Pub Date : 2022-08-25DOI: 10.23889/ijpds.v7i3.2051
E. Frymire, M. Green, R. Glazier, Shahriar Khan, Kamila Premji, I. Bayoumi, L. Jaakkimainen, T. Kiran, P. Gozdyra
ObjectivesTo produce open access Primary Care Data Reports using standard health administrative measures in primary care in conjunction with measures for attachment to a primary care provider. Illustrate the importance of incorporating patient attachment data as an essential component in Human Health Resource (HHR) planning. ApproachThis cohort study uses standard health administrative linked data in primary care in conjunction with measures of attachment to a primary care provider for the population of Ontario, Canada (14,632,575). Data includes attached and uncertainly attached patients stratified according to key demographics, patient characteristics, health care utilization and primary care indicators. We stratified based on health utilization characteristics and produced 6 priority populations of interest by region. ResultsThe factors most often utilized in informing human health resource planning were based on policy and practice users input and included:1.Patient enrolment model, 2.Attachment to a primary care provider, 3.Who does and does not receive care, 4.Continuity with regular source of care. Policy planners use the reports for improved understanding of the scope of issues in regions and improved understanding of primary care involvement with priority populations. Policy planners have used this report as a data support and measurement tool to identify supply (physician) and demand (patient) data essential in HHR planning. Health system reform initiatives can use this data to inform improvements in the quality of, and equitable access to, primary care services in specific jurisdictions. ConclusionsThese reports contain key physician and patient data characteristics that correspond to primary care attachment rates. This data is essential to HHR planning when the goal is improving access to primary care for both attached and uncertainly attached patients. Data visualization in the form of mapping is especially impactful for policy and practice stakeholders.
{"title":"Using Primary care data metrics to inform policy and practice: Human Health Resource implications.","authors":"E. Frymire, M. Green, R. Glazier, Shahriar Khan, Kamila Premji, I. Bayoumi, L. Jaakkimainen, T. Kiran, P. Gozdyra","doi":"10.23889/ijpds.v7i3.2051","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.2051","url":null,"abstract":"ObjectivesTo produce open access Primary Care Data Reports using standard health administrative measures in primary care in conjunction with measures for attachment to a primary care provider. Illustrate the importance of incorporating patient attachment data as an essential component in Human Health Resource (HHR) planning. \u0000ApproachThis cohort study uses standard health administrative linked data in primary care in conjunction with measures of attachment to a primary care provider for the population of Ontario, Canada (14,632,575). Data includes attached and uncertainly attached patients stratified according to key demographics, patient characteristics, health care utilization and primary care indicators. We stratified based on health utilization characteristics and produced 6 priority populations of interest by region. \u0000ResultsThe factors most often utilized in informing human health resource planning were based on policy and practice users input and included:1.Patient enrolment model, 2.Attachment to a primary care provider, 3.Who does and does not receive care, 4.Continuity with regular source of care. Policy planners use the reports for improved understanding of the scope of issues in regions and improved understanding of primary care involvement with priority populations. Policy planners have used this report as a data support and measurement tool to identify supply (physician) and demand (patient) data essential in HHR planning. Health system reform initiatives can use this data to inform improvements in the quality of, and equitable access to, primary care services in specific jurisdictions. \u0000ConclusionsThese reports contain key physician and patient data characteristics that correspond to primary care attachment rates. This data is essential to HHR planning when the goal is improving access to primary care for both attached and uncertainly attached patients. Data visualization in the form of mapping is especially impactful for policy and practice stakeholders.","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":"46153634","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.v7i3.1869
Jacqueline Caldwell, Robert Wallace, Carole Morris, Simon Fleming, Rob Baxter, Ruairidh Macleod, W. Kerr, Donald Scobbie, Simon Rogers, F. Ritchie, Esma Mansouri-Benssassi, Susan Krueger, E. Jefferson
ObjectivesThe Scottish Medical Imaging (SMI) service provides linkable, population based, “research-ready” real-world medical images for researchers to develop or validate AI algorithms within the Scottish National Safe Haven. The PICTURES research programme is developing novel methods to enhance the SMI service offering through research in cybersecurity and software/data/infrastructure engineering. ApproachAdditional technical and governance controls were required to enable safe access to medical images. The researcher is isolated from the rest of the trusted research environment (TRE) using a Project Private Zone (PPZ). This enables researchers to build and install their own software stack, and protects the TRE from malicious code. Guidelines are under development for researchers on the safe development of algorithms and the expected relationship between the size of the model and the training dataset. There is associated work on the statistical disclosure control of models to enable safe release of trained models from the TRE. ResultsA policy enabling the use of “Non-standard software” based on prior research, domain knowledge and experience gained from two contrasting research studies was developed. Additional clauses have been added to the legal control – the eDRIS User Agreement – signed by each researcher and their Head of Department. Penalties for attempting to import or use malware, remove data within models or any attempt to deceive or circumvent such controls are severe, and apply to both the individual and their institution. The process of building and deploying a PPZ has been developed allowing researchers to install their own software. No attempt has yet been made to add additional ethical controls; however, a future service development could be validating the performance of researchers’ algorithms on our training dataset. ConclusionThe availability to conduct research using images poses new challenges and risks for those commissioning and operating TREs. The Private Project Zone and our associated governance controls are a huge step towards supporting the needs of researchers in the 21st century.
