Evidence map›Paper›PMID 41887627›Full record

ArticleBMJ open2026

How does the implementation of AI-based automation of administrative tasks affect healthcare professionals' work? Study protocol for a longitudinal embedded case study in Swedish primary and specialist care.

Luís Irgang, Petra Svedberg, Jens Nygren, Lena Petersson

Abstract read
In one paragraph

Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Luís IrgangSchool of Health and Welfare, Halmstad University, Halmstad, Sweden luis.irgang@hh.se.ORCID http://orcid.org/0000-0001-9033-3957
Petra SvedbergSchool of Health and Welfare, Halmstad University, Halmstad, Sweden.
Jens NygrenSchool of Health and Welfare, Halmstad University, Halmstad, Sweden.ORCID http://orcid.org/0000-0002-3576-2393
Lena PeterssonSchool of Health and Welfare, Halmstad University, Halmstad, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionArtificial intelligence (AI) is transforming healthcare through enhanced computational capabilities that process vast amounts of data with unprecedented speed and precision. AI-powered administrative systems hold significant promise for reducing the substantial documentation burden on healthcare professionals, potentially improving operational efficiency and job satisfaction. However, critical knowledge gaps exist regarding how AI implementation affects professional boundaries, work identities and the healthcare work environment. This study protocol describes the Project EFAAI (Efficient and Flexible Working Life in Healthcare with the Support of Digital Tools and AI), which aims to explore how the implementation of AI-based automation of administrative tasks affects healthcare professionals' work. METHODS AND ANALYSIS: This research employs a single-embedded case study with a longitudinal approach, following the implementation of an AI-powered healthcare administration system across 12 primary care facilities and 20 specialist care facilities of a major private healthcare provider in Sweden. Data collection spans 18 months through three sequential waves at 6-month intervals. The project consists of three work packages (WP): WP1 explores changes in professional boundaries and AI literacy requirements using exploratory meetings with healthcare leaders and in-depth semistructured interviews with 20 physicians from primary care and 20 from specialist care (n=40); WP2 investigates implementation barriers and facilitators through in-depth semistructured interviews with the same 40 physicians as WP1 for longitudinal follow-up; and WP3 examines the impact on efficient and flexible work conditions using a mixed-methods approach integrating quantitative operational and administrative data from the healthcare provider's information systems and administrative databases (eg, documentation completion times, consultation duration, workload distribution metrics, operational efficiency ratios) with qualitative data from four focus groups and workshops with physicians, nurses, healthcare leaders and administrative staff. ETHICS AND DISSEMINATION: The study adheres to the ethical guidelines of the Swedish Research Council and complies with the regulations of the Swedish Ethical Review Authority. Data will be collected with informed consent from all participants, anonymised and stored in accordance with General Data Protection Regulation (GDPR) requirements. Results will be disseminated through international publications, conferences, teaching activities and stakeholder engagement.

Indexed as

Artificial IntelligenceAutomationHealth PersonnelPrimary Health CareHumansJob SatisfactionLongitudinal StudiesSwedenAdministrationArtificial IntelligenceDigital TechnologyHealth WorkforceImplementation SciencePrimary Care

Identifiers

PMID41887627
PMCPMC13034228

What OpenQuestion holds

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LicenceCC BY
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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.