This page showcases some of the work done by teams within NHS England.
We aim to deliver world-class data and services to improve the health and wellbeing of people in England by using data, curation and advanced analytics in innovative ways.
We have created this site with this mission in mind, to share and discuss open-source technology work. We will also distribute our code, publications and internal tools for feedback, with the hope this can help us improve our production processes.
Note The repo is curated by the Data Science team: to contact us raise an issue on GitHub or via email (england.RAPchampions@nhs.net) and we will respond promptly.
Repo name | Description | Languages | Published Report |
---|---|---|---|
Open data standards | Draft of open data CSV standards for comment | Markdown | No |
Data Visualisation for Health and Care Community of Practice | Committe of folk working in data visualisation across CSUs, Trusts, NHS Digital, NHS England and others. | Various | No |
Medicines text mining tool | Medicines text mining application. | Python, PySpark | No |
MPS Diagnostics | Interpretable metadata for MPS record linkage and Person ID | Python, PySpark | User Guide |
NHSD analytics services blog | Repo for blog webpage | HTML, CSS | No |
codonPython | Aim to reduce the DAE barrier for new analysts at NHSD. | Python | No |
Artificial Data Generator | Pipelines and reusable code for generating anonymous artificial versions of NHS Digital assets in Databricks. | Python, PySpark | No |
DNAttend | ML framework for predicting patient non-attendance | Python | Documentation |
nhs_time_of_travel | This GitHub repository and accompanying webpage contain the initial proof of concept and exploratory analysis for the design of a holistic and interactive mapping tool to support decision-making in health and social care. | Python | Yes |
MedicalMap | A collaborative open source project between NHS Python Community and Google Health, building on nhs_time_of_travel to create various mapping functionality in a streamlit app | Python | No |
open-cyber | A webpage giving select headline stats on cybersecurity in healthcare organisations | Python | Site |
antibiotic_cost | Plotly chart and folium map visualizing the prescribing cost of the antibiotics Amoxicillin, Doxycycline Hyclate and Caefalexin for Clinical Commissioning Groups (CCGs) | Python | Site |
open-health-statistcs | Statistics on open source healthcare repositories | Python | Site |
Forecasting | A repo of different forecasting methods for different situations | Python | No |
SynPath | Proof Of Concept - Open Patient Pathway Generator using and an agent based approach | Python | Report |
MultiNet | This command line tool provides user-friendly and automated multi-morbidity network analysis. Detect significant associations are correcting for confounding factors such as Age and Sex. Includes community detection for un-directed networks. Option to build directed networks when diagnosis times are available. | Python | No |
ambulance-DES | Proof of concept simmer discrete event simulation for the ambulance setting | R | Conference Slides |
HSMA4-12-DES-rheum | Discrete Event Simulation - The role of Patient Initiated Follow-up in supporting the elective recovery in rheumatology | R | No |
eLfH-PHM-RiskStrat | A worked example to support the e-Learning for Health (e-LfH) PHM Risk Stratification Module. | R | No |
ai-dictionary | Prototype AI Dictionary from the NHS AI Lab | JavaScript | Site |
SystemHierarchies | Aiming to visualise and represent the structure and mapping of different NHS organisations | Python | No |
nhse-io-jekyll-template | Template for io pages using Jekyll incorporating the NHS service manual | html, Ruby | Site |
see Internship Site for more details
Repo Name | Description | Languages | Published Report |
---|---|---|---|
SynthVAE | NHSE DS Internship developing a Synthetic data generation by a Variational AutoEncoder with Differential Privacy assessed using Synthetic Data Vault metrics | Python | Reports |
SynPath_Diabetes | NHSE DS Internship developing a SynPath module for generating type 2 diabetes pathway | Python | Report |
Diabetes Prevalence Management and Health Inequalities | NHSE DS Internship looking at how to identify inequalities in population health data | Python | Report |
stm-survey-text | NHSE DS Internship developing a Structural Topic Modelling code to gain insights from free text responses to NHS surveys and their associated metadata | Python | Report |
LIME-XAI-Facial-Disease-Classification | NHSE DS Internship Scheme project investigating if a LIME application using superpixels is appropriate for facial healthcare image classification | Python | Report |
TxtRayAlign | NHSE DS Internship exploring contrastive alignment of image and text encoders for image-based radiology report retrieval and generation, and identification of possible evaluation metrics | Python | Reports |
commercial-data-healthcare-predictions | NHSE DS Internship investigating of the value of commercial sales data on respiratory death predictions using Model Class Reliance | Python | Report |
