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Partial codebase for project characterising groups of NHS GP online service users based on 2021 GP Patient Survey.

License: MIT License

R 100.00%
clustering digital-inclusion hierarchical-clustering multivariate-regression survey-analysis

gpps-online-services's Introduction

GPPS - Characterisation and Segmentation of online (health) service users

NHS England Analytical Insights

About the Project

status: experimental

This repository holds code for the project on the Characterisation and segmentation of online (health) servie users. Research project using the GP Patient Survey (GPPS) 2021 row-level data to support NHSE evidence-based decision-making and strategy on Customer Experience and Digital Inclusion.

Questions to be answered:

  • Who uses (GP) online services*? Which groups may be excluded?
  • How do characteristics like a) sociodemographics ; b) clinical characteristics; c) local area internet speed, internet user profile and enablement; affect use* ? Which are more prominent?
  • Can we create clusters or pen portraits based on types of online health service users*?

Note: Only public or fake data are shared in this repository.

Project Stucture

  • The main code is found iin folder src (see Usage below for more information)
  • More information about the code usage can be found in the model card
  • {OTHER REPO STRUCTURE}

Built With

R

  • {LIST OF MAIN PACKAGE VERSIONS}

Getting Started

Installation

To get a local copy up and running follow these simple steps.

To clone the repo:

git clone https://github.com/nhsx/{REPO NAME}

To create a suitable environment:

  • Open or create an R project in the root folder.

Usage

  • Repo in construction. Codebase to be added.

Outputs

  • Stakeholder deck with insights and avenues for further use of techniques in research.
  • HACA 2023 conference presentation, available here .

{NOTES ON REPRODUCIBILITY OF RESULTS}

Datasets

  • GP Patient Survey (GPPS) 2021, selected questions. More information on the survey is available here. Aggregate information is available online but this work required access to the respondent-level information through an internal data access request and IG clearance.

  • CDRC Internet User Classification. Dataset available here.

  • POMI (Patient Online Management Information). Dataset available here.

  • We aim to in due course share a dummy data version for the core GPPS data, against which the code could be run (though insights themselves will not be obtained or reproduced given the expected random and non-multivariately correlated nature of this dummy dataset).

Roadmap

See the {LINK TO REPO ISSUES} for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

See CONTRIBUTING.md for detailed guidance.

License

Unless stated otherwise, the codebase is released under the MIT Licence. This covers both the codebase and any sample code in the documentation.

See LICENSE for more information.

The documentation is © Crown copyright and available under the terms of the Open Government 3.0 licence.

Contact

To find out more about the Digitial Analytics and Research Team visit our project website or get in touch at [email protected].

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