract":"ObjectiveThe objective was to examine the relationship between maternal intimate partner violence (IPV) victimization and children’s developmental health using linked population-wide administrative datasets. We examined developmental vulnerability (DV) at kindergarten of children exposed to maternal IPV victimization aged 0 to 5 using provincial prosecution records compared to unexposed counterparts. \u0000ApproachThis retrospective cohort study linked administrative datasets (legal, health, education, social services) from the Population Research Data Repository at the Manitoba Centre for Health Policy. Exposed mother-child pairs with 1+ prosecution records of maternal IPV victimization during early childhood (child aged 0 to 5) between 2003-2018 in Manitoba (n = 5,728) were matched to unexposed pairs (1:3) based on sex/birthdate of child and neighbourhood income. DV at kindergarten was measured across 5 domains (physical, social, emotional, language/cognitive [LC], communication/general knowledge) using the Early Developmental Instrument (EDI). Children without eligible EDI scores were excluded. Multiple logistic regression models were conducted. \u0000ResultsThe cohort included 5321 children (exposed n=1365, unexposed n=3956). 32.98% of the cohort was developmentally vulnerable in one or more domains (1/+) and 19.60% was developmentally vulnerable in two or more domains (2/+). Unadjusted relationships between maternal IPV victimization from age 0 to 5 and developmental vulnerability at kindergarten were statistically significant across all 5 domains (e.g., LC OR=2.76 [2.36, 3.23]) and in 1/+ (OR=2.72 [2.39, 3.09]) as well as 2/+ (OR=2.89 [2.51, 3.34]) domains. After adjusting for covariates, children who were exposed to maternal IPV victimization from ages 0 to 5 had increased odds of being developmentally vulnerable in social competence (aOR=1.33 [1.07, 1.66]) and emotional maturity (aOR=1.29 [1.03, 1.62]), also in 2/+ domains (aOR=1.42 [1.15, 1.73]) at kindergarten, compared to unexposed counterparts. \u0000ConclusionThe study provided Canadian population-wide evidence of the association between maternal IPV victimization and early childhood development, specifically later socio-emotional vulnerability. Interventions and support systems for this population of families should be developed and implemented, with an emphasis on mitigating long-term socio-emotional developmental risks in children exposed to IPV.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43078214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.1805
D. Lopez, D. Preen, W. Raymond, C. Inderjeeth, K. Murray, H. Nossent, G. Dwivedi, H. Keen
ObjectivesCardiovascular disease is the largest contributor of increased mortality in patients with gout. Acute inflammation as seen with gout attacks may have a mechanistic role in developing Major Adverse Cardiovascular Events (MACE). We examined the temporal relationship between admission to hospital with acute gout and MACE. ApproachLinked inpatient and mortality data from the Western Australian Rheumatic Disease Epidemiology Registry were used. We identified patients with an incident acute gout (index) hospitalisation and admission or death records due to MACE (composite of acute coronary syndrome, stroke, heart failure, cardiovascular death). The risk of MACE during the index post-discharge period (1-30 days after index admission) and control period (365 days prior to index admission and 365 days post-discharge) was determined using a self-controlled case-series (SCCS) design. Conditional fixed-effects Poisson regression was used to obtain incidence rate ratios (IRR). Sensitivity analyses were performed excluding deaths and 180-day events. ResultsWe identified 962 patients (mean age=76.2 years [SD=12.2]; 66.8% male) with incident acute gout admission and documented MACE during the control and/or index post-discharge periods. 917 (95.3%) patients experienced MACE during the control period and 114 (11.9%) during the index post-discharge period. The rate of MACE during the control and post-discharge periods were 0.84 and 1.44 events per person-year, respectively, with an IRR=1.67 (95% CI: 1.38-2.02) for the post-discharge period compared with the control period from regression analysis. Sensitivity analyses excluding deaths and 180-day events were IRR=1.68 (95% CI=1.29-2.20) and IRR=1.66 (95% CI=1.34-2.07) respectively. ConclusionOur self-controlled case-series study using linked administrative data found an increased risk of MACE during the 30 days after discharge for index gout hospitalisation. This suggests a temporal association between acute inflammation and MACE.
