# Simulate each hospital's cancer pathway as a queue to find and remove the waits

Source: https://onco.cc/ideas/idea-acc-pathway-capacity-simulation/  
OnCo record `idea-acc-pathway-capacity-simulation` (Idea). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

Hospitals rarely know which step, the scanner, the biopsy, the pathologist or the clinic slot, is causing the queue. Modelling the pathway like a factory line shows where a small change would remove weeks of waiting.

## Summary

Discrete-event simulation and queueing analysis are standard in manufacturing and logistics but rarely applied to cancer diagnostic pathways, where a mismatch between weekly clinic capacity and scanner slots can create long waits that no single department sees. A reusable model fed by routine timestamp data would locate the binding constraint per pathway and quantify the effect of interventions before they are made.

## Fields

- Kind: Idea
- Last checked: 2026-09-08
- Hypothesis: Hospitals using pathway simulation to target interventions will reduce the referral-to-treatment interval for at least two tumour pathways by 25% within a year, at lower cost than untargeted capacity expansion.
- Rationale: Operations research routinely finds that a small number of constraints determine throughput and that adding capacity elsewhere achieves nothing; cancer pathways have the same structure.
- Proposed test: Apply the model in five hospitals, implement the top recommendation in each, and measure interval change against five matched hospitals.
- Maturity: speculative
- Actor: engineering

## Sources

- Bottleneck evidence (Fragmented care and guideline gaps): Hanna et al., Mortality due to cancer treatment delay: systematic review and meta-analysis (BMJ 2020): https://doi.org/10.1136/bmj.m4087

## Connected records

- fronts: [AI & Computation](https://onco.cc/fronts/ai-computation/)
- bottlenecks: [Fragmented care and guideline gaps](https://onco.cc/bottlenecks/b-care-fragmentation/), [Not enough oncologists, nurses, pathologists, physicists](https://onco.cc/bottlenecks/b-workforce/)
- key papers: [Mortality due to cancer treatment delay: systematic review and meta-analysis](https://onco.cc/key-papers/paper-hanna-bmj/)

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