scholarly journals An Integrated, Scalable, Electronic Video Consent to Power Precision Health Research: A large population-based single institutional cohort implementation and scalability study (Preprint)

10.2196/31121 ◽  
2021 ◽  
Author(s):  
Clara Lajonchere ◽  
Arash Naeim ◽  
Sarah Dry ◽  
Neil Wenger ◽  
David Elashoff ◽  
...  
Keyword(s):  
Health Research ◽  
Large Population ◽  
Population Based ◽  
Precision Health

scholarly journals Measuring high-density built environment for public health research: Uncertainty with respect to data, indicator design and spatial scale

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Guibo Sun ◽  
Chris Webster ◽  
Michael Y. Ni ◽  
Xiaohu Zhang
Keyword(s):  
Hong Kong ◽  
Built Environment ◽  
Urban Health ◽  
Health Research ◽  
Spatial Scales ◽  
Large Population ◽  
Rank Correlation ◽  
Public Health Research ◽  
Population Based ◽  
High Density

Uncertainty with respect to built environment (BE) data collection, measure conceptualization and spatial scales is evident in urban health research, but most findings are from relatively lowdensity contexts. We selected Hong Kong, an iconic high-density city, as the study area as limited research has been conducted on uncertainty in such areas. We used geocoded home addresses (n=5732) from a large population-based cohort in Hong Kong to extract BE measures for the participants’ place of residence based on an internationally recognized BE framework. Variability of the measures was mapped and Spearman’s rank correlation calculated to assess how well the relationships among indicators are preserved across variables and spatial scales. We found extreme variations and uncertainties for the 180 measures collected using comprehensive data and advanced geographic information systems modelling techniques. We highlight the implications of methodological selection and spatial scales of the measures. The results suggest that more robust information regarding urban health research in high-density city would emerge if greater consideration were given to BE data, design methods and spatial scales of the BE measures.

scholarly journals The Constances cohort

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
M Z Zins
Keyword(s):  
Public Health ◽  
Health Research ◽  
Neuropsychological Testing ◽  
Large Population ◽  
Public Health Research ◽  
Population Based ◽  
Industrial Companies ◽  
Wide Range ◽  
Public Health Institutions

Abstract The overarching objective of CONSTANCES is to constitute a research infrastructure based on a large population-based cohort to serve as a versatile, high quality and efficient platform for population health research. Constances is designed as a representative sample of 200,000 adults aged 18-69 at inception living in different regions of France. CONSTANCES, which is accessible to the national and international research community, enables the conduct of valid and well-powered studies in a wide range of scientific domains. For each participant, it combines detailed data collection at baseline, englobing lifestyle, environmental, social, and medical history information, with medical examinations, neuropsychological testing with the added advantage of linkage with two major national administrative data bases (SNDS and CNAV). Further, CONSTANCES collects information about changing lifestyles, environments, health behaviors and health conditions on a prospective ongoing basis. A biobank of blood and urine samples is in the process of being constituted. As of April 2018, 85 nested projects designed by French and international teams in many areas of biomedical and public health research were initiated. Constances participates in several French and international consortiums. We established relationships with public health institutions and industrial companies. In the next years, we plan to continue longitudinal follow-up CONSTANCES along the same lines by extending the follow-up of the cohort and by developing innovative new themes prioritizing the strengthening of certain “niches” where CONSTANCES can have international leadership.

scholarly journals Psychiatric research platform within SAIL - Linkage of prospectively ascertained phenotypically rich and genetic data to routinely collected anonymised records.

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Joanna McGregor ◽  
Ann John ◽  
Keith Lloyd
Keyword(s):  
Mental Health ◽  
Health Research ◽  
Large Population ◽  
Genetic Data ◽  
Population Based ◽  
Mental Health Research ◽  
Response To Treatment ◽  
Psychiatric Research ◽  
Illness Onset ◽  
Polygenic Scores