{"title":"Scottish Medical Imaging Service - Technical and Governance controls.","authors":"Jacqueline Caldwell, Robert Wallace, Carole Morris, Simon Fleming, Rob Baxter, Ruairidh Macleod, W. Kerr, Donald Scobbie, Simon Rogers, F. Ritchie, Esma Mansouri-Benssassi, Susan Krueger, E. Jefferson","doi":"10.23889/ijpds.v7i3.1869","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1869","url":null,"abstract":"ObjectivesThe Scottish Medical Imaging (SMI) service provides linkable, population based, “research-ready” real-world medical images for researchers to develop or validate AI algorithms within the Scottish National Safe Haven. The PICTURES research programme is developing novel methods to enhance the SMI service offering through research in cybersecurity and software/data/infrastructure engineering. \u0000ApproachAdditional technical and governance controls were required to enable safe access to medical images. \u0000The researcher is isolated from the rest of the trusted research environment (TRE) using a Project Private Zone (PPZ). This enables researchers to build and install their own software stack, and protects the TRE from malicious code. \u0000Guidelines are under development for researchers on the safe development of algorithms and the expected relationship between the size of the model and the training dataset. There is associated work on the statistical disclosure control of models to enable safe release of trained models from the TRE. \u0000ResultsA policy enabling the use of “Non-standard software” based on prior research, domain knowledge and experience gained from two contrasting research studies was developed. Additional clauses have been added to the legal control – the eDRIS User Agreement – signed by each researcher and their Head of Department. Penalties for attempting to import or use malware, remove data within models or any attempt to deceive or circumvent such controls are severe, and apply to both the individual and their institution. The process of building and deploying a PPZ has been developed allowing researchers to install their own software. \u0000No attempt has yet been made to add additional ethical controls; however, a future service development could be validating the performance of researchers’ algorithms on our training dataset. \u0000ConclusionThe availability to conduct research using images poses new challenges and risks for those commissioning and operating TREs. The Private Project Zone and our associated governance controls are a huge step towards supporting the needs of researchers in the 21st century.","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":"46605876","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.v7i3.2020
M. Fleming
ObjectivesLooked-after-children are defined as children who are in the care of their local authority. Previous studies have reported that looked-after-children have poorer mental and physical health, increased behavioural problems, and increased self-harm and mortality compared to peers. They also experience poorer educational outcomes yet population wide research into the latter is lacking, particularly in the UK. Education and health share a bidirectional relationship therefore it is important to dually investigate both outcomes. Our study aimed to compare educational and health outcomes for looked-after-children with peers, adjusting for sociodemographic, maternity and comorbidity confounders. ApproachLinkage of nine Scotland-wide databases, covering dispensed prescriptions, hospital admissions, maternity records, death certificates, annual pupil census, examinations, school absences/exclusions, unemployment, and looked-after-children provided retrospective data on 715,111 children attending Scottish schools between 2009 and 2012. ResultsCompared to peers, 13,898 (1.9%) looked-after-children were more likely to be absent and excluded from school, have special educational need and neurodevelopmental multimorbidity, achieve the lowest level of academic attainment, and be unemployed after leaving school. They were more likely to require treatment for epilepsy, attention deficit hyperactivity disorder and depression, be hospitalised overall, for injury and self-harm, and die prematurely. Compared to children looked after at home, children looked after away from home had less absenteeism, less exclusion, less unemployment, and better attainment. Therefore, amongst those in care, being cared for away from home appeared to be a protective factor resulting in better educational outcomes. ConclusionsLooked-after-children had poorer health and educational outcomes than peers independent of increased neurodevelopmental conditions and special educational need. Further work is required to understand whether poorer outcomes relate to reasons for entering care, including maltreatment and adverse childhood events, neurodevelopmental vulnerabilities, or characteristics of the care system.
