The Impact of Perioperative Data Science in Hospital Knowledge Management

Area of Science:

• Healthcare Informatics
• Data Science
• Knowledge Management

Background:

• Traditional perioperative care relies on manual registries with limited analytical capabilities.
• Technological advancements are driving a shift towards enhanced quality and value in perioperative services.
• Effective knowledge management is crucial for future healthcare service transformation.

Purpose of the Study:

• To investigate the impact of data science and knowledge management on perioperative care.
• To describe the principal results of research conducted at Hospital Dr. Nélio Mendonça (2013-2015).

Main Methods:

• Data science and knowledge management research conducted in a perioperative department.
• Implementation and analysis of a perioperative electronic system (PES).

Main Results:

• Perioperative decision-making was enhanced through the integration of data science tools into the PES.
• Preoperative visit registration by nurses increased from 1.2% to 87.6% post-PES implementation.
• The system enabled assessment of patient features like anxiety and pain levels.

Conclusions:

• Integrating data science into perioperative electronic systems improves decision support and knowledge management.
• The study highlights the potential of data science for enhancing perioperative care quality.
• A conceptual model for data science-grounded perioperative decision support systems is proposed as a key knowledge management tool.