{"id":3862,"date":"2025-01-01T00:00:00","date_gmt":"2025-01-01T00:00:00","guid":{"rendered":"https:\/\/hdl.handle.net\/20.500.12008\/51531"},"modified":"2025-01-01T00:00:00","modified_gmt":"2025-01-01T00:00:00","slug":"inteligencia-artificial-en-la-gestion-de-caidas-impactos-operativos-emocionales-eticos-y-organizacionales-en-enfermeria","status":"publish","type":"post","link":"https:\/\/hlrnet.net\/sites\/actu-es\/2025\/01\/01\/inteligencia-artificial-en-la-gestion-de-caidas-impactos-operativos-emocionales-eticos-y-organizacionales-en-enfermeria\/","title":{"rendered":"Inteligencia Artificial en la gesti\u00f3n de ca\u00eddas: impactos operativos, emocionales, \u00e9ticos y organizacionales en enfermer\u00eda"},"content":{"rendered":"\n\n
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T\u00edtulo: Inteligencia Artificial en la gesti\u00f3n de ca\u00eddas: impactos operativos, emocionales, \u00e9ticos y organizacionales en enfermer\u00eda
\nAutor: Ramos-Zaga, Fernando
\nResumen: Introducci\u00f3n: La sobrecarga estructural en los sistemas sanitarios contempor\u00e1neos ha deteriorado la salud del personal de enfermer\u00eda, generando un entorno laboral caracterizado por estr\u00e9s cr\u00f3nico, agotamiento y reducci\u00f3n en la calidad asistencial. Esta situaci\u00f3n exige soluciones tecnol\u00f3gicas que alivien la presi\u00f3n sobre el personal sin comprometer la atenci\u00f3n al paciente. Objetivo: Identificar los efectos operativos, emocionales, \u00e9ticos y organizativos de los sistemas basados en inteligencia artificial en la reducci\u00f3n de factores estresantes asociados a la gesti\u00f3n de ca\u00eddas de pacientes en contextos de enfermer\u00eda. M\u00e9todo: Se realiz\u00f3 una revisi\u00f3n sistem\u00e1tica conforme a los lineamientos PRISMA 2020, consultando las bases de datos Scopus, PubMed y IEEE Xplore. Se seleccionaron 23 estudios emp\u00edricos publicados entre 2019 y 2023, que abordan la aplicaci\u00f3n de inteligencia artificial en la prevenci\u00f3n de ca\u00eddas y el manejo del estr\u00e9s en entornos cl\u00ednicos de enfermer\u00eda. Resultado: Los sistemas basados en inteligencia artificial mejoraron la eficiencia operativa mediante detecci\u00f3n temprana, alertas automatizadas y documentaci\u00f3n precisa de eventos. A nivel emocional, se observ\u00f3 una reducci\u00f3n en el estr\u00e9s agudo y cr\u00f3nico del personal. En el plano \u00e9tico, se identificaron tensiones entre la vigilancia tecnol\u00f3gica y la autonom\u00eda del paciente mientras que, a nivel organizativo, la inteligencia artificial facilit\u00f3 la integraci\u00f3n funcional de equipos y optimizaci\u00f3n de flujos de trabajo. No obstante, la resistencia del personal y la ausencia de marcos regulatorios claros constituyen obst\u00e1culos significativos para su implementaci\u00f3n sostenida. Conclusi\u00f3n: La incorporaci\u00f3n de la inteligencia artificial en el cuidado enfermero frente a ca\u00eddas representa una transformaci\u00f3n paradigm\u00e1tica del acto cl\u00ednico. Su impacto va m\u00e1s all\u00e1 de la eficiencia t\u00e9cnica, implicando una reorganizaci\u00f3n \u00e9tica, emocional y estructural del entorno asistencial. Para garantizar su legitimidad y sostenibilidad, se requiere un enfoque integrador que combine avances tecnol\u00f3gicos con pol\u00edticas institucionales claras y compromiso con la dignidad humana.; Introduction: Structural over load in contemporary health care systems has compromised the well-being of nursing staff, leading to chronic stress, burnout, and a decline in care quality. This scenario demands technological solutions that relieve pressure on personnel without compromising patient care. Objective: This study aims to identify the operational, emotional, ethical, and organizational effects of artificial intelligence systems in reducing stress-related factors associated with fall management in nursing contexts. Methods: A systematic review was conducted in accordance with PRISMA 2020 guidelines. Searches were performed in Scopus, PubMed, and IEEE Xplore. A total of 23 empirical studies published between 2019 and 2023 were selected, focusing on the application of artificial intelligence to fall prevention and stress management in clinical nursing environments. Results: AI-based systems enhanced operational efficiency through early detection, automated alerts, and accurate event documentation. Emotionally, a reduction in both acute and chronic stress among nursing personnel was observed. Ethically, tensions emerged between technological surveillance and patient autonomy. Organizationally, artificial intelligence facilitated functional team integration and stream lined work flows. However, staff resistance and the absence of clear regulatory frameworks