Percorrer por autor "Saturno-Hernandez, Pedro"
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- Effects of an internal and participatory intervention: improving the radiological imagePublication . Almeida, Rui; Gama, Zenewton; Saturno-Hernandez, Pedro; da Silva, CarlosThe main goal of this research was to assess the effect of an internal and participative intervention aimed through the implementation of best practices and quality improvement applied to general radiology exams. Therefore, a quality improvement cycle was conducted in a radiology department considering a total of 5 criteria and 13 sub-criteria of quality assessment. At baseline, 11 of the criteria/sub-criteria presented quality failures but during the revaluation the improvements were significant in 8 of the criteria/subcriteria. So, the internal quality assessment cycle has been useful and effective as a routine tool for continuous quality improvement of the healthcare process.
- Melhoria da qualidade como ferramenta potenciadora de implementação de boas práticas e de otimização da imagem radiológicaPublication . Almeida, Rui; Gama, Zenewton; Saturno-Hernandez, Pedro; Silva, CarlosO acesso aos serviços de saúde aumentou em todo o mundo, mas a qualidade da assistência prestada ainda é um desafio de saúde global (Scott, Phil & Jha, 2014). Neste campo, é de salientar o trabalho desenvolvido na década de 60 por Avedis Donabedian, na transposição dos modelos da qualidade do sector industrial para um modelo unificado no sector da saúde, o qual teve um contributo considerável para a construção conceptual dos diversos modelos de sistemas da qualidade atualmente existentes (Cabral, Colaço & Guerreiro, 2001; Macedo & Rodrigues, 2009). Entre estes, salientam-se alguns comumente adotados pelas organizações de saúde, que são os modelos da EFQM (European Foundation for Quality Management), ISO (International Organization for Standardization), JCAHO (Joint Commission on Accreditation of Health Care Organisations) e King’s Fund Organisational Audit (Cabral, Colaço & Guerreiro, 2001).
- Multinational attitudes toward AI in Health Care and diagnostics among Hospital patients.Publication . Busch, Felix; Hoffmann, Lena; Xu, Lina; Zhang, Long Jiang; Hu, Bin; García-Juárez, Ignacio; Toapanta-Yanchapaxi, Liz; Gorelik, Natalia; Gorelik, Valérie; Rodriguez-Granillo, Gaston; Ferrarotti, Carlos; Cuong, Nguyen; Thi, Chau; Tuncel, Murat; Kaya, Gürsan; Solis-Barquero, Sergio; Mendez Avila, Maria; Ivanova, Nevena; Kitamura, Felipe; Hayama, Karina; Puntunet Bates, Monserrat; Torres, Pedro Iturralde; Ortiz-Prado, Esteban; Izquierdo-Condoy, Juan; Schwarz, Gilbert; Hofstaetter, Jochen; Hide, Michihiro; Takeda, Konagi; Peric, Barbara; Pilko, Gašper; Thulesius, Hans; Lindow, Thomas; Kolawole, Israel; Olatoke, Samuel Adegboyega; Grzybowski, Andrzej; Corlateanu, Alexandru; Iaconi, Oana-Simina; Li, Ting; Domitrz, Izabela; Kepczynska, Katarzyna; Mihalcin, Matúš; Fašaneková, Lenka; Zatonski, Tomasz; Fulek, Katarzyna; Molnár, András; Maihoub, Stefani; da Silva Gama, Zenewton; Saba, Luca; Sountoulides, Petros; Makowski, Marcus; Aerts, Hugo; Adams, Lisa; Bressem, Keno; Navarro, Álvaro Aceña; Águas, Catarina; Aineseder, Martina; Alomar, Muaed; Al Sliman, Rashid; Anand, Gautam; Angkurawaranon, Salita; Aoki, Shuhei; Arkoh, Samuel; Ashraf, Gizem; Astri, Yesi; Bakhshi, Sameer; Bayramov, Nuru; Billis, Antonis; Bitencourt, Almir; Bolejko, Anetta; Bollas Becerra, Antonio; Bwambale, Joe; Capela, Andreia; Cau, Riccardo; Chacon-Acevedo, Kelly; Chaunzwa, Tafadzwa; Chojniak, Rubens; Clements, Warren; Cuocolo, Renato; Dahlblom, Victor; Sousa, Kelienny de Meneses; Villarrubia, Jorge Esteban; Desai, Vijay; Dhakal, Ajaya; Dignum, Virginia; Andrade, Rubens G. Feijo; Ferraioli, Giovanna; Ganguly, Shuvadeep; Garg, Harshit; Savevska, Cvetanka Gjerakaroska; Radovikj, Marija Gjerakaroska; Gkartzoni, Anastasia; Gorospe, Luis; Griffin, Ian; Hadamitzky, Martin; Ndahiro, Martin Hakorimana; Hering, Alessa; Hochhegger, Bruno; Huseynova, Mehriban; Ishida, Fujimaro; Jha, Nisha; Jiang, Lili; Kader, Rawen; Kavnoudias, Helen; Klein, Clément; Kolostoumpis, George; Koshy, Abraham; Kruger, NicholaS; Löser, Alexander; Lucijanic, Marko; Mantziari, Despoina; Margue, Gaelle; McFadden, Sonyia; Miyake, Masahiro; Morakote, Wipawee; Ngabonziza, Issa; Nguyen, Thao; Niehues, Stefan; Nortje, Marc; Palaian, Subish; Pentara, Natalia; Poma, Gianluigi; Almeida, Rui; Purwoko, Mitayani; Pyrgidis, Nikolaos; Rafailidis, Vasileios; Rainey, Clare; Ribeiro, João; Agudelo, Nicolás Rozo; Sado, Keina; Saidman, Julia; Saturno-Hernandez, Pedro; Suryadevara, Vidyani; Schulz, Gerald; Soric, Ena; Soto-Pérez-Olivares, Javier; Stanzione, Arnaldo; Struck, Julian Peter; Takaoka, Hiroyuki; Tanioka, Satoru; Huyen, Tran; Truhn, Daniel; van Dijk, Elon; van Wijngaarden, Peter; Wang, Yuan-Cheng; Weidlich, Matthias; Zhang, ShuhangThe successful implementation of artificial intelligence (AI) in health care depends on its acceptance by key stakeholders, particularly patients, who are the primary beneficiaries of AI-driven outcomes. OBJECTIVES To survey hospital patients to investigate their trust, concerns, and preferences toward the use of AI in health care and diagnostics and to assess the sociodemographic factors associated with patient attitudes. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study developed and implemented an anonymous quantitative survey between February 1 and November 1, 2023, using a nonprobability sample at 74 hospitals in 43 countries. Participants included hospital patients 18 years of age or older who agreed with voluntary participation in the survey presented in 1 of 26 languages. EXPOSURE Information sheets and paper surveys handed out by hospital staff and posted in conspicuous hospital locations. MAIN OUTCOMES AND MEASURES The primary outcome was participant responses to a 26-item instrument containing a general data section (8 items) and 3 dimensions (trust in AI, AI and diagnosis, preferences and concerns toward AI) with 6 items each. Subgroup analyses used cumulative link mixed and binary mixed-effects models.