DISCRETE EVENT SIMULATION MODELLING TO ANALYSE INNOVATIONS IN CANCER PATHOLOGY SERVICES

Purpose:

   The study explores how modelling, in particular discrete event simulation (DES) can be used to explore impacts of new or planned innovations in pathology services on the breast cancer pathway and determine cost-effectiveness of these interventions.

Method(s):

   A structured review of the existing literature was carried out to identify modelling techniques that had previously been used to guide how best to construct the breast cancer model. The literature review identified all relevant health economic material to allow a clear illustration of the extent of evidence available including the types of economic evaluations being undertaken.

   A breast cancer pathway was developed by carrying out a literature search to locate all of the available UK guidelines used to inform clinician decision making. This was further refined by seeking expert opinion by interviewing the clinicians involved along the pathway. Data collected from a UK based hospital further informed the model in order to reflect as best as possible current practice. Based on the UK guidelines, interviews and the hospital data a DES model of the breast cancer pathway was built using the Simul8 software.

Result(s):

   A DES model has been constructed that can be used to analyse the role of pathology services in breast cancer diagnosis and treatment selection through the simulation of individual patients’ experiences, and predict the impact and cost-effectiveness of pathology service innovations.

   The importance of developing such a model was highlighted by the results of the literature review, which was only able to identify 28 economic studies. Over two thirds of the papers research the effect of pathology interventions on breast cancer and nearly 60% originated in the USA. 14 out of 28 papers carried out an economic analysis on the introduction of genetic assays. It was also only this group that presented any type of modelling, incremental cost-effectiveness ratio and sensitivity analysis. The economic evidence for the other interventions was poor.

Conclusion(s):

   The DES model developed can be used to explore how innovations in pathology can impact cancer outcomes. This will add to the limited pool of existing studies that use modelling techniques to investigate pathology interventions. Specifically this is the first DES model created to explore innovations in cancer pathology services.