{"title":"Risk of a major adverse cardiovascular event (MACE) following first-ever hospitalisation for acute gout: a Western Australian population-level linked data study.","authors":"D. Lopez, D. Preen, W. Raymond, C. Inderjeeth, K. Murray, H. Nossent, G. Dwivedi, H. Keen","doi":"10.23889/ijpds.v7i3.1805","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1805","url":null,"abstract":"ObjectivesCardiovascular disease is the largest contributor of increased mortality in patients with gout. Acute inflammation as seen with gout attacks may have a mechanistic role in developing Major Adverse Cardiovascular Events (MACE). We examined the temporal relationship between admission to hospital with acute gout and MACE. \u0000ApproachLinked inpatient and mortality data from the Western Australian Rheumatic Disease Epidemiology Registry were used. We identified patients with an incident acute gout (index) hospitalisation and admission or death records due to MACE (composite of acute coronary syndrome, stroke, heart failure, cardiovascular death). The risk of MACE during the index post-discharge period (1-30 days after index admission) and control period (365 days prior to index admission and 365 days post-discharge) was determined using a self-controlled case-series (SCCS) design. Conditional fixed-effects Poisson regression was used to obtain incidence rate ratios (IRR). Sensitivity analyses were performed excluding deaths and 180-day events. \u0000ResultsWe identified 962 patients (mean age=76.2 years [SD=12.2]; 66.8% male) with incident acute gout admission and documented MACE during the control and/or index post-discharge periods. 917 (95.3%) patients experienced MACE during the control period and 114 (11.9%) during the index post-discharge period. The rate of MACE during the control and post-discharge periods were 0.84 and 1.44 events per person-year, respectively, with an IRR=1.67 (95% CI: 1.38-2.02) for the post-discharge period compared with the control period from regression analysis. Sensitivity analyses excluding deaths and 180-day events were IRR=1.68 (95% CI=1.29-2.20) and IRR=1.66 (95% CI=1.34-2.07) respectively. \u0000ConclusionOur self-controlled case-series study using linked administrative data found an increased risk of MACE during the 30 days after discharge for index gout hospitalisation. This suggests a temporal association between acute inflammation and MACE.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43192361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.1784
Nishadi Kirelle, P. Christen, Garrett Eilidh
ObjectivesDemographers are interested in the degree to which marriage is driven by prenuptial pregnancy within particular communities. To help answer this question, we present a novel method which links marriage certificates to birth certificates, where the birth-mother is the marriage-bride, considering only births which occur in the first seven months after a marriage. ApproachTo identify prenuptial births we employed an unsupervised graph-based record linkage method to link birth and marriage certificates. We first extracted related groups of individuals: babies and their parents from birth certificates, and brides, grooms, and their parents from marriage certificates. To link births with marriages, we employed techniques to address challenges such as changing attribute values over time (such as names and addresses), the ambiguity of attribute values giving priority to rare names over common names, and different relationships encountered at different points in time (by applying temporal constraints). Based on the obtained links we then extracted prenuptial births. ResultsUsing two Scottish data sets containing a total of 38,451 births and 8,667 marriage certificates from the period 1861 to 1901 and employing different linkage thresholds we identified between 853 and 945 first birth-marriage links in the smaller (rural) data set, and between 2,165 and 2,232 links in the larger (urban) data set. In the rural data set, between 16.9% and 17.7% of these links were with birth less than 8 months after marriage (i.e. prenuptial births), where the corresponding ground truth contained 17.6% prenuptial births. For the urban data set, we identified between 51.3% and 51.4% prenuptial births. Our results show clear differences between rural and urban prenuptial pregnancies in 19th Century Scotland. ConclusionWe have presented an unsupervised graph-based record linkage method that compares attribute values of individuals and their relationships to link records based on the ambiguity of attribute values, attribute value changes, and temporal constraints. This linking process helps us to identify prenuptial births to help us understand the degree to which marriages may have been driven by pregnancy.