{"title":"Educational and health outcomes of schoolchildren in local authority care in Scotland: a retrospective record linkage study.","authors":"M. Fleming","doi":"10.23889/ijpds.v7i3.2020","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.2020","url":null,"abstract":"ObjectivesLooked-after-children are defined as children who are in the care of their local authority. Previous studies have reported that looked-after-children have poorer mental and physical health, increased behavioural problems, and increased self-harm and mortality compared to peers. They also experience poorer educational outcomes yet population wide research into the latter is lacking, particularly in the UK. Education and health share a bidirectional relationship therefore it is important to dually investigate both outcomes. Our study aimed to compare educational and health outcomes for looked-after-children with peers, adjusting for sociodemographic, maternity and comorbidity confounders. \u0000ApproachLinkage of nine Scotland-wide databases, covering dispensed prescriptions, hospital admissions, maternity records, death certificates, annual pupil census, examinations, school absences/exclusions, unemployment, and looked-after-children provided retrospective data on 715,111 children attending Scottish schools between 2009 and 2012. \u0000ResultsCompared to peers, 13,898 (1.9%) looked-after-children were more likely to be absent and excluded from school, have special educational need and neurodevelopmental multimorbidity, achieve the lowest level of academic attainment, and be unemployed after leaving school. They were more likely to require treatment for epilepsy, attention deficit hyperactivity disorder and depression, be hospitalised overall, for injury and self-harm, and die prematurely. Compared to children looked after at home, children looked after away from home had less absenteeism, less exclusion, less unemployment, and better attainment. Therefore, amongst those in care, being cared for away from home appeared to be a protective factor resulting in better educational outcomes. \u0000ConclusionsLooked-after-children had poorer health and educational outcomes than peers independent of increased neurodevelopmental conditions and special educational need. Further work is required to understand whether poorer outcomes relate to reasons for entering care, including maltreatment and adverse childhood events, neurodevelopmental vulnerabilities, or characteristics of the care system.","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":"44607312","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.v7i3.1962
Yinshan Zhao, Mike Jarrett, Kimberlyn McGail, Brent Hills
ObjectivesPopulation Data BC (PopData) is an agency in British Columbia, Canada, that routinely performs linkages of various administrative and researcher-collected data to a population spine. We developed a linkage report template in order to increase transparency of linkage process and outcome for end users and data providers. ApproachPopData performs probabilistic and deterministic data linkage using an in-house software. A literature review identified existing guidelines and examples of linkage reporting. A survey collected input from a wide range of end users about their interest in receiving linkage reports and specific information that is important to their work. A draft template was developed by PopData’s linkage experts and data scientists which then was reviewed by PopData staff and external partners. Privacy requirements, mode of delivery, readability to the intended audience and operational feasibility were carefully considered. ResultsThe resulting template built on our existing internal linkage summaries. The report follows a framework suggested in the literature with three key components: 1) information on the data source and linkage fields, 2) data pre-processing and linkage methodology, and 3) linkage results, presented in tables and figures, including overall linkage rates, detail on matched fields, and the distribution of linkage weights of linked and unliked pairs. In addition, an appendix describes the linkage methods and population spine in detail, and supplementary notes will comment on unique issues related to the data, when those are applicable. Educational materials to aid understanding of linkage methodologies and reporting are also under development. ConclusionLinked data are increasingly used in research, making it important to provide information on linkage process and performance to the research community. Rigorous and standardized linkage reports produced by data centres can facilitate evaluation of the impact of linkage performance on research findings and enable transparent reporting in peer-reviewed research.
