Banca de DEFESA: CLARISSA OLIVEIRA DE CARVALHO

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : CLARISSA OLIVEIRA DE CARVALHO
DATE: 03/12/2020
TIME: 09:00
LOCAL: GoogleMeet
TITLE:

Internal communication in a federal university hospital of the Ebserh: optimizing the process with machine learning.

KEY WORDS:

Communication 4.0, Collective Intelligence, Collaborative Intelligence, Hospital 4.0, Machine Learning.

PAGES: 26
BIG AREA: Ciências da Saúde
AREA: Medicina
SUMMARY:

The current context of digital technological innovation that Industry 4.0 brought, generating a gigantic volume of data, poses new challenges for the internal communication of organizations. Hospitals are naturally complex institutions due to their diversity of activities, professional profiles, types of audiences and regulations to be followed, being an example of an institution with large-scale data management demands. The organizational profile of university hospitals and their role in society, prompted reflection on the importance of the quality of information, the way they are disseminated, as well as the way they are received by the internal public of a university hospital, that is, or, on the effectiveness in the internal communication of this type of institution, considering that it will impact everyone who deals directly or indirectly with patients, influencing the results delivered, whether in academic training or health care.

However, it is observed that the processes refer to internal communication in this type of organization presents some difficulties such as a lack of directed communication and interactivity between the different segments of the internal public. The objective of this work was to verify the needs and deficiencies of the internal public of a large university

hospital in the Ebserh network (Complex Hospital de Clínicas da UFPR) and make a proposal to use intelligence as na artificial instrument to carry out targeted communication, through recommendation of content. The study was based on bibliographic research, quantitative and qualitative research with the qualified sample of the internal public of the Hospital de Clínicas Complex of UFPR (formed by professionals and residents from all areas), as well as proof of concept for recommending content from news available on the CHC-UFPR and Ebserh portals. This work enabled us to verify the importance and difficulties that exist in the internal communication of a large university hospital, while demonstrating that the use of artificial intelligence, such as data management and content recommendation, can be a viable and promising solution for these needs by inserting this type of organization in the age of communication 4.0.

BANKING MEMBERS:
Externo à Instituição - ANDRE HERMAN FREIRE BEZERRA - USP
Interno - 1510735 - DANILO ALVES PINTO NAGEM
Presidente - 1422699 - HERTZ WILTON DE CASTRO LINS
Interna - 2562782 - KARILANY DANTAS COUTINHO
Externo ao Programa - 1668928 - LUIZ GONZAGA DE QUEIROZ SILVEIRA JUNIOR