Segurança do paciente: análise das notificações de eventos em um hospital privado

• Autor(a) principal: Melchiades, Ediana Preisler [UNESP]
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/137998
• topic: Segurança; Paciente; Eventos; Notificações; Safety; Patient; Events; Notifications

Patient safety and risk management are key requirements for strengthening the management process in the organization. This study aimed to identify and analyze events reported to the Patient Safety Unit in a private hospital in the state of São Paulo, Brazil. It is a descriptive, exploratory study, retrospective with a quantitative data analysis of the events related to assistance and involving health products, from January to December 2014. Seven hundred and eleven (711) notifications related to patient care and health care products were analyzed . The time analysis of the notifications related to care processes was significantly higher than that of direct patient care. The units that received most event notifications were: Surgical I and II (23.63 %), Adult Intensive Care Unit (17.30%), Pharmacy (11.11%) and Internal Medicine (10.27 %). Most reported event groups were: medication error (14.21%), loss of nutritional probe (13,22 %) and skin lesions (11.95 %). The positions that most reported events of the direct assistance group to the patient and care process were: nursing care coordinator and nurse. It can be concluded that the notification of events related to patient care and involving health products is fundamentally important within the institution and contributes to the adoption of incident prevention strategies and improvement of the quality of the provided care. From the research, we developed two products to be adopted in the institution involved : a) Patient Safety Plan , in accordance with the requirements of the official directives (DRC number 36 of July 25, 2013) b ) Risk Management Matrix per unit based on the Healthcare Failure Mode and Effect Analysis (HFMEA) methodology.