ABSTRACT ObjectivesWe have conducted a feasibility study linking clinically rich survey data to routine data to create a platform for psychosis research in Wales: K Lloyd et al (2015), A national population-based e-cohort of people with psychosis (PsyCymru) linking prospectively ascertained phenotypically rich and genetic data to routinely collected records: overview, recruitment and linkage, Schizophrenia Research. Now we expand upon this through the linkage of large clinically rich cohorts with a range of mental health diagnoses along with genetic data to conduct validation exercises, develop novel methodologies, assess genetic and environment interactions and outcomes and address hypothesis-driven research questions. ApproachThrough collaborations between the Farr Institute, Cardiff University based MRC centre for Neuropsychiatric Genetics and Genomics and the National Centre for Mental Health (NCMH) clinically rich data and genetic (CNVs, SNPs & polygenic scores) data from around 6000+ participants recruited from a variety of mental health research studies including ‘PsyCymru’, ‘Genetic susceptibility to cognitive deficits study and NCMH amongst others will be loaded and linked to the datasets within SAIL. The analysis plan would firstly include validation exercises to compare the data between sources. Methodologies would be developed using this data to determine illness onset, relapse, chronicity, severity and response to treatment applied to large population-based mental health e-cohorts. ResultsBy pooling together health service data, genetic variants, environmental and lifestyle factors, phenotypic and endo-phenotypic (cognitive scores) along with the ability to ascertain temporal relationships afforded by the longitudinal perspective available in SAIL we may be able to evaluate potential risk factors, assess the complex GxE interactions that lead to disease progression, and assess outcomes such as prognosis, remission, relapse and premature mortality. The on-going routine updates provide us with the opportunity to follow-up these individuals across multiple health care settings in a cost effective and in-obtrusive manner and to carry out health services utilization/benefit and treatment surveillance in a naturalistic setting. This resource will continue to expand over the coming years in size, breadth and depth of data, with continued recruitment and additional measures planned. ConclusionTo advance mental health research by developing our understanding of the causes, course and outcomes of mental illness that may lead to the development of better diagnostic classification, predictive, preventative strategies and therapeutic approaches.

scholarly journals An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study (Preprint)

2021 ◽  
Author(s):  
Clara Lajonchere ◽  
Arash Naeim ◽  
Sarah Dry ◽  
Neil Wenger ◽  
David Elashoff ◽  
...  
Keyword(s):  
Los Angeles ◽  
Health System ◽  
Health Research ◽  
Large Population ◽  
University Of California ◽  
Consent Process ◽  
Academic Health ◽  
Clinical Laboratories ◽  
Explicit Consent ◽  
Precision Health

BACKGROUND Obtaining explicit consent from patients to use their remnant biological samples and deidentified clinical data for research is essential for advancing precision medicine. OBJECTIVE We aimed to describe the operational implementation and scalability of an electronic universal consent process that was used to power an institutional precision health biobank across a large academic health system. METHODS The University of California, Los Angeles, implemented the use of innovative electronic consent videos as the primary recruitment tool for precision health research. The consent videos targeted patients aged ≥18 years across ambulatory clinical laboratories, perioperative settings, and hospital settings. Each of these major areas had slightly different workflows and patient populations. Sociodemographic information, comorbidity data, health utilization data (ambulatory visits, emergency room visits, and hospital admissions), and consent decision data were collected. RESULTS The consenting approach proved scalable across 22 clinical sites (hospital and ambulatory settings). Over 40,000 participants completed the consent process at a rate of 800 to 1000 patients per week over a 2-year time period. Participants were representative of the adult University of California, Los Angeles, Health population. The opt-in rates in the perioperative (16,500/22,519, 73.3%) and ambulatory clinics (2308/3390, 68.1%) were higher than those in clinical laboratories (7506/14,235, 52.7%; <i>P</i>&lt;.001). Patients with higher medical acuity were more likely to opt in. The multivariate analyses showed that African American (odds ratio [OR] 0.53, 95% CI 0.49-0.58; <i>P</i>&lt;.001), Asian (OR 0.72, 95% CI 0.68-0.77; <i>P</i>&lt;.001), and multiple-race populations (OR 0.73, 95% CI 0.69-0.77; <i>P</i>&lt;.001) were less likely to participate than White individuals. CONCLUSIONS This is one of the few large-scale, electronic video–based consent implementation programs that reports a 65.5% (26,314/40,144) average overall opt-in rate across a large academic health system. This rate is higher than those previously reported for email (3.6%) and electronic biobank (50%) informed consent rates. This study demonstrates a scalable recruitment approach for population health research.

