Opioid prescribing has risen by 127% in England between 1998 and 2016 Curtis et al, 2018 which along with the US Opioid Crisis has fuelled concern over current opioid prescribing patterns and potential addiction in England. At the direction of the Secretary of State for Health, Public Health England have produced a report the evidence for dependence on, and withdrawal from, prescribed medicines. The first recommendation of this report is
Increasing the availability and use of data on the prescribing of medicines that can cause dependence or withdrawal to support greater transparency and accountability and help ensure practice is consistent and in line with guidance.
OpenPrescribing has over 70 measures of prescribing safety, effectiveness and cost including measures on opioids and opioid prescribing dashboards for every single general practice, primary care network (PCN), clinical commissioning group (CCG), sustainability and transformation partnership (STP), NHS region and for the whole of England. We also have various methods for detecting changes in prescribing and highlighting to prescribers.
This notebook seeks to implement the OpenPrescribing Change Detection python library which has previously been described in a paper in the BMJ on two specific measures (desogestrel & nitrofurantoin/trimethoprim). We aim to support the recomendations of the PHE review by identifing clinical commissioning groups (CCG) and general practices whose prescribing data indicates they have successfully implemented an intervention to reduce prescribing of opioids.
We have also implemeted the CUSUM technique we use for powering the OpenPrescribing bespoke email alerts in this repo to support further investigations.
This is a skeleton project for creating a reproducible, cross-platform analysis notebook, using Docker. It also includes:
- configuration for
jupytext, to support easier code review - cross-platform startup scripts
- best practice folder structure and documentation
Developers and analysts using this skeleton for new development should
refer to DEVELOPERS.md for instructions on getting
started. Update this README.md so it is a suitable introduction to
your project.
Notebooks live in the notebooks/ folder (with an ipynb
extension). You can most easily view them on
nbviewer,
though looking at them in Github should also work.
To do development work, you'll need to set up a local jupyter server
and git repository - see DEVELOPERS.md for more detail.
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