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Automation of hospital workflows using international standards: A case study with imaging exams
Cristiana Neto1, Francini Hak1, Diana Ferreira1
1Algoritmi/LASI, University of Minho, Gualtar Campus, Braga, 4710-057, Portugal.
Background:
Hospital workflow automation holds paramount importance in modern healthcare systems. By streamlining complex processes, it is possible to enhance operational efficiency and patient care. Automated workflows aligned with open standards, such as openEHR, enable accurate data capture, seamless communication, and timely task execution among healthcare professionals. This leads to reduced errors, improved patient outcomes, and optimized resource utilization.
Objective:
This study aims to advance knowledge in healthcare workflow automation by improving a Portuguese hospital's medical imaging exams circuit through the implementation of clinical standards. Specifically, the study explores how openEHR specifications, particularly the Task Planning component, can be applied to streamline workflows and enhance interoperability.
Methods:
A case study research design was selected to examine the imaging exams circuit in a Portuguese hospital, enabling detailed observation of system implementation and its effects. The focus was on implementing openEHR's Task Planning specification, along with forms and decision rules, to achieve comprehensive workflow automation.
Results:
Following implementation, data from over 6800 imaging exam requests were analyzed, demonstrating health professionals' willingness to adopt the automated tools. A significant reduction in waiting times for outsourcing management was observed, with fewer waiting days on average in 2022 compared to 2019.
Conclusion:
This study shows the development of a new approach to the imaging exams workflow using the openEHR specifications achieving an automated process with structured data generation. The authors believe that the developed system represents an important step towards efficient knowledge discovery from the registry of high-quality and structured data.
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