{"title":"A proposed approach for standardized reporting of data linkage processes and results.","authors":"Yinshan Zhao, Mike Jarrett, Kimberlyn McGail, Brent Hills","doi":"10.23889/ijpds.v7i3.1962","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1962","url":null,"abstract":"ObjectivesPopulation Data BC (PopData) is an agency in British Columbia, Canada, that routinely performs linkages of various administrative and researcher-collected data to a population spine. We developed a linkage report template in order to increase transparency of linkage process and outcome for end users and data providers. \u0000ApproachPopData performs probabilistic and deterministic data linkage using an in-house software. A literature review identified existing guidelines and examples of linkage reporting. A survey collected input from a wide range of end users about their interest in receiving linkage reports and specific information that is important to their work. A draft template was developed by PopData’s linkage experts and data scientists which then was reviewed by PopData staff and external partners. Privacy requirements, mode of delivery, readability to the intended audience and operational feasibility were carefully considered. \u0000ResultsThe resulting template built on our existing internal linkage summaries. The report follows a framework suggested in the literature with three key components: 1) information on the data source and linkage fields, 2) data pre-processing and linkage methodology, and 3) linkage results, presented in tables and figures, including overall linkage rates, detail on matched fields, and the distribution of linkage weights of linked and unliked pairs. In addition, an appendix describes the linkage methods and population spine in detail, and supplementary notes will comment on unique issues related to the data, when those are applicable. Educational materials to aid understanding of linkage methodologies and reporting are also under development. \u0000ConclusionLinked data are increasingly used in research, making it important to provide information on linkage process and performance to the research community. Rigorous and standardized linkage reports produced by data centres can facilitate evaluation of the impact of linkage performance on research findings and enable transparent reporting in peer-reviewed research.","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":"43188260","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.v7i3.2061
L. Williamson, C. Dibben
ObjectivesAims of this research, involving data linkage and health outcomes, is to gain a full understanding of the impact of both fertility histories and childlessness on health outcomes mid-life accounting for socio-economic background and area of residence. The research draws on and extends work on reproductive histories and life-course outcomes. ApproachWe aim to extend this area of research, specifically for Scotland, using Census data (1991-2011) from the Scottish Longitudinal Study (SLS) linked to health data. The Census health measures – including the 2011 Census health condition question on mental health - are the research outcomes and the explanatory information is from Census socio-economic data (captured around peak fertility for the research cohort in 1991), along with the SMR02 Maternity and SMR04 Mental Health datasets. The time-frame for available data allows 20 year follow-up from the 1991 Census to mid-life for specific female SLS birth cohorts (born 1959-1966, aged ~45-52 in 2011). ResultsFrom preliminary modelling we initially find, for this specific female research cohort, high birth parity to be an important factor in relation to self-reported mental health conditions at follow-up in 2011, but not once socio-economic and area-level variables are controlled for. ConclusionPreliminary modelling also highlights that relationship status – single, married or cohabiting – to be important over that of legal marital status as recorded at Census. For limiting long-term illness as a health outcome the findings are similar.
{"title":"Understanding the impact of fertility history on health outcomes in later life.","authors":"L. Williamson, C. Dibben","doi":"10.23889/ijpds.v7i3.2061","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.2061","url":null,"abstract":"ObjectivesAims of this research, involving data linkage and health outcomes, is to gain a full understanding of the impact of both fertility histories and childlessness on health outcomes mid-life accounting for socio-economic background and area of residence. The research draws on and extends work on reproductive histories and life-course outcomes. \u0000ApproachWe aim to extend this area of research, specifically for Scotland, using Census data (1991-2011) from the Scottish Longitudinal Study (SLS) linked to health data. The Census health measures – including the 2011 Census health condition question on mental health - are the research outcomes and the explanatory information is from Census socio-economic data (captured around peak fertility for the research cohort in 1991), along with the SMR02 Maternity and SMR04 Mental Health datasets. The time-frame for available data allows 20 year follow-up from the 1991 Census to mid-life for specific female SLS birth cohorts (born 1959-1966, aged ~45-52 in 2011). \u0000ResultsFrom preliminary modelling we initially find, for this specific female research cohort, high birth parity to be an important factor in relation to self-reported mental health conditions at follow-up in 2011, but not once socio-economic and area-level variables are controlled for. \u0000ConclusionPreliminary modelling also highlights that relationship status – single, married or cohabiting – to be important over that of legal marital status as recorded at Census. For limiting long-term illness as a health outcome the findings are similar.","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":"46647192","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.v7i3.1785
F. Grimm, D. Lewer, J. Craig, R. Rogans-Watson, J. Shand
ObjectivesOlder people and people with complex needs often require both health and social care services, but there is limited insight into individual journeys across these services. To help inform joint health and social care planning, we aimed to assess the relationship between hospital admissions and domiciliary care receipt. ApproachWe used an individually linked dataset of primary care activity, hospital admissions and local authority-held social care records for adults living in Barking and Dagenham, a borough in London, England, on 1 April 2018, and followed them up until 31 March 2020. The outcome was initiation of a new domiciliary care package. We estimated the rate of hospital-associated care package initiation, and of care packages unrelated to hospital admissions. We also described the characteristics of hospital admissions that preceded domiciliary care and examined which primary diagnoses codes were associated with receiving domiciliary care after discharge. ResultsIn our cohort, 1.4 of participants had a domiciliary care package during a median follow-up of 1.87 years. One in three domiciliary care packages were initiated during a hospital stay or within 7 days of discharge. The rate of new domiciliary care packages was 120 times greater (95% CI 110-130) during or after a hospital stay than at other times, and this association was present for all age groups. Primary admission reasons accounting for the largest number of domiciliary care packages were hip fracture, pneumonia, urinary tract infection, septicaemia, and exacerbations of long-term conditions (COPD and heart failure). Admission reasons with the greatest likelihood of a subsequent domiciliary care package were fractures and strokes. ConclusionHospitals are a major referral route into domiciliary care. While new and acute illnesses account for many domiciliary care packages, exacerbations of long-term conditions and age- and frailty-related conditions are also an important driver. National-level linked datasets are needed for a better understanding of the relationship between health and social care receipt.
