The top three things that I have learnt building the simulation model for Monitor's “Moving Healthcare closer to home” report
15 September 2015
Monitor, the regulator for health services in England, wanted to understand whether healthcare can be delivered out of a hospital environment and closer to people’s homes in a more cost effective way. With the NHS under pressure to reduce costs and improve patient outcomes, moving healthcare closer to people's homes is an approach that is widely being considered to help address these challenges. However, there has previously been been a lack of clear evidence about whether this would reduce the overall cost of treating patients. By using simulation analytics we could consider this question in detail, understanding when it would or would not be more cost effective to treat patients closer to home rather than in hospitals. Here's what I learnt from building the simulation model for Monitor:
1) Simulation analytics can provide objective insights to complicated questions
Whether healthcare can be delivered out of a hospital environment in a more cost effective way is a subject that people can feel strongly about, and at times I’ve witnessed passionate disagreements on the topic, in part because this is a complicated question looking at a number of different, interlinked factors. For example, we need to think about a range of factors about the type of care being delivered, the patients that would be affected and the hospitals where the patients would have otherwise been treated.
Simulation analytics allows us to explore the impact of these different variables and to run a large number of simulations to identify when it may or may not be more cost effective to treat patients closer to home for a specific local health economy.
2) A well designed simulation model can make these problems fun and engaging
Seeing a complicated model for the first time can be a frustrating experience. Models often look like they are clever and complicated, but at a glance it can be hard to understand exactly what they’re calculating. Showing our simulation model to people has been a different experience. People are always engaged, asking questions and wanting to find out more. The same people who I have seen looking at complicated models with a sense of horror and panic have found our simulation model interesting, engaging, and even fun to play with.
3) The flexibility of simulation analytics means it can answer a wide range of important strategic questions in health and beyond
The level of insight we discovered about when and how healthcare can be delivered in a cost effective way demonstrates how simulation analytics can deliver powerful, relevant and important findings. I personally can’t wait to start applying some of the same approaches and techniques to other big questions that are difficult to answer.