Immunization information and population data sources

Author(s):  
Rebecca A. Hills ◽  
Blaine Reeder ◽  
Debra Revere ◽  
William B. Lober ◽  
Neil F. Abernethy
Keyword(s):  
2015 ◽  
Vol 31 (3) ◽  
pp. 431-451 ◽  
Author(s):  
Dilek Yildiz ◽  
Peter W.F. Smith

Abstract Administrative data sources are an important component of population data collection and they have been used in census data production in the Nordic countries since the 1960s. A large amount of information about the population is already collected in administrative data sources by governments. However, there are some challenges to using administrative data sources to estimate population counts by age, sex, and geographical area as well as population characteristics. The main limitation with the administrative data sources is that they only collect information from a subset of the population about specific events, and this may result in either undercoverage or overcoverage of the population. Another issue with the administrative data sources is that the information may not have the same quality for all population groups. This research aims to correct an inaccurate administrative data source by combining aggregate-level administrative data with more accurate marginal distributions or two-way marginal information from an auxiliary data source and produce accurate population estimates in the absence of a traditional census. The methodology developed is applied to estimate population counts by age, sex, and local authority area in England and Wales. The administrative data source used is the Patient Register which suffers from overcoverage, particularly for people between the ages of 20 and 50.


Author(s):  
Sabrina Wong ◽  
Alan Katz ◽  
Tyler Williamson ◽  
Alexander Singer ◽  
Sandra Peterson ◽  
...  

IntroductionFrailty is a complex condition that affects many aspects of a patients’ wellbeing and health outcomes. ObjectivesWe used available Electronic Medical Record (EMR) and administrative data to determine definitionsof frailty. We also examined whether there were differences in demographics or health conditionsamong those identified as frail in either the EMR or administrative data. MethodsEMR and administrative data were linked in British Columbia (BC) and Manitoba (MB) to identifythose aged 65 years and older who were frail. The EMR data were obtained from the CanadianPrimary Care Sentinel Surveillance Network (CPCSSN) and the administrative data (e.g. billing,hospitalizations) was obtained from Population Data BC and the Manitoba Population ResearchData Repository. Sociodemographic characteristics, risk factors, prescribed medications, use andcosts of healthcare are described for those identified as frail. ResultsSociodemographic and utilization differences were found among those identified as frail from theEMR compared to those in the administrative data. Among those who were >65 years, who hada record in both EMR and administrative data, 5%-8% (n=191 of 3,553, BC; n=2,396 of 29,382,MB) were identified as frail. There was a higher likelihood of being frail with increasing age andbeing a woman. In BC and MB, those identified as frail in both data sources have approximatelytwice the number of contacts with primary care (n=20 vs. n=10) and more days in hospital (n=7.2vs. n=1.9 in BC; n=9.8 vs. n=2.8 in MB) compared to those who are not frail; 27% (BC) and 14%(MB) of those identified as frail in 2014 died in 2015. ConclusionsIdentifying frailty using EMR data is particularly challenging because many functional deficits arenot routinely recorded in structured data fields. Our results suggest frailty can be captured along acontinuum using both EMR and administrative data.


BMJ Open ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. e031352 ◽  
Author(s):  
Isabelle Niedhammer ◽  
Allison Milner ◽  
Béatrice Geoffroy-Perez ◽  
Thomas Coutrot ◽  
Anthony D LaMontagne ◽  
...  

IntroductionAlthough evidence has been provided on the associations between psychosocial work exposures and morbidity outcomes in the literature, knowledge appears much more sparse on mortality outcomes. The objective of STRESSJEM is to explore the prospective associations between psychosocial work exposures and mortality outcomes among the national French working population. In this paper, we describe the study protocol, study population, data sources, method for exposure assessment, data analysis and future plans.Methods and analysisData sources will include: the data from the national SUMER survey from DARES on the evaluation of psychosocial work exposures and the data from the COSMOP programme from Santé publique France linking job history (DADS data from INSEE) and mortality according to causes of death (data from the national death registry, INSERM-CépiDc). A sample of 1 511 456 individuals will form the studied prospective cohort for which data are available on both job history and mortality over the period 1976–2002. Psychosocial work exposures will be imputed via a job-exposure matrix using three job title variables that are available in both the SUMER and COSMOP data sets. Our objectives will be to study the associations between various psychosocial work exposures and mortality outcomes. Psychosocial work exposures will include the job strain model factors as well as other psychosocial work factors. Various measures of exposure over time will be used. All-cause and cause-specific mortality will be studied.Ethics and disseminationBoth the SUMER survey and the COSMOP programme have been approved by French ethics committees. Dissemination of the study results will include a series of international peer-reviewed papers and at least one paper in French. The results will be presented in national and international conferences. This project will offer a unique opportunity to explore mortality outcomes in association with psychosocial work exposures in a large national representative sample of the working population.


Author(s):  
Karen Susan Tingay ◽  
Amrita Bandyopadhyay ◽  
Lucy Griffiths ◽  
Ashley Akbari ◽  
Sinead Brophy ◽  
...  

