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1.
Radiol Artif Intell ; 5(6): e230038, 2023 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-38074792

RESUMO

Poor positioning decreases mammography sensitivity and is arguably the single most important contributor to image quality (IQ). Inadequate IQ may subject patients to technical repeat views during the examination or return for technical recalls. Artificial intelligence (AI) software can objectively evaluate breast positioning and compression metrics for all images and technologists. This study assessed whether implementation of AI software across the authors' institution improved IQ and reduced rates of technical repeats and recalls (TR). From April 2019 to March 2022, TR was retrospectively evaluated for 40 technologists (198 054 images; Centricity electronic medical record system, GE HealthCare), and AI IQ metrics were available for 42 technologists (211 821 images; Analytics, Volpara Health Technologies). Diagnostic and digital breast tomosynthesis images and implant cases were excluded. Kolmogorov-Smirnov, χ2, and paired t tests were used to evaluate whether AI IQ metrics and TR rates improved between the initial and most recent 12-month periods following AI software implementation (ie, baseline [April 2019 to March 2020] vs current [April 2021 to March 2022]). Comparing baseline with current periods, TR significantly reduced from 0.77% (788 of 102 953 images) to 0.17% (160 of 95 101 images), respectively (P < .001), and overall mean quality score improved by 6% ([2.42 - 2.28]/2.28; P = .001), demonstrating the potential of AI software to improve IQ and reduce patient TR. Keywords: Mammography, Breast, Oncology, QA/QC, Screening, Technology Assessment © RSNA, 2023.

2.
J Am Coll Radiol ; 16(6): 869-877, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30559039

RESUMO

The 2018 radiology Intersociety Committee reviewed the current state of stress and burnout in our workplaces and identified approaches for fostering engagement, wellness, and job satisfaction. In addition to emphasizing the importance of personal wellness (the fourth aim of health care), the major focus of the meeting was to identify strategies and themes to mitigate the frequency, manifestations, and impact of stress. Strategies include reducing the stigma of burnout, minimizing isolation through community building and fostering connectivity, utilizing data and benchmarking to guide effectiveness of improvement efforts, resourcing and training "wellness" committees, acknowledging value contributions of team members, and improving efficiency in the workplace. Four themes were identified to prioritize organizational efforts: (1) collecting, analyzing, and benchmarking data; (2) developing effective leadership; (3) building high-functioning teams; and (4) amplifying our voice to increase our influence.


Assuntos
Esgotamento Profissional/prevenção & controle , Promoção da Saúde/organização & administração , Satisfação no Emprego , Estresse Ocupacional/prevenção & controle , Radiologistas/psicologia , Esgotamento Profissional/psicologia , Consenso , Feminino , Humanos , Masculino , Avaliação das Necessidades , Qualidade de Vida , Medição de Risco , Sociedades Médicas , Estados Unidos , Local de Trabalho/psicologia
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