International Journal of Population Data Science最新文献

{"title":"Linking migration and hospital data in England: linkage process and evaluation of bias","authors":"Rachel Burns, Sacha Wyke, Y. Boukari, Sirinivasa Vittal Katikireddi, D. Zenner, I. Campos-Matos, Katie Harron, Robert Aldridge","doi":"10.23889/ijpds.v9i1.2181","DOIUrl":"https://doi.org/10.23889/ijpds.v9i1.2181","url":null,"abstract":"IntroductionDifficulties ascertaining migrant status in national data sources such as hospital records have limited large-scale evaluation of migrant healthcare needs in many countries, including England. Linkage of immigration data for migrants and refugees, with National Health Service (NHS) hospital care data enables research into the relationship between migration and health for a large cohort of international migrants.\u0000ObjectivesWe aimed to describe the linkage process and compare linkage rates between migrant sub-groups to evaluate for potential bias for data on non-EU migrants and resettled refugees linked to Hospital Episode Statistics (HES) in England.\u0000MethodsWe used stepwise deterministic linkage to match records from migrants and refugees to a unique healthcare identifier indicating interaction with the NHS (linkage stage 1 to NHS Personal Demographic Services, PDS), and then to hospital records (linkage stage 2 to HES). We calculated linkage rates and compared linked and unlinked migrant characteristics for each linkage stage.\u0000ResultsOf the 1,799,307 unique migrant records, 1,134,007 (63%) linked to PDS and 451,689 (25%) linked to at least one hospital record between 01/01/2005 and 23/03/2020. Individuals on work, student, or working holiday visas were less likely to link to a hospital record than those on settlement and dependent visas and refugees. Migrants from the Middle East and North Africa and South Asia were four times more likely to link to at least one hospital record, compared to those from East Asia and the Pacific. Differences in age, sex, visa type, and region of origin between linked and unlinked samples were small to moderate.\u0000ConclusionThis linked dataset represents a unique opportunity to explore healthcare use in migrants. However, lower linkage rates disproportionately affected individuals on shorter-term visas so future studies of these groups may be more biased as a result. Increasing the quality and completeness of identifiers recorded in administrative data could improve data linkage quality.","PeriodicalId":507952,"journal":{"name":"International Journal of Population Data Science","volume":"42 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139782437","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}

{"title":"Implementing the English health inequalities agenda: addressing challenges to person-level, cross-sectoral data linkage, access and routine use for local authority public health","authors":"Abraham George, Richard A. Powell, Mala Rao","doi":"10.23889/ijpds.v8i4.2166","DOIUrl":"https://doi.org/10.23889/ijpds.v8i4.2166","url":null,"abstract":"Local authorities are central to the implementation of English Integrated Care Systems' health inequalities agendas, embedding public health into population health management planning. They work with partners to deliver a range of 'health determinant' services and facilities for people in a defined geographic area. This work is substantially premised on the use of cross-sectoral data that is linked at the individual level, readily available, longitudinal and contemporaneous. However, multiple challenges exist to such data availability. This paper elaborates upon these challenges to local authority public health systems and their potential solutions.","PeriodicalId":507952,"journal":{"name":"International Journal of Population Data Science","volume":"3 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139855017","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}

{"title":"Implementing the English health inequalities agenda: addressing challenges to person-level, cross-sectoral data linkage, access and routine use for local authority public health","authors":"Abraham George, Richard A. Powell, Mala Rao","doi":"10.23889/ijpds.v8i4.2166","DOIUrl":"https://doi.org/10.23889/ijpds.v8i4.2166","url":null,"abstract":"Local authorities are central to the implementation of English Integrated Care Systems' health inequalities agendas, embedding public health into population health management planning. They work with partners to deliver a range of 'health determinant' services and facilities for people in a defined geographic area. This work is substantially premised on the use of cross-sectoral data that is linked at the individual level, readily available, longitudinal and contemporaneous. However, multiple challenges exist to such data availability. This paper elaborates upon these challenges to local authority public health systems and their potential solutions.","PeriodicalId":507952,"journal":{"name":"International Journal of Population Data Science","volume":"27 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139795163","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}

{"title":"Relative risks of childhood developmental vulnerabilities in three Australian communities with exposure to per- and polyfluoroalkyl substances: data linkage study","authors":"Hsei-Di Law, Bruce Armstrong, Catherine D'este, Rose Hosking, K. Smurthwaite, S. Trevenar, N. Lazarevic, Robyn M Lucas, Archie C. A. Clements, Martyn D Kirk, Rosemary J Korda","doi":"10.23889/ijpds.v9i1.2180","DOIUrl":"https://doi.org/10.23889/ijpds.v9i1.2180","url":null,"abstract":"BackgroundAqueous film forming foams (AFFF) containing per- and polyfluoroalkyl substances (PFAS) caused local environmental contamination in three Australian residential areas: Katherine in the Northern Territory (NT), Oakey in Queensland (Qld) and Williamtown in New South Wales (NSW). We examined whether children who lived in these areas had higher risks of developmental vulnerabilities than children who lived in comparison areas without known contamination.\u0000MethodsAll children identified in the Medicare Enrolment File-a consumer directory for Australia's universal healthcare insurance scheme-who ever lived in exposure areas, and a sample of children who ever lived in selected comparison areas, were linked to the Australian Early Development Census (AEDC). The AEDC data were available from four cycles: 2009, 2012, 2015 and 2018. For each exposure area, we estimated relative risks (RRs) of developmental vulnerability on each of five AEDC domains and a summary measure, adjusting for sociodemographic characteristics and other potential confounders.\u0000FindingsWe included 2,429 children from the NT, 2,592 from Qld and 510 from NSW. We observed lower risk of developmental vulnerability in the Communication skills and general knowledge domain in Katherine (RR = 0.74, 95% confidence interval (CI) 0.57 to 0.97), and higher risks of developmental vulnerability in the same domain (RR = 1.49, 95% CI 1.18 to 1.87) and in the Physical health and wellbeing domain in Oakey (RR = 1.31, 95% CI 1.06 to 1.61). Risks of developmental vulnerabilities on other domains were not different from those in the relevant comparison areas or were uncertain due to small numbers of events.\u0000ConclusionThere was inadequate evidence for increased risks of developmental vulnerabilities in children who ever lived in three PFAS-affected areas in Australia.","PeriodicalId":507952,"journal":{"name":"International Journal of Population Data Science","volume":"14 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139862574","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}

