Who should attend
- NHS staff: data analysts, planners and decision makers, clinicians, etc
- It is available to whoever interested in the uncertainty in healthcare.
About the course
Do you always set plans and rarely achieve them because by the time they are published things changed? Do you generate a forecast and it’s always wrong? If these questions are familiar, this workshop is for you. It’s not your fault if your forecast is wrong and your plan fails – traditional deterministic forecasting and planning is seriously incomplete because it ignores uncertainties.
At present, healthcare planning and forecasting is primarily deterministic. Decision making based on deterministic analysis are made based on exact numbers (average) and generally follows a “go-no go” framework. If we forecast and plan too low, we cause shortages and plan disruption, if we forecast and plan too high, we create waste and inefficiency. Therefore, decision making based on deterministic analysis may result in aggressive or conservative cases which may lead to suboptimal plans. Moreover, changes in patients’ needs, demography, regulatory framework, health services triggered and driven by crisis, innovation in treatments, technologies and care models introduce new uncertainties that cannot be solely addresses by deterministic forecasting and planning.
Healthcare planers are looking for approaches to address challenges related to uncertainties in the sector. Probabilistic forecasting and planning techniques have the potential to address these concerns and consider various type of uncertainties facing planners in more rigorous manner. There is a clear need in the healthcare to highlight how probabilistic forecasting and planning can be used to address uncertainty challenges facing the sector.
In this 2-day workshop you will:
- discover how probabilistic planning and forecasting can empower your organisation to make better decisions
- learn how to use R software to produce probabilistic forecast.
What you’ll learn
- Describe uncertainties facing healthcare and their consequences
- Quantify healthcare uncertainties
- Identify benefits of probabilistic planning and forecasting
- Produce probabilistic forecast and measure its accuracy
- Distinguish probabilistic forecasting from statistical forecasting
- Include probabilistic planning and forecasting in current processes.
- Uncertainty in healthcare
- Probabilistic forecasting and planning.
- Have a greater appreciation and understanding of healthcare uncertainty and its consequences
- Gain expertise to apply probabilistic planning and forecasting in an organisation
- Learn how to quantify uncertainty
- Gain insights from successful cases in using probabilistic planning and forecasting
- Hear from three unique companies in the World that use probabilistic forecasting and planning in their solution.
Bahman is Senior Lecturer (Associate Professor) in Management Science at Cardiff Business School, Cardiff University. Bahman's life objective is to help the world becoming a better place by freely offering his skills and developing free resources. Bahman holds a Ph.D. in Industrial Engineering ...
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.