# Future plans

We started by creating the simplest model. We are building on it iteratively, adding complexity in stages aligned with ambulance service use cases. At each stage, we will assess whether the additional detail meaningfully improves validity or whether a simpler model remains sufficient.


# Resource types

This stage would distinguish between resource types, for example cars and double-crewed ambulances (DCAs).

Relevant time information has already been provided for this work.


# Spatial model

This stage adds **geography**: a single model containing all locations (counties or finer areas), so spatial variation and cross-location interactions are simulated together rather than via separate runs.

Key question:

> When vehicle hours change in one county, how are response time and utilisation affected both locally and in neighbouring counties?

Arrivals and resources become linked to area - county or smaller.

Brings with it possible changes to e.g., travel times (as can estimate now based on distance), and demand profiles (e.g., vary by area).

There will be alot to figure here about how to do things, but can address at later stage.

- E.g. Whether do **times, catetgories and conveyance by area**.
- Where ambulances **start from and where they go** after release.
- How we model **travel times**.

Other things to consider would be:

- What **size area** is required to answer this question?
- Does this question require **shifts** in the model?
- **Socioeconomic inequalities**… Could explore outcome of not just reducing overall response time, but about gaps in response time between more and less deprived? Although, in this case, sometimes it's about rurality rather than socioeconomic - with actually better response times for lower SES.
- Is it relevant to know proportion of crews going straight from one job to the next versus returning to station between jobs? Here or elsewhere?
  - They can be cleared at hospital
  - Depending on whether there's a job straight away, they'll either remain at hospital, or return to base, or return to dispatch point.
  - Will also depends on whether close to break window or end of shift.


# Station-level model

This stage moves to **lower-level geographies** so stations can be modelled. Resources can be allocated to sites and we can model deployment, dispatching and repositioning policies.

Key question: *What is the impact of adding/moving/removing individual station shifts?*

For example, identifying stations with low utilisation, as candidates.

This requires representing individual stations explicitly. And linking resources to those.

Depending on how model a station and what incorporate in prior stage, may not be super different structure. Just requires **sufficiently small areas** to represent different stations.

System should be like this (although reality can be different with high demand and queues and so on): System status plan. What is most likely location of next call. Lord Carter 2018, all staff book on at a main operating hub, then get sent out to a community ambulance point. They don't start/finish there but are sent there and response from there. That decision on where to send them and that is based on system status plan as well as dynamic changes. THe choice varies during the day. Each location gets a priority level e.g., in 4th window, each location x priority. Use data to create plan. Then manager dynamically changes it on the day. But plan e.g., first crew on call to priority 1.