Evidence map›Paper›PMID 35778736›Full record

ArticleBMC health services research2022

Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden.

Lena Petersson, Ingrid Larsson, Jens M Nygren, Per Nilsen, Margit Neher, Julie E Reed, Daniel Tyskbo, Petra Svedberg

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 166 papers, 15 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
166citing papers in PubMed, 15 pooled it
22.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

166 citing papers in PubMed, 15 syntheses or guidelines pooled it, 387 citations in OpenAlex.

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  6. Artificial intelligence in rehabilitation: a living systematic mapping review - first release.European journal of physical and rehabilitation medicine · 2025
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  7. Machine learning for personalized risk assessment of HIV, syphilis, gonorrhoea and chlamydia: A systematic review and meta-analysis.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2025
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  8. AI in Medical Questionnaires: Scoping ReviewJournal of medical Internet research · 2025
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106 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Lena PeterssonSchool of Health and Welfare, Halmstad University, Box 823, 301 18, Halmstad, Sweden. lena.petersson@hh.se.
Ingrid LarssonSchool of Health and Welfare, Halmstad University, Box 823, 301 18, Halmstad, Sweden.
Jens M NygrenSchool of Health and Welfare, Halmstad University, Box 823, 301 18, Halmstad, Sweden.
Per NilsenSchool of Health and Welfare, Halmstad University, Box 823, 301 18, Halmstad, Sweden.
Margit NeherSchool of Health and Welfare, Halmstad University, Box 823, 301 18, Halmstad, Sweden.
Julie E ReedSchool of Health and Welfare, Halmstad University, Box 823, 301 18, Halmstad, Sweden.
Daniel TyskboSchool of Health and Welfare, Halmstad University, Box 823, 301 18, Halmstad, Sweden.
Petra SvedbergSchool of Health and Welfare, Halmstad University, Box 823, 301 18, Halmstad, Sweden.
Halmstad University · SELinköping University · SE

Funding

Carl Bennet AB L2013/77Knowledge Foundation, Sweden grant 20200208 01HVINNOVA grant 2019-04526
6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) for healthcare presents potential solutions to some of the challenges faced by health systems around the world. However, it is well established in implementation and innovation research that novel technologies are often resisted by healthcare leaders, which contributes to their slow and variable uptake. Although research on various stakeholders' perspectives on AI implementation has been undertaken, very few studies have investigated leaders' perspectives on the issue of AI implementation in healthcare. It is essential to understand the perspectives of healthcare leaders, because they have a key role in the implementation process of new technologies in healthcare. The aim of this study was to explore challenges perceived by leaders in a regional Swedish healthcare setting concerning the implementation of AI in healthcare.

methodsThe study takes an explorative qualitative approach. Individual, semi-structured interviews were conducted from October 2020 to May 2021 with 26 healthcare leaders. The analysis was performed using qualitative content analysis, with an inductive approach.

resultsThe analysis yielded three categories, representing three types of challenge perceived to be linked with the implementation of AI in healthcare: 1) Conditions external to the healthcare system; 2) Capacity for strategic change management; 3) Transformation of healthcare professions and healthcare practice.

conclusionsIn conclusion, healthcare leaders highlighted several implementation challenges in relation to AI within and beyond the healthcare system in general and their organisations in particular. The challenges comprised conditions external to the healthcare system, internal capacity for strategic change management, along with transformation of healthcare professions and healthcare practice. The results point to the need to develop implementation strategies across healthcare organisations to address challenges to AI-specific capacity building. Laws and policies are needed to regulate the design and execution of effective AI implementation strategies. There is a need to invest time and resources in implementation processes, with collaboration across healthcare, county councils, and industry partnerships.

Indexed as

Artificial IntelligenceDelivery of Health CareHealth FacilitiesHumansQualitative ResearchSwedenArtificial intelligenceDigital transformationHealthcareHealthcare leadersImplementationOrganizational changeQualitative methodsStakeholders

Identifiers

PMID35778736
PMCPMC9250210
OpenAlexW4283749268

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.