Evidence map›Paper›PMID 41754016›Full record

ReviewHealthcare (Basel, Switzerland)2026

Postgraduate General Practice Training Under Early Clinical Responsibility: A Narrative Review on System-Based Supervision and the Supportive Role of Artificial Intelligence.

Christian J Wiedermann, Giuliano Piccoliori, Pietro Murali, Cristina Pizzini, Doris Hager von Strobele Prainsack

Abstract readReview
In one paragraph

Review in Healthcare (Basel, Switzerland), 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

5 authors.

Christian J WiedermannInstitute of General Practice and Public Health, Claudiana-College of Health Professions, 39100 Bolzano, Italy.ORCID 0000-0002-4639-8195
Giuliano PiccolioriInstitute of General Practice and Public Health, Claudiana-College of Health Professions, 39100 Bolzano, Italy.ORCID 0000-0003-1974-4184
Pietro MuraliInstitute of General Practice and Public Health, Claudiana-College of Health Professions, 39100 Bolzano, Italy.
Cristina PizziniInstitute of General Practice and Public Health, Claudiana-College of Health Professions, 39100 Bolzano, Italy.
Doris Hager von Strobele PrainsackInstitute of General Practice and Public Health, Claudiana-College of Health Professions, 39100 Bolzano, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesPrimary care faces transformation due to workforce shortages and reform. Italy's Decree 77/2022 promotes Community Centers and extended care, while postgraduate training in general practice involves early clinical responsibility. In South Tyrol, trainees assume significant patient care duties early in a three-year program. This review examines traditional apprenticeship-based training and explores system-based supervision and AI as strategies for improving quality and safety.

methodsA narrative review synthesized the literature and policy on postgraduate general practice education, supervised autonomy, and AI tools in primary care. Searches used the PubMed and Consensus platforms, focusing on Italian primary care reform and South Tyrol. Evidence was analyzed using SANRA guidance.

resultsEvidence consistently indicates that training quality depends less on individual supervisors and more on structured, system-based supervision frameworks, clear entrustment criteria, and supportive organizational contexts. Early supervised clinical autonomy in community-based primary care settings can accelerate competency development without compromising the quality of care when robust supervision and team structures are in place. AI-supported educational tools have the potential to augment feedback, assessment, and learning analytics, especially in settings with limited supervisory capacity; however, current evidence supports their use only as adjuncts to human supervision.

conclusionsEvidence supports system-based, competency-oriented supervision models over traditional apprenticeships in settings characterized by workforce constraints and distributed training sites. Integrated general-practitioner-led primary care settings offer favorable learning environments for postgraduate training, while service-oriented community hubs need careful governance as training sites. Though AI may support supervision, professional oversight remains essential for quality and safety.

Indexed as

artificial intelligenceclinical decision support systemsclinical supervisioncompetency-based educationeducationfamily practicegeneral practicegraduatehealth care reformmedicalpatient safetyprimary health care

Identifiers

PMID41754016
PMCPMC12940306

What Socratic 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 Socratic graph.