{"title":"Identifying prenuptial births from family pedigrees using record linkage.","authors":"Nishadi Kirelle, P. Christen, Garrett Eilidh","doi":"10.23889/ijpds.v7i3.1784","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1784","url":null,"abstract":"ObjectivesDemographers are interested in the degree to which marriage is driven by prenuptial pregnancy within particular communities. To help answer this question, we present a novel method which links marriage certificates to birth certificates, where the birth-mother is the marriage-bride, considering only births which occur in the first seven months after a marriage. \u0000ApproachTo identify prenuptial births we employed an unsupervised graph-based record linkage method to link birth and marriage certificates. We first extracted related groups of individuals: babies and their parents from birth certificates, and brides, grooms, and their parents from marriage certificates. To link births with marriages, we employed techniques to address challenges such as changing attribute values over time (such as names and addresses), the ambiguity of attribute values giving priority to rare names over common names, and different relationships encountered at different points in time (by applying temporal constraints). Based on the obtained links we then extracted prenuptial births. \u0000ResultsUsing two Scottish data sets containing a total of 38,451 births and 8,667 marriage certificates from the period 1861 to 1901 and employing different linkage thresholds we identified between 853 and 945 first birth-marriage links in the smaller (rural) data set, and between 2,165 and 2,232 links in the larger (urban) data set. In the rural data set, between 16.9% and 17.7% of these links were with birth less than 8 months after marriage (i.e. prenuptial births), where the corresponding ground truth contained 17.6% prenuptial births. For the urban data set, we identified between 51.3% and 51.4% prenuptial births. Our results show clear differences between rural and urban prenuptial pregnancies in 19th Century Scotland. \u0000ConclusionWe have presented an unsupervised graph-based record linkage method that compares attribute values of individuals and their relationships to link records based on the ambiguity of attribute values, attribute value changes, and temporal constraints. This linking process helps us to identify prenuptial births to help us understand the degree to which marriages may have been driven by pregnancy.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43211296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.1991
Elisa Jones, L. Frith, A. Chiumento, S. Rodgers, Alan Clarke, S. Markham
ObjectivesPublic involvement and engagement (PIE)) is playing an increasingly important role in big data initiatives and projects. It is therefore important to gain a deeper understanding of the different approaches used. ApproachThis study explores PIE using ethnographically-informed qualitative case studies. The case studies include: three citizen juries, each one carried out over eight days and that asked jurors to consider different real-world health data initiatives; and a public panel set up by a regional databank that carries out data linking. Data collection is ongoing and I will be continuing to carry out close observations of activities, and conducting semi-structured 1:1 interviews with those that organise and have taken part in the activities. ResultsData collection so far comprises completed observations at the citizen juries (~96 hours), ongoing observations of the public panel meetings (~15 hours), and thirty semi-structured 1:1 interviews with public contributors and other stakeholders about their experiences of the activities they were involved in. Early data analysis indicates key themes of: jurors feeling heard, but unsure whether anybody was listening; stakeholders being impressed by informed jurors, but raising concerns over contributors becoming too ‘expert’; how who is at the table and what information is presented impacts what is discussed; differences between online and in-person participation; and public involvement not being a substitute for informing the public about how their data is used. Conclusion‘Who’ is involved, and ‘how’ PPIE activities are designed and run can facilitate or constrain discussion, enhancing or limiting public contributions. If public involvement is to achieve its aims, including increasing trustworthiness, deeper consideration of these factors by those who seek the public’s views in their data projects is recommended.
{"title":"Public involvement in big data projects: an ethnographically-informed study.","authors":"Elisa Jones, L. Frith, A. Chiumento, S. Rodgers, Alan Clarke, S. Markham","doi":"10.23889/ijpds.v7i3.1991","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1991","url":null,"abstract":"ObjectivesPublic involvement and engagement (PIE)) is playing an increasingly important role in big data initiatives and projects. It is therefore important to gain a deeper understanding of the different approaches used. \u0000ApproachThis study explores PIE using ethnographically-informed qualitative case studies. The case studies include: three citizen juries, each one carried out over eight days and that asked jurors to consider different real-world health data initiatives; and a public panel set up by a regional databank that carries out data linking. Data collection is ongoing and I will be continuing to carry out close observations of activities, and conducting semi-structured 1:1 interviews with those that organise and have taken part in the activities. \u0000ResultsData collection so far comprises completed observations at the citizen juries (~96 hours), ongoing observations of the public panel meetings (~15 hours), and thirty semi-structured 1:1 interviews with public contributors and other stakeholders about their experiences of the activities they were involved in. Early data analysis indicates key themes of: jurors feeling heard, but unsure whether anybody was listening; stakeholders being impressed by informed jurors, but raising concerns over contributors becoming too ‘expert’; how who is at the table and what information is presented impacts what is discussed; differences between online and in-person participation; and public involvement not being a substitute for informing the public about how their data is used. \u0000Conclusion‘Who’ is involved, and ‘how’ PPIE activities are designed and run can facilitate or constrain discussion, enhancing or limiting public contributions. If public involvement is to achieve its aims, including increasing trustworthiness, deeper consideration of these factors by those who seek the public’s views in their data projects is recommended.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43560839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.1852