NHSSynth | NHSE DS Internship developing a Python package alongside research and investigative materials covering the effectiveness of the package and synthetic data more generally when applied to NHS use cases. | Python | No |
ELM4PSIR | NHSE DS Internship exploring Language Modelling for (NHS) Patient Safety Incident Reports - DART PhD Internship Project | Python | Report |
Repo name | Description | Languages | Published Report |
---|---|---|---|
RAP Community of Practice | Collection of NHSD RAP resources to help analysts adopt and apply RAP practices. The github pages website of this repo is here: RAP Community of Practice Website | Python, PySpark, Markdown | No |
RAP package template | RAP package template | Python | No |
RAP Example Pipeline - PySpark | Example of good practices in a simple pipeline using artificial HES data | Python | No |
An easy way to find all fo the NHS Digital publication repos, is to look at the #nhs-digital-publication topic
Repo name | Description | Languages | Published Report | First Published |
---|---|---|---|---|
ASC-Outcomes-Framework | This is the code repository for Adult Social Care Outcomes Framework | Python | ✔️ | 2023-04-17 |
ASC-Overview | Code repository for Adult Social Care Overview | Python | ✔️ | 2023-06-13 |
ASC-Safeguarding-Adults | Safeguarding Adults is a legal obligation for English Councils responsible for Adult Social Services. It aims to protect vulnerable adults from abuse or neglect. The Safeguarding Adults Collection (SAC) gathers data from these councils, generating insights on national, regional, and local safeguarding efforts. | Python | ✔️ | 2023-06-13 |
ASC-User-Survey | Code repository for the Personal Social Services Adult Social Care Survey publication | R, Python, Markdown | ✔️ | 2022-09-20 |
ASC_LA_Peer_Groups | Calculates statistical neighbours (aka peers) for Local Authorities in England, for use in Adult Social Care statistics. | Python, Markdown | ✔️ | 2024-01-16 |
GDPPR_Analytical_Code | To share analysis code using the GDPPR dataset. | SQL, Python, Markdown | ✔️ | 2021-03-08 |
IAPT Patient Outcomes Data Science Accelerator Project | Code used to produce the Data Science Accelerator on IAPT patient outcomes | Python, Markdown | 2022-11-03 | |
idhc_publication | Code used to produce the Learning Disability Health Check Scheme publication | Python | ✔️ | 2023-04-17 |
iif_indicators | Code for the following IIF indicators: AC-02: Emergency admissions for specified Ambulatory Care Sensitive Conditions per registered patient. ACC-08: Number of general practice appointments for which the time from booking to appointment was two weeks or less. EHCH-04: Number of general practice appointments categorised as 'patient contact as part of weekly care home round'. | Python, PySpark | 2023-01-10 | |
mental-health-act-annual-statistics | This repository contains all of code used to create the Annual Uses of The Mental Health Act publication. | Python, PySpark | ✔️ | 2023-06-29 |
mental-health-bulletin | This repository contains all of code used to create the Mental Health Bulletin publication. | Python, PySpark | ✔️ | 2023-06-29 |
mental-health-monthly-statistics | This repository contains all of code used to create the Mental Health Monthly Statistics publication. | Python, PySpark | ✔️ | 2023-06-29 |
National Child Measurement Programme Provisional Report Code | Codebase for NCMP Report publication | SQL, Python | ✔️ | 2022-08-11 |
National Child Measurement Programme Report Code | Codebase for NCMP Report publication | SQL, Python | ✔️ | 2022-12-12 |
National Diabetes Audit | A sample repo for working with Reproducible Analytical Pipelines (RAP). | Python, PySpark | 2021-10-14 | |
NCDes package | Code used to produce the Network Contract Directed Enhanced Service publication | Python, Markdown | ✔️ | 2022-10-07 |
NHS-Breast-Screening-Programme-Report-Code | Code repository for the NHS Breast Screening Programme report | Python | ✔️ | 2023-03-15 |
Sexual-Reproductive-Health-Services-Report-Code | This project produces the required publication outputs for the Sexual and Reproductive Health Services (Contraception) publication: Data tables, charts, and map data. | Python | ✔️ | 2023-06-19 |
Smoking-Drinking-and-Drug-Use-Report-Code | Code repository for the Smoking Drinking and Drug Use Report | R, Python, Markdown | ✔️ | 2022-08-26 |
Workforce: Absence Rates | Codebase for Absence Rates publication | SQL, Python | ✔️ | 2022-07-21 |
Please visit our NHS Digital Blog to discover the latest developments and updates from our analytics teams.
Our teams design, develop and operate the national IT and data services that support clinicians at work, help patients get the best care, and use data to improve health and care. Our mission demands smart, usable, and reliable technology. Come serve the people by helping us design and build better products.
Learn more about the work we do in Data, Insights and Statistics group of the Data services - NHS Digital.
Data Analytics Services codebase is released under the MIT License.
The documentation is © Crown copyright and available under the terms of the Open Government 3.0 licence.