{"title":"Using cross-sector data linkage to track patient journeys across health and social care.","authors":"F. Grimm, D. Lewer, J. Craig, R. Rogans-Watson, J. Shand","doi":"10.23889/ijpds.v7i3.1785","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1785","url":null,"abstract":"ObjectivesOlder people and people with complex needs often require both health and social care services, but there is limited insight into individual journeys across these services. To help inform joint health and social care planning, we aimed to assess the relationship between hospital admissions and domiciliary care receipt. \u0000ApproachWe used an individually linked dataset of primary care activity, hospital admissions and local authority-held social care records for adults living in Barking and Dagenham, a borough in London, England, on 1 April 2018, and followed them up until 31 March 2020. The outcome was initiation of a new domiciliary care package. We estimated the rate of hospital-associated care package initiation, and of care packages unrelated to hospital admissions. We also described the characteristics of hospital admissions that preceded domiciliary care and examined which primary diagnoses codes were associated with receiving domiciliary care after discharge. \u0000ResultsIn our cohort, 1.4 of participants had a domiciliary care package during a median follow-up of 1.87 years. One in three domiciliary care packages were initiated during a hospital stay or within 7 days of discharge. The rate of new domiciliary care packages was 120 times greater (95% CI 110-130) during or after a hospital stay than at other times, and this association was present for all age groups. Primary admission reasons accounting for the largest number of domiciliary care packages were hip fracture, pneumonia, urinary tract infection, septicaemia, and exacerbations of long-term conditions (COPD and heart failure). Admission reasons with the greatest likelihood of a subsequent domiciliary care package were fractures and strokes. \u0000ConclusionHospitals are a major referral route into domiciliary care. While new and acute illnesses account for many domiciliary care packages, exacerbations of long-term conditions and age- and frailty-related conditions are also an important driver. National-level linked datasets are needed for a better understanding of the relationship between health and social care receipt.","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":"43684699","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.v7i3.1853
R. Ewesesan, M. Chartier, Nathan C. Nickel, E. Wall-Wieler, Marcelo L. Urquia
ObjectivesPerinatal risk factors can vary by immigration status. To advance knowledge on sociobehavioral health risks among pregnant and childbearing immigrant women, we compared perinatal health indicators between immigrant and non-immigrants, overall, and according to key immigrant characteristics (refugee status, secondary migration, birth region, and duration of residence). ApproachWe conducted a population-based cross-sectional study of 33,754 immigrant and 172,342 non-immigrant childbearing women in Manitoba, Canada, aged 15-55 years, who had newborn screening data completed by public health nurses within two weeks postpartum from 2000 to 2017. The screening data was linked to a Canadian national immigration database. Additional databases were linked to collect demographic and perinatal clinical information. Logistic regression models were used to examine the associations between immigration characteristics and perinatal health indicators, such as social isolation, relationship distress, partner violence, depression, alcohol, smoking, substance use and late prenatal care initiation. ResultsMore immigrant women reported being socially isolated (12.3%) than non-immigrants (3.0%) (Adjusted Odds Ratio (aOR): 6.90, 95% Confidence Interval (CI): 6.53, 7.28) but exhibited lower odds of other outcomes. In the analysis restricted to immigrants, recent immigrants (< 5 years of stay) had higher odds of being socially isolated (aOR: 9.29, 95% CI: 7.80, 11.06) and late prenatal care (aOR: 1.73, 95% CI: 1.23, 2.42) compared to long-term immigrants, but lower odds relationship distress, depression, alcohol, smoking and substance use. Refugee status was positively associated with social isolation, relationship distress, depression, and late prenatal care whereas secondary migration was protective for social isolation, relationship distress, and smoking. Relationship distress and behavioral health indicators varied by maternal birth region. ConclusionThe novel linkage of birth screening data with the immigration data advances knowledge on immigrant perinatal health by identifying risk patterns for multiple psychosocial and behavioral health indicators, highlighting subgroups at higher and lower risk of exposures that may contribute to adverse perinatal health outcomes.