BackgroundIn longitudinal health research, combining the richness of cohort data to the extensiveness of routine data opens up new possibilities, providing information not available from one data source alone. In this study, we set out to extend information from a longitudinal birth cohort study by linking to the cohort child’s routine primary and secondary health care data. The resulting linked datasets will be used to examine health outcomes and patterns of health service utilisation for a set of common childhood health problems. We describe the experiences and challenges of acquiring and linking electronic health records for participants in a national longitudinal study, the UK Millennium Cohort Study (MCS). MethodWritten parental consent to link routine health data to survey responses of the MCS cohort member, mother and her partner was obtained for 90.7% of respondents when interviews took place at age seven years in the MCS. Probabilistic and deterministic linkage was used to link MCS cohort members to multiple routinely-collected health data sources in Wales and Scotland. ResultsOverall linkage rates for the consented population using country-specific health service data sources were 97.6% for Scotland and 99.9% for Wales. Linkage rates between different health data sources ranged from 65.3% to 99.6%. Issues relating to acquisition and linkage of data sources are discussed. ConclusionsLinking longitudinal cohort participants with routine data sources is becoming increasingly popular in population data research. Our results suggest that this is a valid method to enhance information held in both sources of data.


Author(s):  
Emily Mosites ◽  
Sapna Bamrah Morris ◽  
Julie Self ◽  
Jay C Butler

Abstract Homelessness is associated with a multitude of poor health outcomes. However, the full extent of the risks associated with homelessness are not possible to quantify without reliable population data. Here, we outline three federal, publicly-available data sources available to estimate the number of people experiencing homelessness in the United States. We describe the appropriate uses and limitations of each data source in the context of infectious disease epidemiology. These data sources provide an opportunity to expand current research and develop actionable analyses.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Brian Erard

Abstract Although one often has detailed information about participants in a program, the lack of comparable information on non-participants precludes standard qualitative choice estimation. This challenge can be overcome by incorporating a supplementary sample of covariate values from the general population. This paper presents new estimators based on this sampling strategy, which perform comparably to the best existing supplementary sampling estimators. The key advantage of the new estimators is that they readily incorporate sample weights, so that they can be applied to Census surveys and other supplementary data sources that have been generated using complex sample designs. This substantially widens the range of problems that can be addressed under a supplementary sampling estimation framework. The potential for improving precision by incorporating imperfect knowledge of the population prevalence rate is also explored.


2021 ◽  
Vol 13 (12) ◽  
pp. 5747-5801
Author(s):  
Kytt MacManus ◽  
Deborah Balk ◽  
Hasim Engin ◽  
Gordon McGranahan ◽  
Rya Inman

Abstract. The accurate estimation of population living in the low-elevation coastal zone (LECZ) – and at heightened risk from sea level rise – is critically important for policymakers and risk managers worldwide. This characterization of potential exposure depends on robust representations not only of coastal elevation and spatial population data but also of settlements along the urban–rural continuum. The empirical basis for LECZ estimation has improved considerably in the 13 years since it was first estimated that 10 % of the world's population – and an even greater share of the urban population – lived in the LECZ (McGranahan et al., 2007a). Those estimates were constrained in several ways, not only most notably by a single 10 m LECZ but also by a dichotomous urban–rural proxy and population from a single source. This paper updates those initial estimates with newer, improved inputs and provides a range of estimates, along with sensitivity analyses that reveal the importance of understanding the strengths and weaknesses of the underlying data. We estimate that between 750 million and nearly 1.1 billion persons globally, in 2015, live in the ≤ 10 m LECZ, with the variation depending on the elevation and population data sources used. The variations are considerably greater at more disaggregated levels, when finer elevation bands (e.g., the ≤ 5 m LECZ) or differing delineations between urban, quasi-urban and rural populations are considered. Despite these variations, there is general agreement that the LECZ is disproportionately home to urban dwellers and that the urban population in the LECZ has grown more than urban areas outside the LECZ since 1990. We describe the main results across these new elevation, population and urban-proxy data sources in order to guide future research and improvements to characterizing risk in low-elevation coastal zones (https://doi.org/10.7927/d1x1-d702, CIESIN and CIDR, 2021).


2021 ◽  
Author(s):  
Kytt MacManus ◽  
Deborah Balk ◽  
Hasim Engin ◽  
Gordon McGranahan ◽  
Rya Inman

Abstract. The accurate estimation of population living in the Low Elevation Coastal Zone (LECZ), and at heightened risk from sea level rise, is critically important for policy makers and risk managers worldwide. This characterization of potential exposure depends not only on robust representations of coastal elevation and spatial population data, but also of settlements along the urban-rural continuum. The empirical basis for LECZ estimation has improved considerably in the 13 years since it was first estimated that 10 % of the world’s population, and an even greater share of the urban population, lived in the LECZ (McGranahan et al., 2007). Those estimates were constrained in several ways, most notably by a single 10-meter LECZ, but also by a dichotomous urban-rural proxy and population from a single source. This paper updates those initial estimates with newer, improved inputs and provides a range of estimates, along with sensitivity analyses that reveal the importance of understanding the strengths and weaknesses of the underlying data. We estimate that between 750 million to nearly 1.1 billion persons globally, in 2015, live in the ≤ 10 m LECZ, with the variation depending on the elevation and population data sources used. The variations are considerably greater at more disaggregated levels, when finer elevation bands (e.g. the ≤ 5 m LECZ) or differing delineations between urban, quasi-urban and rural populations are considered. Despite these variations, there is general agreement that the LECZ is disproportionately home to urban dwellers, and that the urban population in the LECZ has grown more than urban areas outside the LECZ since 1990. We describe the main results across these new elevation, population, and urban proxy data sources in order to guide future research and improvements to characterizing risk in low elevation coastal zones. DOI: assigned upon completion of data peer-review.


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