Implementing PyautoGUI for Enhanced Heart Team Protocol Creation: Improving Efficiency in Cardiovascular Patient Management.

Roberto Fernandes Branco, Diego Fernandes Branco, Isabel Mattig, Julia Lueg, Gina Barzen, Nanike Bühring, Sven Bischoff, Stefan Hegselmann, Simon Sündermann, Anna Brand, Gerhard Hindricks, Henryk Dreger, Sebastian Spethmann
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Abstract

Introduction: The integration of the "heart team" (HT) concept has become essential in managing complex cardiovascular diseases,. Initially, decisions on CAD treatment were predominantly made by cardiologists or cardiac surgeons. However, the increasing complexity of patient data and the publication of milestone studies underscored the need for an interdisciplinary approach. The HT approach, which first gained traction in Dutch hospitals in the late 1990s, has since been endorsed by European guidelines, highlighting its importance in patient management. Conversely, managing the increasing number of multimorbid patients and the complexity of cardiovascular diagnostics has become challenging.

Methods: We have designed a standardized protocol including all necessary data for risk assessment and social medicine considerations. This protocol, while comprehensive, has become increasingly cumbersome, prompting the need for automation. We have implemented an automated script using PyautoGUI, a Python library for GUI automation, to enhance efficiency. We conducted a timed comparison of data entry efficiency between this automated software program and an experienced human operator. Each participant entered all required data elements, and the total completion times were recorded. Comparative analysis of the two methods was performed using a two-sample Student's t-test, under the assumption of normally distributed means. Statistical analyses were conducted using SPSS software, version 30.0.0.

Results: This script automates data entry from referring departments into our standardized heart team protocol operating via screen coordinates. The automated data entry script demonstrated a statistically significant improvement in data collection efficiency compared to manual entry, with a p-value of 0.049. This suggests that the automated approach may provide meaningful time savings in standardized protocol completion.

Discussion: Our automation means a crucial step in managing the increasing number of multimorbid patients and the complex therapeutic approaches. Although not fully integrated into the KIS, our approach adheres to ethical standards and provides a foundation for future advancements.

Conclusion: This automated script allows physicians to focus on quality control and decision-making, without the burden of manual data entry. Continuous validation and optimization are essential to fully realize the benefits of automation in clinical practice, enhancing patient care and outcomes while maintaining data protection.

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