M. Chartier, W. Phillips-Beck, M. Brownell, L. Star, Nora Murdock, Wendy Au, J. Bowes, Brooke Cochrane, R. Campbell
ObjectivesGiven the impact of colonization and responding to Canada’s Truth and Reconciliation Commission, we aimed to provide baseline measures of First Nations children’s health and social outcomes in Manitoba, Canada. We also aimed to create a research process where Indigenous and non-Indigenous researchers work collaboratively and in culturally safe ways. ApproachWe formed a team consisting of members of First Nation organizations and academic researchers. Knowledge Keepers from Anishinaabe, Cree, Anishininew, Dakota and Dene Nations guided the study, interpreted results and ensured meaningful knowledge translation. This retrospective cohort study utilized population-based health, social services, education and justice administrative data that allowed de-identified individual-level linkages across all databases through a scrambled health number. Adjusted rates and rate ratios were calculated using a generalized liner modeling approach to compare First Nations children (n=61,726) and all other Manitoba children (n=279,087) and comparing First Nations children living on and off-reserve. ResultsLarge disparities between First Nations and other Manitoba children were found in birth outcomes, physical and mental health, health services, education, social services, justice system involvement and mortality. First Nations infants had higher rates of preterm births, large-for-gestational-age births, newborn readmissions to hospital and lower rates of breastfeeding initiation compared with other Manitoba infants. Suicide rates among First Nations adolescents were ten times higher than among other adolescents in Manitoba, yet we found few differences in diagnosis of mood and anxiety disorders between the groups. First Nations children were also seven times more likely to apprehended by child protection services and youth were ten times more likely to be criminally accused. Knowledge Keepers offered their perspectives on these findings. ConclusionThese findings demonstrate that an enormous amount of work is required in virtually every area – health, social, education and justice – to improve First Nations children’s lives. There is an urgent need for equitable access to services, and these services should be self-determined, planned and implemented by First Nations people.
{"title":"Our Children, Our Future: The Health and Well-being of First Nations Children in Manitoba, Canada.","authors":"M. Chartier, W. Phillips-Beck, M. Brownell, L. Star, Nora Murdock, Wendy Au, J. Bowes, Brooke Cochrane, R. Campbell","doi":"10.23889/ijpds.v7i3.1852","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1852","url":null,"abstract":"ObjectivesGiven the impact of colonization and responding to Canada’s Truth and Reconciliation Commission, we aimed to provide baseline measures of First Nations children’s health and social outcomes in Manitoba, Canada. We also aimed to create a research process where Indigenous and non-Indigenous researchers work collaboratively and in culturally safe ways. \u0000ApproachWe formed a team consisting of members of First Nation organizations and academic researchers. Knowledge Keepers from Anishinaabe, Cree, Anishininew, Dakota and Dene Nations guided the study, interpreted results and ensured meaningful knowledge translation. This retrospective cohort study utilized population-based health, social services, education and justice administrative data that allowed de-identified individual-level linkages across all databases through a scrambled health number. Adjusted rates and rate ratios were calculated using a generalized liner modeling approach to compare First Nations children (n=61,726) and all other Manitoba children (n=279,087) and comparing First Nations children living on and off-reserve. \u0000ResultsLarge disparities between First Nations and other Manitoba children were found in birth outcomes, physical and mental health, health services, education, social services, justice system involvement and mortality. First Nations infants had higher rates of preterm births, large-for-gestational-age births, newborn readmissions to hospital and lower rates of breastfeeding initiation compared with other Manitoba infants. Suicide rates among First Nations adolescents were ten times higher than among other adolescents in Manitoba, yet we found few differences in diagnosis of mood and anxiety disorders between the groups. First Nations children were also seven times more likely to apprehended by child protection services and youth were ten times more likely to be criminally accused. Knowledge Keepers offered their perspectives on these findings. \u0000ConclusionThese findings demonstrate that an enormous amount of work is required in virtually every area – health, social, education and justice – to improve First Nations children’s lives. There is an urgent need for equitable access to services, and these services should be self-determined, planned and implemented by First Nations people.","PeriodicalId":36483,"journal":{"name":"International Journal of Population Data Science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45279857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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