Associations between Body Composition and Mortality: A Large Population-Based Cohort Study

2020 ◽  
Author(s):  
Fu-Rong Li ◽  
Pei-Liang Chen ◽  
Xin Cheng ◽  
Hai-Lian Yang ◽  
Wen-Fang Zhong ◽  
...  
Keyword(s):  
Body Composition ◽  
Cohort Study ◽  
Large Population ◽  
Population Based

Fracture Risk in Patients with Myasthenia Gravis: A Population-Based Cohort Study

2021 ◽  
pp. 1-8
Author(s):  
Charles Kassardjian ◽  
Jessica Widdifield ◽  
J. Michael Paterson ◽  
Alexander Kopp ◽  
Chenthila Nagamuthu ◽  
...  
Keyword(s):  
Myasthenia Gravis ◽  
Lower Risk ◽  
Cox Regression ◽  
Large Population ◽  
Population Based ◽  
Osteoporosis Prevention ◽  
Inception Cohort ◽  
Hazard Ratios ◽  
Multiple Covariates ◽  
Region Of Residence

Background: Prednisone is a common treatment for myasthenia gravis (MG), and osteoporosis is a known potential risk of chronic prednisone therapy. Objective: Our aim was to evaluate the risk of serious fractures in a population-based cohort of MG patients. Methods: An inception cohort of patients with MG was identified from administrative health data in Ontario, Canada between April 1, 2002 and December 31, 2015. For each MG patient, we matched 4 general population comparators based on age, sex, and region of residence. Fractures were identified through emergency department and hospitalization data. Crude overall rates and sex-specific rates of fractures were calculated for the MG and comparator groups, as well as rates of specific fractures. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox regression. Results: Among 3,823 incident MG patients (followed for a mean of 5 years), 188 (4.9%) experienced a fracture compared with 741 (4.8%) fractures amongst 15,292 matched comparators. Crude fracture rates were not different between the MG cohort and matched comparators (8.71 vs. 7.98 per 1000 patient years), overall and in men and women separately. After controlling for multiple covariates, MG patients had a significantly lower risk of fracture than comparators (HR 0.74, 95% CI 0.63–0.88). Conclusions: In this large, population-based cohort of incident MG patients, MG patients were at lower risk of a major fracture than comparators. The reasons for this finding are unclear but may highlight the importance osteoporosis prevention.

scholarly journals Estimating the asymptomatic proportion of SARS-CoV-2 infection in the general population: Analysis of nationwide serosurvey data in the Netherlands

2021 ◽  
Author(s):  
Scott A. McDonald ◽  
Fuminari Miura ◽  
Eric R. A. Vos ◽  
Michiel van Boven ◽  
Hester E. de Melker ◽  
...  
Keyword(s):  
The Netherlands ◽  
Population Analysis ◽  
Large Population ◽  
Population Based ◽  
Attributable Risk ◽  
Case Definition ◽  
Aggregated Data ◽  
Age Dependent ◽  
Additive Regression ◽  
June July

Abstract Background The proportion of SARS-CoV-2 positive persons who are asymptomatic—and whether this proportion is age-dependent—are still open research questions. Because an unknown proportion of reported symptoms among SARS-CoV-2 positives will be attributable to another infection or affliction, the observed, or 'crude' proportion without symptoms may underestimate the proportion of persons without symptoms that are caused by SARS-CoV-2 infection. Methods Based on two rounds of a large population-based serological study comprising test results on seropositivity and self-reported symptom history conducted in April/May and June/July 2020 in the Netherlands (n = 7517), we estimated the proportion of reported symptoms among those persons infected with SARS-CoV-2 that is attributable to this infection, where the set of relevant symptoms fulfills the ECDC case definition of COVID-19, using inferential methods for the attributable risk (AR). Generalised additive regression modelling was used to estimate the age-dependent relative risk (RR) of reported symptoms, and the AR and asymptomatic proportion (AP) were calculated from the fitted RR. Results Using age-aggregated data, the 'crude' AP was 37% but the model-estimated AP was 65% (95% CI 63–68%). The estimated AP varied with age, from 74% (95% CI 65–90%) for < 20 years, to 61% (95% CI 57–65%) for the 50–59 years age-group. Conclusion Whereas the 'crude' AP represents a lower bound for the proportion of persons infected with SARS-CoV-2 without COVID-19 symptoms, the AP as estimated via an attributable risk approach represents an upper bound. Age-specific AP estimates can inform the implementation of public health actions such as targetted virological testing and therefore enhance containment strategies.

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