The DataLab is a mixed team of clinicians, academics, and software engineers, all pooling knowledge and skills to create tools like OpenPrescribing.net. We build all our informatics tools in-house, which means our academic research is fully integrated with our software development. Our research program spans four streams of work:
- Innovative informatics methods;
- Practice variation;
- Behaviour change;
- Policy analysis on prescribing and informatics.
1. OpenPrescribing “Informatics Methods” Papers
We publish research papers on the innovative informatics methods we have developed to run our interactive data tools.
Variation in Responsiveness To Warranted Behaviour Change Among NHS Clinicians: a Novel Implementation of Change-Detection Methods in Longitudinal Prescribing Data
Walker AJ, Pretis F, Powell-Smith A, Goldacre B.
BMJ 2019; 367 :l5205. https://doi.org/10.1136/bmj.l5205
Detecting Change in Comparison to Peers in NHS Prescribing Data: a Novel Application of Cumulative Sum Methodology
Walker AJ, Bacon S, Croker R, Goldacre B.
BMC Medical Informatics, 2018, Volume 18, Number 1, Page 1. https://doi.org/10.1186/s12911-018-0642-6
A New Mechanism To Identify Cost Savings in English NHS Prescribing: Minimising “Price-Per-Unit”, a Cross Sectional Study
Croker R, Walker AJ, Bacon S, Curtis HJ, French L, Goldacre B.
BMJ Open 2018;8:e019643.
OpenPrescribing: Normalised Data and Software Tool to Research Trends in English NHS Primary Care Prescribing 1998-2016
Curtis HJ, Goldacre B.
BMJ Open 2018;8:e019921.
OpenPrescribing 1-6: an openly accessible online tool to audit and research prescribing in primary care
Goldacre B, DataLab team.
BMJ, under review.
2. OpenPrescribing “Practice Variation” Papers
We publish research papers on variation in clinical practice in the NHS, across a wide range of medical fields. These papers typically include: 18 year national practice trends, corrected for population and inflation; graphs and atlases of current CCG and GP practice-level variation; 5 year GP practice-level decile trends; and regression analyses to describe factors associated with specific problematic or advantageous prescribing behaviours.
Opioid Prescribing Trends and Geographical Variation in England 1998-2017 – A Retrospective Database Study
Curtis HJ, Croker R, Walker AJ, Richards G, Quinlan J, Goldacre B
Dec 2018, Lancet Psychiatry.
Is Use of Homeopathy Associated With Poor Prescribing in English Primary Care? A Cross-Sectional Study
Walker AJ, Croker R, Bacon S, Curtis H, Goldacre B
Journal of the Royal Society of Medicine 2018 May;111(5):167-174.
Trends and variation in Prescribing of Low-Priority Treatments Identified by NHS England: A Cross-Sectional Study and Interactive Data Tool in English Primary Care
Walker AJ, Croker R, Bacon S, Ernst E, Curtis H, Goldacre B
Journal of the Royal Society of Medicine 2018 Jun;111(6):203-213.
Time Trends and Geographical Variation in Prescribing of Drugs for Diabetes in England 1998-2016
Curtis HJ, Dennis JM, Shields BM, Walker AJ, Bacon S, Hattersley AT, Jones AG, Goldacre B
Diabetes, Obesity & Metabolism. 2018;1–10. https://doi.org/10.1111/dom.13346
Trends, geographic variation, and factors associated with prescribing of gluten-free foods in English primary care: a cross sectional study
Walker AJ, Curtis HJ, Bacon S, Croker R, Goldacre B
BMJ Open, 2018;8:e021312.
Antibiotic Prescribing Trends and Geographical Variation in England 1998-2017 – A Retrospective Database Study
Curtis HJ, Walker AJ, Goldacre B
Journal of Antimicrobial Chemotherapy 2018, dky377 https://doi.org/10.1093/jac/dky377.
Do doctors in dispensing practices with a financial conflict of interest prescribe more expensive drugs? A cross-sectional analysis of English primary care prescribing data.
Goldacre B, Reynolds C, Powell-Smith A, Walker AJ, Yates TA, Croker R, Smeeth L
BMJ Open 2019;9:e026886.
Trends and variation in unsafe prescribing of methotrexate: a cohort study in English NHS primary care.
MacKenna B, Curtis HJ, Walker AJ, Croker R, Bacon S, Goldacre B
Annals of Rheumatological Disease, submitted.
Preprint: medRxiv, submitted.
3. OpenPrescribing “Behaviour Change” Papers
We publish original research papers on how clinical practice is changed in the NHS, including interrupted time series analyses assessing clinicians’ response to new guidelines, evidence landmarks, and price shocks; RCTs and observational research on the impact of the OpenPrescribing.net tools; and research on the diffusion of innovation in primary care.
Impact of NICE Guidance on Tamoxifen Prescribing in England 2011-2016 – An Interrupted Time Series Analysis
Curtis HJ, Walker AJ, Goldacre B
British Journal of Cancer 2018; 118, p1268–1275.
