Open Access Publication of the Month - May 2020
27 May 2020 | Author: Jaya Chaturvedi, Health Informatician and Data Analyst, Department of Biostatistics and Health Informatics
The OpenSAFELY health data platform: harnessing NHS records to tackle COVID-19
OpenSAFELY is a new secure analytics platform for electronic health records in the NHS, created to deliver urgent results during the global COVID-19 emergency. It is now successfully delivering analyses across more than 24 million patients’ full pseudonymised primary care NHS records, with more to follow. All analytic software is open for security review, scientific review, and re-use. OpenSAFELY uses a new model for enhanced security and timely access to data. This pragmatic and secure approach has allowed the OpenSAFELY team to deliver their first analyses in just five weeks from project start. OpenSAFELY is a collaboration led by two NHS doctors, HDR UK members, Ben Goldacre and Liam Smeeth.
Publication of the month May 2020
A related pre-print publication won HDR UK’s Open Access Publication of the Month in May 2020: “OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients”. This pre-print was selected from latest publications by HDR UK’s Early Career Researcher Committee, and one of its members, Jaya Chaturvedi (Health Informatician and Data Analyst, Department of Biostatistics and Health Informatics at King’s College London, HDR UK London) explains why:
Who is at highest risk of COVID-19?
This publication presents the implementation of a secure and pseudonymised analytics platform, OpenSAFELY, in collaboration with NHS England. Their aim was to establish who is at risk of COVID-19 related death, and why. Their source of data was primary care electronic health records which were pseudonymously linked to data from the COVID-19 Patient Notification System. They included data from over 17 million adult patients from a time period of 1st February 2020 to 25th April 2020. Statistical analysis of this data found that deaths from COVID-19 were strongly associated with the male gender, older age and deprivation, and certain health conditions such as uncontrolled diabetes, severe asthma, and various others. They also focused on the association with ethnicity and found that people with a Black, Asian or other minority ethnic group background appeared to be at higher risk of in-hospital death. Deprivation was also found to be a major risk factor. The OpenSAFELY platform is rapidly adding further NHS patients’ records and will be updating results regularly.
Award-winning features of this work
Amongst the 27 papers reviewed this month, this paper had the highest score overall, and particularly stood out to the committee for various reasons. One of the most impressive features was the scale of the project, representing data from such a large cohort of people and linking it to the COVID-19 Patient Notification System as well as data from the Office for National Statistics. Their commitment to open science was remarkable as well. They made all their codes and algorithms openly available for re-use by the broader research community. They have developed a publicly available website which allows any patients or members of the public to provide feedback. Their focus on equality, diversity and inclusion was another feature that made them stand out for publication of the month by inclusion of ethnicity and deprivation as part of the study. Their greatest strength was the speed at which they were able to execute this project and produce timely results from current patient records.
HDR UK’s Early Career Researcher Committee congratulates and commends the OpenSAFELY Collaborative for their contributions to the research community, and for promoting open science and inclusivity through their work.
Early Career Committee
Meet our Early Career Committee (ECC) who each month, select an Open Access Publication of the Month.
As the national institute for health data, find out how we are championing the use of health data to respond to COVID-19.