scholarly journals La déclaration RECORD (Reporting of Studies Conducted Using Observational Routinely Collected Health Data) : directives pour la communication des études réalisées à partir de données de santé collectées en routine

2019 ◽  
Vol 191 (8) ◽  
pp. E216-E230
Author(s):  
Eric I. Benchimol ◽  
Liam Smeeth ◽  
Astrid Guttmann ◽  
Katie Harron ◽  
David Moher ◽  
...  
Keyword(s):  
Health Data ◽  
Routinely Collected Health Data

scholarly journals The RECORD reporting guidelines: meeting the methodological and ethical demands of transparency in research using routinely-collected health data

2016 ◽  
Vol Volume 8 ◽  
pp. 389-392 ◽  
Author(s):  
Stuart Nicholls ◽  
Sinead Langan ◽  
Henrik Toft Sørensen ◽  
Irene Petersen ◽  
Eric Benchimol
Keyword(s):  
Health Data ◽  
Reporting Guidelines ◽  
Routinely Collected Health Data

Occupational groups and ischaemic heart disease in New Zealand – a longitudinal linkage study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
L.A Barnes ◽  
A Eng ◽  
M Corbin ◽  
H.J Denison ◽  
A t'Mannetje ◽  
...  
Keyword(s):  
Heart Disease ◽  
New Zealand ◽  
Ischaemic Heart Disease ◽  
Cox Regression ◽  
Health Data ◽  
Funding Source ◽  
Inverse Association ◽  
Occupational Groups ◽  
Routinely Collected Health Data ◽  
Machine Operators

Abstract Background/Introduction Occupation is a poorly characterised risk factor for cardiovascular disease (CVD), with females and minority populations particularly under-represented in research. There is also a lack of longitudinal studies using detailed health data that does not rely on self-reports. Purpose This study aimed to address these gaps by assessing the association between a range of occupational groups and ischaemic heart disease (IHD) in New Zealand (NZ), through linkage of population-based occupational surveys to routinely collected health data. Half of the study population were females and 40% were indigenous Māori (who comprise 15% of the total 4.8 million NZ population), which enabled sex and ethnicity-specific aspects of the relationship between occupation and IHD to be assessed. Methods Two probability-based sample surveys of the NZ adult population (New Zealand Workforce Survey (NZWS); 2004–2006; n=3003) and of the Māori population (NZWS Māori; 2009–2010; n=2107), for which detailed occupational histories and lifestyle factors were collected, were linked with routinely collected health data available through Statistics NZ. Cox regression was used to calculate hazard ratios (HR) for “ever-worked” in any one of nine major occupational groups, with “never worked” in that occupational group defined as the reference group. Analyses were controlled for age, deprivation and smoking, and stratified by sex and ethnicity. Results The strongest associations were found for “plant/machine operators and assemblers” and “elementary workers”, particularly among female Māori (HR 2.19, 95% CI 1.16–4.13 and HR 2.03, 1.07–3.82 respectively). In contrast, inverse associations with IHD across all groups were observed for “technicians and associate professionals”, which was significant for NZWS males (HR 0.52, 0.32–0.84). There were some sex and ethnic differences, particularly for “clerks”, where a positive association was found for NZWS males (HR 1.81, 1.19–2.74), whilst an inverse association was observed for Māori females (HR 0.42, 0.22–0.82). Duration analyses (≤2 years, 2–10 years and 10+ years) showed significant dose-response trends for “clerks” in NZWS males, and “plant/machine operators and assemblers” and “elementary workers” in Māori females. Further adjustments for other potential confounders such diabetes mellitus, hypertension and high cholesterol did not affect the results. Conclusion Associations between occupation and IHD differed significantly across occupational groups and between sexes and ethnicities, even within the same occupational groups. This suggests that results may not be generalised across these groups and occupational interventions to reduce IHD risk may therefore need different approaches depending on the population and specific groups of interest. Funding Acknowledgement Type of funding source: Other. Main funding source(s): Health Research Council (HRC) of New Zealand

scholarly journals 173 Systematic review of atopic dermatitis disease definitions in routinely-collected health data

2017 ◽  
Vol 137 (5) ◽  
pp. S29 ◽  
Author(s):  
M.P. Dizon ◽  
A.M. Yu ◽  
R.K. Singh ◽  
J. Wan ◽  
D.J. Margolis ◽  
...  
Keyword(s):  
Systematic Review ◽  
Atopic Dermatitis ◽  
Health Data ◽  
Routinely Collected Health Data

scholarly journals Why are feasibility studies accessing routinely collected health data? A systematic review