Measuring the Impact of an Open Online Prescribing Data Analysis Service on Clinical Practice: a Cohort Study in NHS England Data
Walker AJ, Curtis HJ, Croker R, Bacon S, Goldacre B
Journal of Medical Internet Research 2019;21(1):e10929
Why did some practices not implement new antibiotic prescribing guidelines on urinary tract infection? A cohort study and survey in NHS England primary care
Croker R, Walker A, Goldacre B
Journal of Antimicrobial Chemotherapy 2018, dky509
Impact of Chief Medical Officer Activity on Prescribing of Antibiotics in England – An Interrupted Time Series Analysis
Walker AJ, Curtis HJ, Goldacre B
Journal of Antimicrobial Chemotherapy, 2019, dky528
Letter: Six months on – NHS England needs to focus on dissemination, implementation and audit of its Low-Priority Initiative
Walker AJ, Bacon S, Curtis HJ, Croker R, MacKenna B, Goldacre B
Journal of the Royal Society of Medicine, 2018
The Effect of Audit & Feedback on Prescribing Behaviour and Engagement with Data on OpenPrescribing.net – A Randomised Controlled Trial
Preprint of protocol: https://doi.org/10.6084/m9.figshare.6188633
Results in draft.
4. OpenPrescribing Policy Papers
We publish research and policy analysis on prescribing and informatics.
Analysis: Implications from the patent litigation over pregabalin
Smyth D, Croker R, Goldacre B
The clinician impact and financial cost to the NHS of litigation over pregabalin: a cohort study in English primary care
Croker R, Smyth D, Walker AJ, Goldacre B
BMJ Open 2018;8:e022416.
The NHS deserves better use of hospital medicines data.
Goldacre B, MacKenna B
BMJ; under second review.
OpenPrescribing: Demonstrating the Benefits of Open Data, Open Source Software, and Open Audit
Ben Goldacre, DataLab co-auths, final draft.
OpenPrescribing: What We Do; What We Need.
Ben Goldacre, presentation to NHS National Information Board, Nov 2017, various others.
The OpenPrescribing Database
We have substantial back-end processes for rapidly importing, processing and matching prescribing data, demographic and clinical information, deprivation scores, age profiles, list sizes, QoF, and more, with a regular cycle of data updates. This is held in a highly optimised and indexed Postgres database to drive our online tools, and mirrored in BigQuery for rapid research queries.
The EBM DataLab Approach
We are very different to other teams, because we pool skills and build all our digital tools in-house. The traditional route to building an informatics service is slow: some senior managers write a specification document, that is given to a software company, who bid a price, and deliver a product 18 months later. Our approach is different: clinicians, academics, and software engineers all work together, to produce rapidly iterating prototypes that are launched and used by the community, with open feedback from all.
This is important: it means we are fast. But more than that, it means we now have clinicians and academics who know about software development, and software developers who know about medical data and evidence-based medicine. Our traditional academic researchers and clinicians can work creatively with software tools such as Python, Jupyter notebooks, Github, Pandas, SQL, and more; they know what is possible with the tools our developers use, so they can be creative in developing new ideas and services. Similarly, our software engineers understand the problems we’re trying to fix in evidence based medicine, clinical trials, prescribing data, and NHS informatics; so they can be much more creative and efficient.
As a consequence of our approach we are able to innovate on short cycles, develop new approaches to data, prototype for rapid testing, and deliver working tools and papers efficiently. Because the DataLab team works across a range of outputs including research integrity, clinical trials, prescribing data, and clinical informatics, we can pool insights across a range of fields. We follow a flexible approach, based on the principles on agile software development. We share all our code on github. We share all our data alongside our papers.
Future DataLab Activity
We have a range of new tools in other areas of medicine under development. Closely related to our work on prescribing we are creating OpenPathology.net. We have a wide range of additional OpenPrescribing research planned around our existing four themes above, including new RCTs and new data science approaches to describing and improving the diffusion of innovation in the NHS; further papers on variation in trends; and more. We are developing new teaching programmes around clinical informatics, and specific teaching and online training around prescribing and prescribing data for clinicians and pharmacists. We are embarking on a programme of practical applied policy research around better use of data in healthcare, and have close links with the policy community. In the DataLab more broadly we also have a wide portfolio of projects in progress across other areas of science, including extensive work on clinical trial methods and reporting, our high impact TrialsTracker.net, and retracted.net.
Get in touch
We are actively seeking funds for more staff to deliver more tools and papers. Some of our best work comes from open collaboration with clinicians, researchers, policymakers, and students: if you would like to work with us then please get in touch. If you want to send a CV, then 2 pages on skills and interests is good.
We are especially keen to hear from:
- Software engineers, clinicians, researchers or students who want to work with us.
- Anyone who uses data in their current clinical / policy role and has hit a problem.
- Policymakers with interesting problems for us to fix.
- Researchers who have hit policy barriers in their work with data.
- Funders who can help us deliver more tools, more papers, and train more workforce.