Overall benefit assessment

The three prioritization criteria (benefit, resource use and severity) for the health service in Norway also apply to AI. A cost-benefit analysis can help determine whether an AI system is the right solution and whether investment is justified.

An estimate may include costs associated with:

  • Investments to be able to deploy the AI system
  • Testing and validation
  • Implementation
  • Training
  • Usage (personnel, license and unit price)
  • System management

These costs should be weighed against the expected benefits, such as increased patient safety and improved use of resources. Examples of potential benefits include:

Quality

  • Increased diagnostic accuracy or faster diagnostics: Provides more precise diagnoses and shorter time from examination to treatment.
  • Optimization of treatment: Improved treatment regimen, correct dosing and increased personalized care.
  • Improved treatment outcomes: Faster recovery, fewer side effects, complications, relapses and hospital readmissions compared to current treatment.
  • Better training and communication: More effective training for patients, carers and healthcare professionals.
  • Customized information and decision support for patients and relatives: Empowering patients and relatives to take an active role in their care.
  • Better collaboration: Strengthened collaboration between stakeholders, both internally within the organization, between the municipal and the specialist health service, and across sectors.

Economy

  • Task- or labor-saving: Reducing manual work through automation of tasks.
  • Administrative efficiency: Automation of administrative tasks such as contract management, logistics and resource allocation.
  • Improved documentation: Faster and more accurate clinical documentation, including medical coding.
  • Shorter waiting times: Quicker turnaround in, for example, radiological assessments or patient discharge, freeing up system capacity.

Development

  • Research and innovation: Analyzing large datasets to identify new patterns and drive innovation.
  • Better prognostic tools: Improving the ability to predict treatment outcomes and reduce risk.
  • Technology and process development: Enhancing existing systems and introducing new solutions to strengthen healthcare delivery.

Last update: 23. mai 2025