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 815
Author(s):  
Aziza Mirza ◽  
Victoria Yorke-Edwards ◽  
Sarah Lensen ◽  
Macey L. Murray ◽  
Carlos Diaz-Montana ◽  
...  
Keyword(s):  
Controlled Trial ◽  
Feasibility Studies ◽  
Health Data ◽  
Patient Recruitment ◽  
Research And Innovation ◽  
Routinely Collected Health Data ◽  
Randomised Controlled ◽  
The Uk ◽  
National Databases

Background: Feasibility trials are often undertaken to determine whether a larger randomised controlled trial (RCT) is achievable. In a recent review, 15 feasibility trials accessed routinely collected health data (RCHD) from UK national databases and registries. This paper looks at attributes of these trials and the reasons why they accessed RCHD.  Methods: We extracted data from all publicly available sources for the 15 feasibility studies found in a previous review of trials successfully accessing RCHD in the UK between 2013–2018 for the purpose of informing or supplementing participant data. We extracted trial characteristics, the registry accessed, and the way the RCHD was used.  Results: The 15 feasibility RCTs were conducted in a variety of disease areas, and were generally small (median sample size 100, range 41–4061) and individually randomised (60%, 9/15). The primary trial outcome was predominantly administrative (non-clinical) (80%, 12/15) such as feasibility of patient recruitment. They were more likely to recruit from secondary care (67%, 10/15) settings than primary (33%, 5/15).  NHS Digital was the most commonly accessed registry (33% (5/15)) with SAIL databank (20% (3/15)), electronic Data Research and Innovation Service (eDRIS) and Paediatric Intensive Care Audit Network (PICANET) (each 13% 2/15) also being accessed. Where the information was clear, the trials used RCHD for data collection during the trial (47%, 7/15), follow-up after the trial (27%, 4/15) and recruitment (13%, 2/15).  Conclusions: Between 2013 and 2018, 15 feasibility trials successfully accessed UK RCHD. Feasibility trials would benefit, as with other trials, from guidance on reporting the use of RCHD in protocols and publications.

scholarly journals Use of routinely collected health data in randomised clinical trials: comparison of trial-specific death data in the BOSS trial with NHS Digital data

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Sharon B. Love ◽  
Anna Kilanowski ◽  
Victoria Yorke-Edwards ◽  
Oliver Old ◽  
Hugh Barr ◽  
...  
Keyword(s):  
Overall Survival ◽  
Clinical Trials ◽  
Oesophageal Cancer ◽  
Health Data ◽  
Digital Data ◽  
Phase Iii ◽  
Specific Data ◽  
Routinely Collected Health Data ◽  
Death Data

Abstract Background A promising approach to reduce the increasing costs of clinical trials is the use of routinely collected health data as participant data. However, the quality of this data could limit its usability as trial participant data. Methods The BOSS trial is a randomised controlled trial comparing regular endoscopies versus endoscopies at need in patients with Barrett’s oesophagus with primary endpoint death. Data on death and cancer collected every 2 years after randomisation (trial-specific data) were compared to data received annually (all patients on one date) from the routinely collected health data source National Health Service (NHS) Digital. We investigated completeness, agreement and timeliness and looked at the implications for the primary trial outcome. Completeness and agreement were assessed by evaluating the number of reported and missing cases and any disparities between reported dates. Timeliness was considered by graphing the year a death was first reported in the trial-specific data against that for NHS Digital data. Implications on the primary trial outcome, overall survival, of using one of the data sources alone were investigated using Kaplan-Meier graphs. To assess the utility of cause of death and cancer diagnoses, oesophageal cancer cases were compared. Results NHS Digital datasets included more deaths and often reported them sooner than the trial-specific data. The number reported as being from oesophageal cancer was similar in both datasets. Due to time lag in reporting and missing cases, the event rate appeared higher using the NHS Digital data. Conclusion NHS Digital death data is useful for calculating overall survival where trial-specific follow-up is only every 2 years from randomisation and the follow-up requires patient response. The cancer data was not a large enough sample to assess usability. We suggest that this assessment of registry data is done for more phase III RCTs and for more registry data to get a more complete picture of when RCHD would be useful in phase III RCT. Trial registration ISRCTN54190466 (BOSS) 1 Oct 2009.

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