{"title":"Combining immigration records with a postpartum population-based survey to assess prevalence of perinatal psychosocial and behavioral risk factors among immigrant subgroups.","authors":"R. Ewesesan, M. Chartier, Nathan C. Nickel, E. Wall-Wieler, Marcelo L. Urquia","doi":"10.23889/ijpds.v7i3.1853","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1853","url":null,"abstract":"ObjectivesPerinatal risk factors can vary by immigration status. To advance knowledge on sociobehavioral health risks among pregnant and childbearing immigrant women, we compared perinatal health indicators between immigrant and non-immigrants, overall, and according to key immigrant characteristics (refugee status, secondary migration, birth region, and duration of residence). \u0000ApproachWe conducted a population-based cross-sectional study of 33,754 immigrant and 172,342 non-immigrant childbearing women in Manitoba, Canada, aged 15-55 years, who had newborn screening data completed by public health nurses within two weeks postpartum from 2000 to 2017. The screening data was linked to a Canadian national immigration database. Additional databases were linked to collect demographic and perinatal clinical information. Logistic regression models were used to examine the associations between immigration characteristics and perinatal health indicators, such as social isolation, relationship distress, partner violence, depression, alcohol, smoking, substance use and late prenatal care initiation. \u0000ResultsMore immigrant women reported being socially isolated (12.3%) than non-immigrants (3.0%) (Adjusted Odds Ratio (aOR): 6.90, 95% Confidence Interval (CI): 6.53, 7.28) but exhibited lower odds of other outcomes. In the analysis restricted to immigrants, recent immigrants (< 5 years of stay) had higher odds of being socially isolated (aOR: 9.29, 95% CI: 7.80, 11.06) and late prenatal care (aOR: 1.73, 95% CI: 1.23, 2.42) compared to long-term immigrants, but lower odds relationship distress, depression, alcohol, smoking and substance use. Refugee status was positively associated with social isolation, relationship distress, depression, and late prenatal care whereas secondary migration was protective for social isolation, relationship distress, and smoking. Relationship distress and behavioral health indicators varied by maternal birth region. \u0000ConclusionThe novel linkage of birth screening data with the immigration data advances knowledge on immigrant perinatal health by identifying risk patterns for multiple psychosocial and behavioral health indicators, highlighting subgroups at higher and lower risk of exposures that may contribute to adverse perinatal health outcomes.","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":"42017766","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.v7i3.1833
F. Cavallaro, R. Cannings‐John, F. Lugg-Widger, J. H. van der Meulen, R. Gilbert, E. Kennedy, M. Robling, Hywel Jones
ObjectivesWe describe the challenges and lessons learned from two studies using linked administrative data from health, education and social care sectors to evaluate the Family Nurse Partnership (FNP), an intervention supporting adolescent mothers in England(E) and Scotland(S). We present recommendations for studies using linked administrative data to evaluate complex interventions. ApproachWe constructed two cohorts of all mothers aged 13-19 giving birth in NHS hospitals in England and Scotland between 2010-2016/17 using linkage of mothers and babies in hospital admissions data (E:Hospital Episode Statistics/S:Maternity Inpatient and Day Case), and identified FNP participation through linkage to FNP programme data. We additionally linked to health, educational and social care data for mothers and their babies (E:National Pupil Database/S:eDRIS). We used these data to identify key risk factors for enrolment in the FNP, assess the effect of the FNP on maternal and child outcomes, and determine programme characteristics modifying the effect of the FNP. ResultsKey challenges: characterising the intervention and usual care, understanding quality of multi-sector data linkage, data access delays, constructing appropriate comparator groups and interpreting outcomes captured in administrative data. Lessons learned: evaluations require detailed data on intervention activity (dates/geography), and assessment of usual care, which are rarely readily available and are time-consuming to gather; data linkage quality is variable/not available, making defining denominators challenging; data access delays impeded on data analysis time; unmeasured confounders not captured in administrative data may prevent generation of an appropriate comparator group. Recommendations: Characteristics informing targeting should be explicitly documented, and could be enhanced using linked primary care data and information on household members (e.g. fathers). Process evaluation and qualitative research could help to provide better understanding of mechanisms of effect. ConclusionLinkage of administrative data presents exciting opportunities for efficient evaluation of large-scale, complex public health interventions. However, sufficient information is needed on programme meta-data, targeting and important confounders in order to generate meaningful results. Study findings should help stimulate exploration with practitioners about how programmes can be improved.
