Evidence map›Paper›PMID 39063923›Full record

ArticleJournal of personalized medicine2024

Precision Workforce Management for Radiographers: Monitoring and Managing Competences with an Automatic Tool.

Andrea Lastrucci, Yannick Wandael, Giovanni Orlandi, Angelo Barra, Stefano Chiti, Valentina Gigli, Massimo Marletta, Davide Pelliccia, Barbara Tonietti, Renzo Ricci and 1 more

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

11 authors.

Andrea LastrucciDepartment of Allied Health Professions, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy.ORCID 0000-0002-3600-9213
Yannick WandaelDepartment of Allied Health Professions, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy.
Giovanni OrlandiDepartment of Allied Health Professions, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy.
Angelo BarraDepartment of Allied Health Professions, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy.ORCID 0009-0007-6798-4576
Stefano ChitiDepartment of Allied Health Professions, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy.
Valentina GigliStaff della Direzione Aziendale, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy.
Massimo MarlettaDepartment of Allied Health Professions, Azienda Ospedaliero-Universitaria Pisana, 56124 Pisa, Italy.
Davide PellicciaDepartment of Allied Health Professions, Azienda Ospedaliero-Universitaria Pisana, 56124 Pisa, Italy.
Barbara ToniettiStaff della Direzione Aziendale, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy.
Renzo RicciDepartment of Allied Health Professions, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy.
Daniele GiansantiCentre TISP, Istituto Superiore di Sanità, 00161 Roma, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optimizing work shifts in healthcare is crucial for maintaining high standards of service delivery and fostering professional development. This study delves into the emerging field of skill-oriented work shift optimization, focusing specifically on radiographers within the healthcare sector. Through the development of Skills Retention Monitoring (SRH), this research aims to enhance skill monitoring, workload management, and organizational performance. In this study, several key highlights emerged: (a) Introduction of the SRH tool: The SRH tool represents a resource-efficient solution that harnesses existing software infrastructure. A preliminary version, focusing on the radiographers' professional profile, was released, and after several months of use, it demonstrated effectiveness in optimizing work based on competency monitoring. (b) The SRH tool has thus demonstrated the capacity to generate actionable insights in the organizational context of radiographers. By generating weekly reports, the SRH tool streamlines activity management and optimizes resource allocation within healthcare settings. (c) Application of a Computer-Assisted Web Interviewing (CAWI) tool for pre-release feedback during a training event. (d) Strategic importance of a maintenance and monitoring plan: This plan, rooted in a continuous quality improvement approach and key performance indicators, ensures the sustained effectiveness of the SRH tool. (e) Strategic importance of a transfer plan: Involving professional associations and employing targeted questionnaires, this plan ensures the customization of the tool from the perspective of each profession involved. This is a crucial point, as it will enable the release of tool versions tailored to various professions operating within the hospital sector. As a side result, the tool could allow for a more tailored and personalized medicine both by connecting the insights gathered through the SRH tool with the right competencies for healthcare professionals and with individual patient data. This integration could lead to better-informed decision making, optimizing treatment strategies based on both patient needs and the specific expertise of the healthcare provider. Future directions include deploying the SRH tool within the Pisa hospital network and exploring integration with AI algorithms for further optimization. Overall, this research contributes to advancing work shift optimization strategies and promoting excellence in healthcare service delivery.

Indexed as

competencemonitoringperformanceradiographerskillworkload

Identifiers

PMID39063923
PMCPMC11278459

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.