THIS ARTICLE/PRESS RELEASE IS PAID FOR AND PRESENTED BY the Norwegian centre for E-health research - read more

The Norwegian Centre for E-health Research has carried out a comprehensive study on the implementation of artificial intelligence in the health service in Norway.

Will there be more use of artificial intelligence in the Norwegian healthcare system?

Researchers have investigated what is needed to introduce artificial intelligence in the Norwegian healthcare system. They recommend that there be more of it.

Published

Artificial intelligence, abbreviated AI, can have great potential as something useful for patients, healthcare personnel and the Norwegian society in general.

Researchers at the Norwegian Centre for E-health Research know that only a few of the many existing projects with artificial intelligence are adapted to the healthcare system.

So, what is preventing AI from finding its way from research to the clinic?

This was one of the questions the researchers asked themselves in a comprehensive study on the implementation of artificial intelligence in the health service. The study is now the basis for a report that contains the researchers' recommendations.

"The aim of the report has been to examine these obstacles and identify the actions that must be taken to facilitate the transition of AI from research to clinical practice," project manager and senior researcher Maryam Tayefi at the Norwegian Centre for E-health Research says.

Maryam Tayefi is a researcher at the Norwegian Centre for E-health Research.

AI can also make mistakes

There is an ongoing debate about the ethical, clinical and financial advantages and disadvantages of using artificial intelligence and algorithms to treat patients.

Artificial intelligence can potentially provide new insights and simplify healthcare institutions' and patients' handling of health information. However, it can also involve a significant risk in terms of privacy, ethics and medical errors.

Balancing the risks and benefits of AI in the health service will require a joint effort from technology developers, decision makers, health institutions and patients.

Sustainable introduction of AI

The report provides a comprehensive description of the phases in the introduction of AI, from planning to implementation. The report also contains proposals and recommendations for the authorities.

The knowledge is based on interviews, summaries of existing research, strategies and reports.

Maryam Tayefi has been working on the report since 2021. She clearly believes that artificial intelligence can improve the efficiency of the health service and the quality of medical treatment.

Project manager and researcher Maryam Tayefi launched the report together with Centre Director Stein Olav Skrøvseth at the Norwegian Centre for E-health Research in November 2022.

Recommendations to Norwegian health authorities

The researchers believe that Norway has many preconditions for successful introduction of AI in the health sector. We have several large health data registers with data collected over many decades, a large number of available IT specialists, expertise research groups in the area, and acceptance of new technology in general.

Nevertheless, more actions are needed at national level and in health organisations to achieve widespread use in the healthcare system.

The recommendations for AI adoption to authorities and health organisations are as follows:

  1. Increase knowledge about AI among healthcare personnel and citizens.
  2. Focus on clinical needs and patient perspectives in the implementation process.
  3. Collaboration across disciplines and sectors is important for coordinated initiatives.
  4. Regulations must be adapted to the new technology.
  5. Improve opportunities for funding and ensure distribution of medical and computer science resources for AI implementation
  6. Improve data challenges such as quality, access, storage and exchange.
  7. Upgrade current ICT infrastructure.
  8. Standardise implementation and procedures for procurement.
  9. Ensure clinical approval before implementation of AI systems in the health service. And ensure maintenance for systems being introduced.
"Artificial intelligence must be used for better and more efficient patient treatment," says Lars Bjørgan Schrøder.

Collaboration and a good digital infrastructure

The patients and health personnel must play as a team to get artificial intelligence into place in the Norwegian health service.

The report shows that it is just as important to have close collaboration between different disciplines, technologists and clinicians. And it is essential to have a digital infrastructure that facilitates technological development in the health services.

"The health service is already using artificial intelligence, so it is more a question of what to use it for and how much to use it. Artificial intelligence is not a goal in itself either. It will be used for better and more efficient patient treatment,"Lars Bjørgan Schrøder says.

He is the director general at the Ministry of Health and Care Services.

During the launch of the report, he said that history shows that what you think is going to happen, never turns out quite as expected. Innovations often take longer to implement than expected.

The Norwegian Ministry of Health and Care Services has therefore established Helsedataservice (link in Norwegian) as part of the Directorate for e-health. Helsedataservice will make it much easier and faster for researchers to access health data from several registers.

Reference:

Makhlysheva et al. Implementation of artificial intelligence in Norwegian healthcare: The road to broad adoption, Norwegian Centre for E-health Research, Report number 01-2022.

What is artificial intelligence - AI?

In this report, the researchers associate AI with machine learning algorithms that use data-driven methods. Here they use the term "artificial intelligence" to describe computer programs that can process large amounts of data using statistical computing and machine learning techniques, find patterns, interpret them and make predictions for new data entering the system.

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