{"title":"Challenges and lessons learned from two countries using linked administrative data to evaluate the Family Nurse Partnership.","authors":"F. Cavallaro, R. Cannings‐John, F. Lugg-Widger, J. H. van der Meulen, R. Gilbert, E. Kennedy, M. Robling, Hywel Jones","doi":"10.23889/ijpds.v7i3.1833","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1833","url":null,"abstract":"ObjectivesWe describe the challenges and lessons learned from two studies using linked administrative data from health, education and social care sectors to evaluate the Family Nurse Partnership (FNP), an intervention supporting adolescent mothers in England(E) and Scotland(S). We present recommendations for studies using linked administrative data to evaluate complex interventions. \u0000ApproachWe constructed two cohorts of all mothers aged 13-19 giving birth in NHS hospitals in England and Scotland between 2010-2016/17 using linkage of mothers and babies in hospital admissions data (E:Hospital Episode Statistics/S:Maternity Inpatient and Day Case), and identified FNP participation through linkage to FNP programme data. We additionally linked to health, educational and social care data for mothers and their babies (E:National Pupil Database/S:eDRIS). We used these data to identify key risk factors for enrolment in the FNP, assess the effect of the FNP on maternal and child outcomes, and determine programme characteristics modifying the effect of the FNP. \u0000ResultsKey challenges: characterising the intervention and usual care, understanding quality of multi-sector data linkage, data access delays, constructing appropriate comparator groups and interpreting outcomes captured in administrative data. Lessons learned: evaluations require detailed data on intervention activity (dates/geography), and assessment of usual care, which are rarely readily available and are time-consuming to gather; data linkage quality is variable/not available, making defining denominators challenging; data access delays impeded on data analysis time; unmeasured confounders not captured in administrative data may prevent generation of an appropriate comparator group. Recommendations: Characteristics informing targeting should be explicitly documented, and could be enhanced using linked primary care data and information on household members (e.g. fathers). Process evaluation and qualitative research could help to provide better understanding of mechanisms of effect. \u0000ConclusionLinkage of administrative data presents exciting opportunities for efficient evaluation of large-scale, complex public health interventions. However, sufficient information is needed on programme meta-data, targeting and important confounders in order to generate meaningful results. Study findings should help stimulate exploration with practitioners about how programmes can be improved.","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":"42119569","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.v7i3.2079
Yu Deng, Lacey P. Gleason, Adam Culbertson, Don Asmonga, S. Grannis, A. Kho
ObjectivesPatient matching rates between organizations can be as low as fifty percent. Challenges to matching include the variation in quality and availability of patient attributes. Here we describe the changing nature of patient attributes available over the past 11-years across a diversity of care settings in the United States. ApproachOur expert panel identified 64 patient attributes that are currently used or could potentially be candidates for patient matching. We identified a national sample of 14 health care sites who sent us aggregated information on the 64 patient attributes from 2010 to 2020 (inclusive). The information included overall counts and percent availability, overall counts and percent availability by race, and counts and availability by year. Only patients having at least one visit to the site since 2010 and who were between 18 and 89 years of age at time of extraction were included. ResultsThe aggregated results revealed that first name, last name, gender, postal codes, and date of birth are highly available (>90%) across healthcare organizations and time. Patient reported social security number, work phone number, and emergency contact declined markedly, potentially reflecting privacy concerns. Email addresses (from 18.0% to 63.7%) and phone numbers (from 14.7% to 69.4%) increased greatly over the past 11 years. Novel patient matching attributes such as blood type, facial image, thumb print, or eye color are rarely collected across sites for all years. We observed emerging attributes including sexuality, occupation, and nickname with a small number of sites collecting these over 70%, reflecting the feasibility of wider adoption in the future. ConclusionIn this study, we examined the availability of 64 patient attributes across 14 sites from 2010 and 2020. Our findings could inform policy makers and readers about patient attributes that are used for current patient matching and emerging data attributes that could be considered for incorporation into future matching algorithms.
