Meeting the demand of 111 for primary care services: Reusing

DES
Author

Dr Lucy Morgan

Published

January 6, 2027

Model overview

MOOOD is an open-source discrete-event simulation developed by Richard Pilbery and colleagues. It follows callers after an NHS 111 primary-care disposition and represents subsequent contact with primary care, NHS 111, ambulance services and emergency departments. The Python and SimPy model compares the existing system with timely primary-care contact and reports activity across services and avoidable ED attendance.

The original data and parameters relate to callers registered with Bradford and Airedale GP practices, so reuse elsewhere requires local review and validation.

Session objectives and outline

This session will consider whether participants understand the model well enough to reuse it. Participants will:

  • describe how they think the model is structured from input data through to outputs;
  • compare that understanding with the repository and SimPy implementation;
  • identify how patients, events, services and onward contacts are represented;
  • locate the assumptions controlling demand, pathways and service contact;
  • discuss what they would change for a different question, population or service;
  • trace a selected input assumption through the model to its effect on results; and
  • identify how a change would need to be tested, validated and documented.

The aim is for participants to be able to identify an input or pathway assumption they would change, locate it in the model and assess whether they understand the implementation well enough to make the change confidently.

Actions for participants before the session

  • Retain the working environment and editable repository from Session 1.
  • If you did not attend Session 1, confirm that you can complete a model run before this session.
  • Consider one input, pathway or service assumption you would change for your own analytical question.

Additional resources

Reuse elsewhere will require local review and validation of the demand, capacity, pathway and behavioural assumptions.