{"title":"Relative risks of childhood developmental vulnerabilities in three Australian communities with exposure to per- and polyfluoroalkyl substances: data linkage study","authors":"Hsei-Di Law, Bruce Armstrong, Catherine D'este, Rose Hosking, K. Smurthwaite, S. Trevenar, N. Lazarevic, Robyn M Lucas, Archie C. A. Clements, Martyn D Kirk, Rosemary J Korda","doi":"10.23889/ijpds.v9i1.2180","DOIUrl":"https://doi.org/10.23889/ijpds.v9i1.2180","url":null,"abstract":"BackgroundAqueous film forming foams (AFFF) containing per- and polyfluoroalkyl substances (PFAS) caused local environmental contamination in three Australian residential areas: Katherine in the Northern Territory (NT), Oakey in Queensland (Qld) and Williamtown in New South Wales (NSW). We examined whether children who lived in these areas had higher risks of developmental vulnerabilities than children who lived in comparison areas without known contamination.\u0000MethodsAll children identified in the Medicare Enrolment File-a consumer directory for Australia's universal healthcare insurance scheme-who ever lived in exposure areas, and a sample of children who ever lived in selected comparison areas, were linked to the Australian Early Development Census (AEDC). The AEDC data were available from four cycles: 2009, 2012, 2015 and 2018. For each exposure area, we estimated relative risks (RRs) of developmental vulnerability on each of five AEDC domains and a summary measure, adjusting for sociodemographic characteristics and other potential confounders.\u0000FindingsWe included 2,429 children from the NT, 2,592 from Qld and 510 from NSW. We observed lower risk of developmental vulnerability in the Communication skills and general knowledge domain in Katherine (RR = 0.74, 95% confidence interval (CI) 0.57 to 0.97), and higher risks of developmental vulnerability in the same domain (RR = 1.49, 95% CI 1.18 to 1.87) and in the Physical health and wellbeing domain in Oakey (RR = 1.31, 95% CI 1.06 to 1.61). Risks of developmental vulnerabilities on other domains were not different from those in the relevant comparison areas or were uncertain due to small numbers of events.\u0000ConclusionThere was inadequate evidence for increased risks of developmental vulnerabilities in children who ever lived in three PFAS-affected areas in Australia.","PeriodicalId":507952,"journal":{"name":"International Journal of Population Data Science","volume":"48 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139802342","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}

{"title":"Generating synthetic data from administrative health records for drug safety and effectiveness studies","authors":"O. Ayilara, Robert W. Platt, Matt Dahl, J. Coulombe, Pablo Gonzalez Ginestet, Dan Chateau, Lisa M. Lix","doi":"10.23889/ijpds.v8i1.2176","DOIUrl":"https://doi.org/10.23889/ijpds.v8i1.2176","url":null,"abstract":"IntroductionAdministrative health records (AHRs) are used to conduct population-based post-market drug safety and comparative effectiveness studies to inform healthcare decision making. However, the cost of data extraction, and the challenges associated with privacy and securing approvals can make it challenging for researchers to conduct methodological research in a timely manner using real data. Generating synthetic AHRs that reasonably represent the real-world data are beneficial for developing analytic methods and training analysts to rapidly implement study protocols. We generated synthetic AHRs using two methods and compared these synthetic AHRs to real-world AHRs. We described the challenges associated with using synthetic AHRs for real-world study. MethodsThe real-world AHRs comprised prescription drug records for individuals with healthcare insurance coverage in the Population Research Data Repository (PRDR) from Manitoba, Canada for the 10-year period from 2008 to 2017. Synthetic data were generated using the Observational Medical Dataset Simulator II (OSIM2) and a modification (ModOSIM). Synthetic and real-world data were described using frequencies and percentages. Agreement of prescription drug use measures in PRDR, OSIM2 and ModOSIM was estimated with the concordance coefficient. ResultsThe PRDR cohort included 169,586,633 drug records and 1,395 drug types for 1,604,734 individuals. Synthetic data for 1,000,000 individuals were generated using OSIM2 and ModOSIM. Sex and age group distributions were similar in the real-world and synthetic AHRs. However, there were significant differences in the number of drug records and number of unique drugs per person for OSIM2 and ModOSIM when compared with PRDR. For the average number of days of drug use, concordance with the PRDR was 16% (95% confidence interval [CI]: 12%-19%) for OSIM2 and 88% (95% CI: 87%-90%) for ModOSIM. ConclusionsModOSIM data were more similar to PRDR than OSIM2 data on many measures. Synthetic AHRs consistent with those found in real-world settings can be generated using ModOSIM. Synthetic data will benefit rapid implementation of methodological studies and data analyst training.","PeriodicalId":507952,"journal":{"name":"International Journal of Population Data Science","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139232690","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}