OpenPrescribing Research

The Bennett Institute for Applied Data Science is a mixed team of clinicians, academics, and software engineers, all pooling knowledge and skills to create tools like OpenPrescribing.net (read more about these tools here). 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:

  1. Innovative informatics methods;
  2. Practice variation;
  3. Behaviour change;
  4. 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.

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.
https://doi.org/10.1136/bmjopen-2017-019643

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.
https://doi.org/10.1136/bmjopen-2017-019921

Variation in responsiveness to warranted behaviour change among NHS clinicians: novel implementation of change detection methods in longitudinal prescribing data
Walker AJ, Pretis F, Powell-Smith A, Goldacre B
BMJ 2019;367:l5205
doi: https://doi.org/10.1136/bmj.l5205

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 Sub-ICB Location 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.
https://doi.org/10.1016/S2215-0366(18)30471-1

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.
https://doi.org/10.1177/0141076818765779

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.
https://doi.org/10.1177/0141076818769408

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.
https://doi.org/10.1136/bmjopen-2017-021312

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
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.
https://doi.org/10.1136/bmjopen-2018-026886

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
British Journal of General Practice 2020; 70 (696): e481-e488.
https://doi.org/10.3399/bjgp20X710993

Impact Of Electronic Health Record Interface Design On Unsafe Prescribing Of Ciclosporin, Tacrolimus and Diltiazem: A Cohort Study In English NHS Primary Care
MacKenna B, Curtis HJ, Walker AJ, Croker R, Bacon S, Goldacre B
JMIR 2020 Oct 16;22(10):e17003.
https://doi.org/10.2196/17003

Suboptimal Prescribing Behaviour Associated With Clinical Software Design Features: A Retrospective Cohort Study In English NHS Primary Care.
MacKenna B, Curtis HJ, Walker AJ, Croker R, Bacon S, Goldacre B
British Journal of General Practice. Accepted, in production. Preprint: https://doi.org/10.3399/bjgp20x712313

Trends and variation in prescribing of suboptimal statin treatment regimes: a cohort study in English primary care
Curtis HJ, Walker AJ, MacKenna B, Croker R,,Goldacre B
British Journal of General Practice 2020; 70 (698): e636-e643.
https://doi.org/10.3399/bjgp20X712313

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.
https://doi.org/10.1038/s41416-018-0065-2

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
https://doi.org/10.2196/10929

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
https://doi.org/10.1093/jac/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
https://doi.org/10.1093/jac/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
https://doi.org/10.1177%2F0141076818808429

Evaluating the impact of a very low-cost intervention to increase practices’ engagement with data and change prescribing behaviour: a randomized trial in English primary care
Curtis H, Bacon S, Croker R, Walker A, Perera R, Hallsworth M, Harper H, Mahtani K, Heneghan C, Goldacre B
Family Practice,38;373–380
https://doi.org/10.1093/fampra/cmaa128

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
BMJ 2018;361:k2318
https://doi.org/10.1136/bmj.k2318

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.
https://doi.org/10.1136/bmjopen-2018-022416

Barriers to Working With National Health Service England’s Open
Data: Viewpoint

Bacon S, Goldacre B.
JMIR. 2020;22(1):e15603
https://doi.org/10.2196/15603

The NHS deserves better use of hospital medicines data.
Goldacre B, MacKenna B
BMJ 2020;370:m2607.
https://doi.org/10.1136/bmj.m2607

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 Bennett Institute 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.

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.

Please contact [email protected] or [email protected].

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