First of all, it is important to clearly define the healthcare demand and to identify the levels at which it is to be set. Secondly, we have to unlock all the available data and inspect its quality and usability for the purpose. We carry out the necessary quality improvements and supplement the data with relevant data sources.
This produces a good analysis database that we can use to build forecasting models.
To make forecasting models, we have unique state-of-the-art software which makes a tangible difference from the usual statistics packages such as SPSS and SAS. It has been developed by specialists who work exclusively on forecasting and brings together the full range of knowledge in their field. For example, how to deal with missing data, outliers and the detection of causality. Healthcare quality criteria can also be involved in the models too.
This software also offers a whole host of possibilities for the scenario approach and the performance of what-if analyses.
The forecasts of healthcare demand should lead to better procurement of good-quality healthcare. This in turn generates practical data which enables the organisation to optimise the models.
If necessary, we can help the business to use the software and implement the models autonomously. This can be achieved, for example, by further improving the data housekeeping and infrastructure with people with the right knowledge and skills and with appropriate working methods. We make the organisation nimble so that it can respond quickly to changes and incidents.
9 April 2018
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24 March 2017
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