TY - GEN
T1 - Master Data Architecture for Clinical Process Improvement
AU - Chumpitaz-Huarcaya, Juan Gabriel
AU - Auccahuasi, Wilver
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - The health sector is characterized by the use of a high number of technological systems, from medical devices to information systems, within the information systems we have a number of applications, such as the use of programming languages, database managers, which makes it difficult to make decisions based on the data obtained in the reports obtained from the information systems, which allows to have information in individual reports by systems and is not centralized, which makes its analysis difficult, given this situation, a method is proposed to manage reporting and data analysis processes, based on an SQL statement integration platform and which is then stored in a new database, this procedure allows greater integration of information, concluding that the proposed methodology allows to improve the performance of reports and data analysis by improving information management in clinical environments.
AB - The health sector is characterized by the use of a high number of technological systems, from medical devices to information systems, within the information systems we have a number of applications, such as the use of programming languages, database managers, which makes it difficult to make decisions based on the data obtained in the reports obtained from the information systems, which allows to have information in individual reports by systems and is not centralized, which makes its analysis difficult, given this situation, a method is proposed to manage reporting and data analysis processes, based on an SQL statement integration platform and which is then stored in a new database, this procedure allows greater integration of information, concluding that the proposed methodology allows to improve the performance of reports and data analysis by improving information management in clinical environments.
KW - architecture
KW - Data
KW - programming
KW - report
KW - SQL statement
UR - https://www.scopus.com/pages/publications/105037438733
U2 - 10.1109/ICAUC68182.2026.11441250
DO - 10.1109/ICAUC68182.2026.11441250
M3 - Conference contribution
AN - SCOPUS:105037438733
T3 - Proceedings of the 2026 International Conference on AI-Driven Smart Systems and Ubiquitous Computing, ICAUC 2026
SP - 2102
EP - 2107
BT - Proceedings of the 2026 International Conference on AI-Driven Smart Systems and Ubiquitous Computing, ICAUC 2026
T2 - 2026 International Conference on AI-Driven Smart Systems and Ubiquitous Computing, ICAUC 2026
Y2 - 19 January 2026 through 21 January 2026
ER -