{"title":"The changing nature of patient attributes available for matching.","authors":"Yu Deng, Lacey P. Gleason, Adam Culbertson, Don Asmonga, S. Grannis, A. Kho","doi":"10.23889/ijpds.v7i3.2079","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.2079","url":null,"abstract":"ObjectivesPatient matching rates between organizations can be as low as fifty percent. Challenges to matching include the variation in quality and availability of patient attributes. Here we describe the changing nature of patient attributes available over the past 11-years across a diversity of care settings in the United States. \u0000ApproachOur expert panel identified 64 patient attributes that are currently used or could potentially be candidates for patient matching. We identified a national sample of 14 health care sites who sent us aggregated information on the 64 patient attributes from 2010 to 2020 (inclusive). The information included overall counts and percent availability, overall counts and percent availability by race, and counts and availability by year. Only patients having at least one visit to the site since 2010 and who were between 18 and 89 years of age at time of extraction were included. \u0000ResultsThe aggregated results revealed that first name, last name, gender, postal codes, and date of birth are highly available (>90%) across healthcare organizations and time. Patient reported social security number, work phone number, and emergency contact declined markedly, potentially reflecting privacy concerns. Email addresses (from 18.0% to 63.7%) and phone numbers (from 14.7% to 69.4%) increased greatly over the past 11 years. Novel patient matching attributes such as blood type, facial image, thumb print, or eye color are rarely collected across sites for all years. We observed emerging attributes including sexuality, occupation, and nickname with a small number of sites collecting these over 70%, reflecting the feasibility of wider adoption in the future. \u0000ConclusionIn this study, we examined the availability of 64 patient attributes across 14 sites from 2010 and 2020. Our findings could inform policy makers and readers about patient attributes that are used for current patient matching and emerging data attributes that could be considered for incorporation into future matching algorithms.","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":"48932868","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.v7i3.1920
Georgina Eaton, Kylie Hill, A. Summerfield
ObjectivesThe Ministry of Justice’s pioneering data linking programme Data First, funded by Administrative Data Research UK, links administrative datasets across the justice system and with other government departments to enable research providing critical new insights on justice system users, their pathways, and outcomes across a range of public services. ApproachThe first two datasets shared under the Data First project are magistrates’ courts and Crown Court data which have been deidentified, deduplicated and linked to provide a joined-up picture of criminal court defendant and case journeys. Accredited researchers can access this data using the ONS Secure Research Service to conduct research. Administrative Data Research UK has funded four Research Fellows to conduct analysis using this linked data. Additionally, analysts within the Ministry of Justice Data First team have published a research report showcasing the potential of the linked criminal courts data. The presentation will primarily focus on this work. ResultsThe Data First criminal courts datasets have enabled, for the first time, the extent and nature of repeat users to be explored at scale for research. In March 2022, the Ministry of Justice published exploratory analysis of returning defendants and the potential of linked criminal courts data. The key findings of this report will be covered in the presentation. The research demonstrates more than half of defendants returned to the courts within the data period, but this was highest for specific offence groups, including theft, robbery and drug offences. Locality-based analysis on Crown Court defendants highlights important insights on the backgrounds of justice system users, showing an over-representation of defendants residing in the most deprived areas in England and Wales compared to the general population. ConclusionThe presentation will demonstrate how linked administrative data available through the ground-breaking Data First programme can be effectively used for research. This insight improves our understanding of individuals in the justice system as well as providing a rich resource to develop the evidence base for government policy and practice.
{"title":"Data First: Criminal Courts Linked Data research report.","authors":"Georgina Eaton, Kylie Hill, A. Summerfield","doi":"10.23889/ijpds.v7i3.1920","DOIUrl":"https://doi.org/10.23889/ijpds.v7i3.1920","url":null,"abstract":"ObjectivesThe Ministry of Justice’s pioneering data linking programme Data First, funded by Administrative Data Research UK, links administrative datasets across the justice system and with other government departments to enable research providing critical new insights on justice system users, their pathways, and outcomes across a range of public services. \u0000ApproachThe first two datasets shared under the Data First project are magistrates’ courts and Crown Court data which have been deidentified, deduplicated and linked to provide a joined-up picture of criminal court defendant and case journeys. Accredited researchers can access this data using the ONS Secure Research Service to conduct research. Administrative Data Research UK has funded four Research Fellows to conduct analysis using this linked data. Additionally, analysts within the Ministry of Justice Data First team have published a research report showcasing the potential of the linked criminal courts data. The presentation will primarily focus on this work. \u0000ResultsThe Data First criminal courts datasets have enabled, for the first time, the extent and nature of repeat users to be explored at scale for research. In March 2022, the Ministry of Justice published exploratory analysis of returning defendants and the potential of linked criminal courts data. The key findings of this report will be covered in the presentation. The research demonstrates more than half of defendants returned to the courts within the data period, but this was highest for specific offence groups, including theft, robbery and drug offences. Locality-based analysis on Crown Court defendants highlights important insights on the backgrounds of justice system users, showing an over-representation of defendants residing in the most deprived areas in England and Wales compared to the general population. \u0000ConclusionThe presentation will demonstrate how linked administrative data available through the ground-breaking Data First programme can be effectively used for research. This insight improves our understanding of individuals in the justice system as well as providing a rich resource to develop the evidence base for government policy and practice.","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":"47540311","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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