Publicación: Information Management for Decision Making: Public Hospitals. Peru Case
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The pandemic caused by Covid -19 teaches us a great lesson that the health sector is not prepared to undergo drastic changes, which leads to a resumption in the conceptualization of the environment. BANI (fragile, anxious, non-linear and incomprehensible) in what describes the reality lived in these times. The general objective of this article is to design a Theoretical Model based on environments (BANI) that favor the experiences of doctors and nurses in decision-making in response to the needs of the patient, based on the electronic medical record, within the framework of the information management. Specific objectives: i) Reveal the experiences in decision-making of doctors and nurses in chaotic contexts; ii) Characterize clinical histories from the experiences of doctors, nurses and patients; iii) Understand and interpret the results of the experiences and processes that doctors and patients went through in BANI contexts, due to Covid-19 when making decisions based on medical records; iv) Determine the axes that support the BANI Model articulated to the management of electronic medical records, within the framework of information management in a hospital in the Lambayeque Region. The design was non-experimental at the basic - interpretive level with a qualitative approach, with a phenomenological - hermeneutic design. The population consisted of health professionals, doctors (3), nurses (3) and patients (2). For the collection of information, the semi-structured interview was used as a technique, and the interview script was also used as an instrument. Interview. It is concluded that the experiences and processes of medical and nursing staff during Covid-19 in a BANI context, occurred in a chaotic environment, making decision-making difficult due to the lack of medical records during emergencies, causing delays in care., which leads medical and nursing staff to act immediately in the face of crises caused by this changing world. © 2023 Elsevier B.V., All rights reserved.


