Contact person
Clara Larsson
Analytiker
Contact ClaraHealth economic modelling of malnutrition among elderly
Sweden’s aging population entails a growing responsibility for society, especially for the public sector, which plays a significant role in the care and support of older individuals. It is increasingly important to use societal resources effectively to address social and health-related challenges that often accompany advanced age. Malnutrition is an example of such a challenge, and RISE has developed a health-economic model to support the development and prioritization of interventions.
Malnutrition is defined as an imbalance in nutrient intake, leading to illness or deterioration of body composition, functionality, or disease progression. Untreated or undetected malnutrition can have serious consequences, resulting in personal suffering and increased burden on healthcare. Older individuals suffering from malnutrition seek medical care more frequently, experience longer hospital stays, and face a higher risk of complications and mortality compared to well-nourished seniors.
There is insufficient data on the total costs of malnutrition in the Swedish context. To contribute to knowledge in this area, RISE has developed a so-called Markov model to enable health-economic calculations of the costs associated with malnutrition and the potential savings that can be achieved through various preventive interventions. The model was developed within the context of the Food Academy’s work on a Zero Vision for malnutrition in older adults.
Costs of Malnutrition: The model can calculate the costs associated with malnutrition based on a specified target group over a specific time period.
Costs and Potential Savings: It can also estimate the costs and potential savings related to any chosen intervention.
Scenario Analysis: The model allows exploration of different scenarios. For example, it can assess how costs or savings change if we increase or decrease the cost of the intervention
Utilizing the Results
- Demonstrate how various factors impact malnutrition among older adults and the associated costs
- Illustrate how interventions can influence malnutrition and healthcare costs.
- Optimize resource allocation to maximize societal benefits
The model primarily targets statisticians, economists, and analysts familiar with the RStudio program, as it is built within that framework. For a more detailed description of the model, including the technical report and script, you can find them available for download on the Open Science Framework through this link.
RISE offers support to municipalities for adapting and using the model
To facilitate the use of the model for those who are not familiar with RStudio or need assistance with model adaptation, RISE offers support in customizing the model to local or specific conditions. The support includes guidance on local data collection, calculations using the model based on local needs, preferences, and conditions, as well as a summary of conclusions.
Questions to consider before ordering a cost estimate related to malnutrition
How do you intend to use the health-economic calculation regarding malnutrition? What aspects would you like us to examine together?
- For example, how can a municipal dietitian contribute to cost savings?
If you have a specific intervention in mind, do you have an idea of how much it could impact malnutrition rates and its consequences?
- For example, referrals to healthcare centers (related to malnutrition) decreased by 10% after a year.
Do you know the annual cost of the proposed intervention? How many older individuals would be reached by it?
What is the target group in your municipality? Which age group would you primarily focus on?
- For example, all individuals between 65 and 80 years old.
How many people are in the target group?
- For instance, how many individuals aged 65-80 years are there in your municipality?
What time frame do you believe is relevant for the analysis? Over how many years should the cost savings be calculated?
- As an example, consider a 15-year period to assess the savings a municipal dietitian could provide for a group of older adults, such as those aged 65 to 80.
How do you wish the results of the analysis to be delivered? Who should receive the results? In what way is it easiest to present the results so that they are easily understandable?
