Latest news and views from around the Bennett Institute
Our policy lead, Jess Morley, discusses the challenges involved in closing the gap in representation and reward for women working in these fields, and what we in the Bennett Institute are trying to do to help lower some of the associated barriers.
Our latest newsletter including information on: We are recruiting, recent changes to OpenPrescribing Measures, new Outlier Prescribing tool, maps update, recent research publications, OpenSAFELY news, and new data news.
Recently we started reviewing a number of measures that needed the most urgent attention. As a result a number have been updated and a couple have been retired.
I joined Bennett Institute in August 2021 to work as a data scientist on OpenSAFELY. This blog post describes my experience getting up and running with the OpenSAFELY pipeline.
This is a guest blog from the team at Cantabular, who have been exploring how their technology might fit into the OpenSAFELY ecosystem.
The Bennett Institute for Applied Data Science at the University of Oxford has been established to pioneer the better use of data, evidence and digital tools in healthcare and policy, optimizing the impact of interventions to achieve improved outcomes.
All new users of the OpenSAFELY platform get access to our supportive co-pilot programme, where each new OpenSAFELY user is assigned a member of the OpenSAFELY team as their co-pilot for the duration of their project.
This week sees the publication of an independent Citizens’ Jury commissioned for NHSx and the National Data Guardian which found that OpenSAFELY was by far the most strongly and consistently supported of all NHS COVID data projects examined.
On our first anniversary, from the Policy Lead in the Bennett Institute, this is the brief story of the positive side from all our lives: how OpenSAFELY came to life, and what we’ve achieved so far.
Our latest newsletter including information on: new job roles, hospital only measure, total oral morphine equivalence measures, OpenPrescribing and Bennett Institute Papers.
This is a draft discussion paper, the first of a series exploring “open team science” approaches to managing health data, and specifically how to create a collaborative computational data science ecosystem where the sharing and re-use of objects such as codelists and code is facilitated, encouraged, recognised, and rewarded. As a microcosm of this we have first explored “codelists”. There are currently no ‘answers’ or preferred solutions given. We will be holding an open discussion with the research community on 2nd March at 3pm - you can book to join us here.
We have been very busy since our last newsletter back in July and there are tonnes of exciting updates for you here! Measure Update: Total Oral Morphine Equivalence The Faculty of Pain Medicine has recently updated their recommendation on oral morphine equivalence (OME) which we use on our OpenPrescribing measure of OME. We have taken this opportunity to update and a new novel implementation of how we assess OME. Until this work is completed we have taken the decision to “suspend” the measure from dashboards however you can still view the old method using this link.
Victory! We have the hospital medicines data. Now: biologic medicines for severe Asthma In July, Ben and Brian wrote a piece in the British Medical Journal arguing that hospital medicines data should be openly shared. Magnificently, the NHS has now made secondary care medicines data (SCMD) available. You can read the full technical specification of the data here but briefly: it is hospital pharmacy stock control data, which is collected and processed by Rx-Info, and is now published on the NHS Business Services Authority website in the NHS dm+d standard we know, love, and have documented well.
This is the code related to our OpenPathology project. Specifically this repo stores ad-hoc analyses, papers, and related research. The code for the website (and online tool, when developed) are in their own repository.
This is the website code for https://openprescribing.net - a Django application that provides a REST API and dashboards for the English Prescribing Dataset published by the NHS Business Services Authority. Information about data sources used on OpenPrescribing can be found here.
This is the code for the OpenSAFELY cohort extractor tool which supports the authoring of OpenSAFELY-compliant research, by: Allowing developers to generate random data based on their study expectations. They can then use this as input data when developing analytic models. Supporting downloading of codelist CSVs from the OpenSAFELY codelists repository, for incorporation into the study definition Providing tools to understand and visualise the properties of real data, without having direct access to it It is also the mechanism by which cohorts are extracted from live database backends within the OpenSAFELY framework.
This is the repository for the OpenSAFELY job runner. A job runner is a service that encapsulates: the task of checking out an OpenSAFELY study repo; executing actions defined in its project.yaml configuration file when requested via a jobs queue; and storing its results in a particular locations. The documentation is aimed at developers looking for an overview of how the system works. It also has some parts relevant for end users, particularly the project.
This is the code for the OpenSAFELY job server designed for mediating jobs that can be run in an OpenSAFELY secure environment. The Django app provides a simple REST API which provides a channel for communicating between low-security environments (which can request that jobs be run) and high-security environments (where jobs are run).
