Embracing Uncertainty in Healthcare
Using probabilistic forecasting and planning to make better decisions
About the Event
We invited six distinguished academics and practitioners to discuss the topic on Tuesday 17th of November 2020.
Why did we organise this event?
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? 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.
Benefits for researchers and practitioners
- Hear from three unique commercial software leaders in the World that use probabilistic forecasting and planning in their solution
- Have a greater appreciation and understanding of healthcare uncertainty and its consequences
- Better understanding of approaches to quantify uncertainty
- Gain insights from successful cases in using probabilistic planning and forecasting in healthcare
- Gain knowledge on how to include probabilistic planning and forecasting in the current processes of your organisation
Agenda of the event
|10:15||Peter Spilsbury, Director, The Strategy Unit||UK||Uncertainty in healthcare and its challenges and consequences for planning|
|10:50||Kieran Chandler, Solution Specialist, Lokad||France||Quantifying Uncertainty in Healthcare|
|11:45||James Triggs, Chief Operating Officer of Brookes SCS||UK||An application of probabilistic forecasting to plan and optimise the NHS England Blood & Transplant supply chain|
|12:20||Stefan de Kok, Founding CEO of Wahupa||USA||Including probabilistic forecasting and planning in current processes|
|13:45||John Watkins, Consultant Epidemiologist Cardiff University/ Public Health Wales||UK||Modelling in the age of COVID-19|
|14:20||Siddharth Arora, Fellow in Management Science, University of Oxford||UK||Role of Probabilistic Forecasting and Machine Learning in Emergency Healthcare|
Recordings and presentations
The individual recordings are accessible below:
Speaker: Mr. Peter Spilsbury, Director, The Strategy Unit, UK
Speaker: Mr. Kieran Chandler, Solution Specialist, Lokad, France
Speaker: Mr. James Triggs, Chief Operating Officer of Brookes SCS (ToolsGroup’s UK partner, formerly known as ToolsGroup UK), UK
Speaker: Mr. Stefan de Kok, Founding CEO of Wahupa, USA
Speaker: Professor John Watkins, Consultant Epidemiologist with Public Health Wales, UK
Speaker: Dr. Siddharth Arora, Fellow in Management Science, Said Business School, University of Oxford
Title: Role of Probabilistic Forecasting and Machine Learning in Emergency Healthcare