The Wellbeing Services County of North Ostrobothnia (Pohde) has strong reporting capabilities thanks to its data pool solution, giving a solid view of past activities and performance. However, understanding the past wasn’t enough. All wellbeing services counties have a constant need to be able to predict and report on future needs reliably and efficiently. In the pilot, Solita, Istekki, and Pohde jointly developed a service demand forecasting model and scenario tool for traumatology and orthopaedics that can be used to assess future demand for treatment and its impact on waiting times and queue lengths.
The new model:
- Forecasts and calculates future needs for the most needed categories of care by using historical data
- Helps decision-makers to estimate the amount and type of measures needed to meet demand
- Supports knowledge management experts in determining how services and resources should be allocated in future
- Has been piloted in traumatology and orthopaedics, but can be expanded to other medical fields also
Pohde is one of the largest Wellbeing Services Counties in Finland. They are responsible for the welfare, health, and safety of approximately 416,000 residents in Northern Ostrobothnia, and they employ nearly 18,000 professionals. Pohde is developing more diverse services for social and health centers, focusing on new technologies and digital services.
Pohde wanted to reliably and efficiently predict the demand for treatment, and to understand how changes in referral volumes would affect waiting times and the number of people waiting.
Effective model helps predict the future
Pohde has high-quality reporting and data available, but it hasn’t been utilised to envision the future.
Building on top of high-quality data, prediction models utilising AI and machine learning can predict patient flows years in advance. On top of the models, Solita built a scenario tool for the health care experts and decision-makers at Pohde to test the impact of possible measures on the waiting list situation. In practice, the tool helps to calculate how many more surgeries need to be performed, and whether the number of operating theatres needs to be increased, in order to keep the waiting list moderate and waiting times within the treatment guarantee. This information can be used to:
- Knowledge-based decision-making
- Service planning and
- Resource management
“With customers’ permission, Solita uses different kinds of GenAI tools to help us be more productive. For example, we always consider if we should use CollabAI workshops to speed up the planning phase.”
The service demand forecasting model and scenario tool
With this tool, users, decision-makers, or knowledge management experts can test how many procedures are needed to meet demand and how quickly the queue situation responds to changes in capacity. Forecasts can be viewed at the level of the entire specialty or individual procedure category.
