Professional and short courses
|Location||Cavendish, Central London|
|Faculty||Science and Technology|
Planning for both the short and long-term future in health care is vital. Allocating too many resources to a service can lead to waste and overspend, while under-provision can lead to long waiting times and even potential for the loss of lives.
The introduction of a new service or treatment presents further issues in the sense that there may be little or no historic data on which to base cost projections or usage.
In this course, you will learn about tried and tested ways to both generate forecasts in the health care setting and analyse their accuracy. In particular, you will develop an understanding of how to select and justify the appropriate forecasting technique.
Who is this course for?
This course is designed for those engaged in, or supporting, commissioning or provision of health and social care. It helps participants appreciate the value of forecasting in strategic and tactical planning and become familiar with appropriate methods.
To take part in this module, you will need mathematical skills, including simple algebraic manipulation (GCSE grade B or better), and some understanding of basic statistical techniques. You will also need basic IT skills, such as using an Excel spreadsheet.
|Courses no longer available|
|Start date||Duration||Day and time||Price||Apply|
|1 June 2015||1 day||TBA||£350||Already started|
Forecasting in health care
- What forecasting is
- The forecasting process
- Types of problems
- Existing software tools
Time series forecasting
- Key concepts
- Principles of smoothing
- Intermediate and advanced smoothing techniques
Econometric methods for health care forecasting
- basic regression concepts
- least-squared linear regression model
Data preparation and model selection
- collecting and cleaning data
- evaluating forecasting power
- choosing the right forecasting model
- practise learned techniques through several case studies, e.g. GP practice new demand projection, projections of cost and patient numbers over the entire stages of the care pathway for COPD, hospital demand projection
- changes in external factors and outliers
By the end of the course you will be able to:
- appreciate the role and potential benefits of forecasting for estimating future spend and resource use in the healthcare setting
- generate forecasts using time series methods, including simple moving average, exponential smoothing and trend adjusted exponential smoothing
- create forecasts using econometric-based methods, including the linear regression model
- analyse and compare the accuracy of different forecasting methods by analysing their errors
- identify outliers and know when they should be removed to improve forecast accuracy
- incorporate changes factors such as seasonality, changes in population, lifestyle factors and alternative service plans
- perform sensitivity analysis to identify factors that are statistically significant in helping us to understand the future
Philip Worrall obtained a BA (Econ) in Economics from the University of Manchester and an MSc in Operational Research and Management Science from Lancaster University. His MSc project was conducted at the NHS Derbyshire County Primary Care Trust, where he investigated the challenges of building COPD strategic planning models to model long term future demand. At present he studies for a PhD at the University of Westminster on strategic health care planning and forecasting long-term care demand in particular, and works part-time for the NHS London Procurement Programme. He has extensive experience in applying problem structuring and forecasting methods to develop health care modelling tools.