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Background <p>Prostate cancer, the second most prevalent cancer among men with 1.4&#xa0;million newly diagnosed cases, poses intricate challenges in treatment decision-making due to multifaceted influencing factors. The aim was to assess the efficacy of clinical decision support software (CDSS) in pre-therapeutic prostate cancer management.</p> Methods <p>This study evaluated the CDSS “AI Pathway Companion” by comparing traditional manual methods with software-supported processes in patients diagnosed with localized prostate cancer. The assessment included time analysis, user surveys, and data quality evaluations.</p> Results <p>The CDSS notably reduced case preparation time (-41.5% overall time), including accessing laboratory and imaging results, as well as data integration tasks. Users’ survey indicated heightened satisfaction and improved information quality using the software. Despite limitations in sample size and single-center focus, the study underscored the CDSS’s potential to streamline workflows, enhance data quality, and elevate user experience.</p> Conclusion <p>The study highlights the CDSS’s significant impact on consultation preparation time, decision-making efficiency, and user satisfaction in pre-therapeutic prostate cancer management. While showing promise in this setting, further investigations are needed to gauge its effectiveness in advanced stages and post-therapeutic contexts, aligning with evolving healthcare demands for improved efficiency and patient-centered care.</p>

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Accompanying the prostate cancer patient pathway: evaluation of novel clinical decision support software in patients with early diagnosis of prostate cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月11日

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  • Christian Engesser,
  • Maurice Henkel,
  • Aurelien F. Stalder,
  • Horn Tobias,
  • Pawel Trotsenko,
  • Viktor Alargkof,
  • Philip Cornford,
  • Helge Seifert,
  • Bram Stieltjes,
  • Christian Wetterauer

摘要

Background

Prostate cancer, the second most prevalent cancer among men with 1.4 million newly diagnosed cases, poses intricate challenges in treatment decision-making due to multifaceted influencing factors. The aim was to assess the efficacy of clinical decision support software (CDSS) in pre-therapeutic prostate cancer management.

Methods

This study evaluated the CDSS “AI Pathway Companion” by comparing traditional manual methods with software-supported processes in patients diagnosed with localized prostate cancer. The assessment included time analysis, user surveys, and data quality evaluations.

Results

The CDSS notably reduced case preparation time (-41.5% overall time), including accessing laboratory and imaging results, as well as data integration tasks. Users’ survey indicated heightened satisfaction and improved information quality using the software. Despite limitations in sample size and single-center focus, the study underscored the CDSS’s potential to streamline workflows, enhance data quality, and elevate user experience.

Conclusion

The study highlights the CDSS’s significant impact on consultation preparation time, decision-making efficiency, and user satisfaction in pre-therapeutic prostate cancer management. While showing promise in this setting, further investigations are needed to gauge its effectiveness in advanced stages and post-therapeutic contexts, aligning with evolving healthcare demands for improved efficiency and patient-centered care.