remain major barriers to sustained implementation. Conclusion: The integration of artificial intelligence in nursing care for fall prevention signifies a paradigmatic shift in clinical practice. Its impact extends beyond technical efficiency, requiring an ethical, emotional, and structural reorganization of the care environment. Ensuring the legitimacy and sustainability of these innovations necessitates an integrative approach that combines technological advancement with institutional policies and a firm commitment to human dignity.; Introdu\u00e7\u00e3o: A sobrecarga estrutural dos sistemas de sa\u00fade contempor\u00e2neos tem vindo a deteriorar a sa\u00fade dos profissionais de enfermagem, gerando ambientes laborais marcados por estresse cr\u00f4nico, exaust\u00e3o e diminui\u00e7\u00e3o da qualidade dos cuidados prestados. Esta conjuntura exige solu\u00e7\u00f5es tecnol\u00f3gicas que aliviem a press\u00e3o sobre os profissionais sem comprometer a aten\u00e7\u00e3o ao utente. Objetivo: Este estudo tem como finalidade identificar os efeitos operacionais, emocionais, \u00e9ticos e organizacionais dos sistemas baseados em intelig\u00eancia artificial na redu\u00e7\u00e3o de fatores de estresse associados \u00e0 gest\u00e3o de quedas de utentes em contextos de enfermagem. M\u00e9todo: Foi realizada uma revis\u00e3o sistem\u00e1tica segundo as diretrizes PRISMA 2020, com pesquisa nas bases de dados Scopus, PubMed e IEEE Xplore. Selecionaram-se 23 estudos emp\u00edricos publicados entre 2019 e 2023 que abordam a aplica\u00e7\u00e3o de intelig\u00eancia artificial na preven\u00e7\u00e3o de quedas e no controlo do estresse em contextos cl\u00ednicos de enfermagem. Resultados: Os sistemas baseados em intelig\u00eancia artificial melhoraram a efici\u00eancia operacional atrav\u00e9s da detec\u00e7\u00e3o precoce de eventos, alerta automatizados e documenta\u00e7\u00e3o precisa. Ao n\u00edvel emocional, observou-se uma redu\u00e7\u00e3o do estresse agudo e cr\u00f4nico entre os profissionais. No plano \u00e9tico, identificaram-se tens\u00f5es entre a vigil\u00e2ncia tecnol\u00f3gica e a autonomia dos utentes. Organizacionalmente, a intelig\u00eancia artificial facilitou a integra\u00e7\u00e3o funcional das equipas e a optimiza\u00e7\u00e3o dos fluxos de trabalho. Contudo, a resist\u00eancia dos profissionais e a aus\u00eancia de regulamenta\u00e7\u00e3o clara constituem obst\u00e1culos \u00e0 sua implementa\u00e7\u00e3o sustentada. Conclus\u00f5es: A incorpora\u00e7\u00e3o da intelig\u00eancia artificial nos cuidados de enfermagem associados a quedas representa uma transforma\u00e7\u00e3o paradigm\u00e1tica do ato cl\u00ednico. O seu impacto ultrapassa a dimens\u00e3o t\u00e9cnica, implicando uma reorganiza\u00e7\u00e3o \u00e9tica, emocional e estrutural do contexto assistencial. A sua legitima\u00e7\u00e3o e sustentabilidade requerem um enfoque integrador, alicer\u00e7ado em pol\u00edticas institucionais claras e no compromisso com a dignidade humana.
\nDescripci\u00f3n: rue.fenf.edu.uy\/index.php\/rue<\/a> Fuente<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

T\u00edtulo: Inteligencia Artificial en la gesti\u00f3n de ca\u00eddas: impactos operativos, emocionales, \u00e9ticos y organizacionales en enfermer\u00eda Autor: Ramos-Zaga, Fernando Resumen: Introducci\u00f3n: La sobrecarga estructural en los sistemas sanitarios contempor\u00e1neos ha deteriorado la salud del personal de enfermer\u00eda, generando un entorno laboral caracterizado por estr\u00e9s cr\u00f3nico, agotamiento y reducci\u00f3n en la<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"class_list":["post-3862","post","type-post","status-publish","format-standard","hentry","category-america-latina"],"publishpress_future_action":{"enabled":false,"date":"2026-07-02 09:18:39","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/hlrnet.net\/sites\/actu-es\/wp-json\/wp\/v2\/posts\/3862","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hlrnet.net\/sites\/actu-es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hlrnet.net\/sites\/actu-es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hlrnet.net\/sites\/actu-es\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/hlrnet.net\/sites\/actu-es\/wp-json\/wp\/v2\/comments?post=3862"}],"version-history":[{"count":0,"href":"https:\/\/hlrnet.net\/sites\/actu-es\/wp-json\/wp\/v2\/posts\/3862\/revisions"}],"wp:attachment":[{"href":"https:\/\/hlrnet.net\/sites\/actu-es\/wp-json\/wp\/v2\/media?parent=3862"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hlrnet.net\/sites\/actu-es\/wp-json\/wp\/v2\/categories?post=3862"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hlrnet.net\/sites\/actu-es\/wp-json\/wp\/v2\/tags?post=3862"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}