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An algorithm for estimating the duration of a planned surgical procedure based on a historical database.

机译：一种基于历史数据库估算计划手术过程持续时间的算法。

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摘要

The operating suites of a busy hospital will see over 15,000 surgeries per year. Between 50 and 100 surgeries will be performed per day, involving over 300 staff: physicians, nurses, surgical technicians, and other support personnel. A hospital's surgery schedule for a day is constantly being revised for many reasons: difficult procedures may take longer to complete than expected, emergencies may require reshuffling of rooms and personnel, and ambulatory patients may not arrive when scheduled. While there is an inherent element of unpredictability in estimating in advance a surgery schedule, having and maintaining an accurate schedule is still important for a number of reasons: every change to the schedule requires many people to change their plans, expensive surgical resources can be wasted, and patient satisfaction is adversely effected.; This research makes two contributions: (1) a system for efficiently developing and executing a surgical schedule is described, and (2) an algorithm is described to estimate the surgery time of future surgeries by comparing the surgeon's descriptive coding of the proposed procedures against a historical database of similar procedures and it demonstrates that the implemented algorithm results in estimated surgery times that are statistically more accurate than the surgeons' estimates of the same surgeries.; The resulting algorithm uses a classification-tree approach modified to remove the computational intractability of the “classic” classification tree, and the modified approach provides an explanation of why the resulting surgery duration was chosen. As the size of the database containing the historical surgical information grows, the algorithm is well behaved—the size of the resulting classification tree, the computer time required to generate the tree, and the access time required to find the duration estimate from the tree all grow slightly faster than linearly. The algorithm can accommodate many years of surgical history with modest computer hardware resources. With a cumulative, absolute error rate of 28.3%, the algorithm proved to be more accurate in estimating the duration of 14,250 surgeries than the 33.0% error rate of the surgeons performing the surgery.
机译：繁忙医院的手术室每年将接受超过15,000例手术。每天将进行50到100次手术，涉及300多名员工：医生，护士，外科技术人员和其他支持人员。医院一天的手术时间表由于许多原因而不断修改：困难的程序可能需要比预期更长的时间才能完成，紧急情况可能需要重新安排房间和人员，非卧床患者可能无法按计划到达。虽然预先估计手术时间表具有不可预测性的内在因素，但出于多种原因，拥有并保持准确的时间表仍然很重要：时间表的每次更改都需要许多人更改其计划，但浪费的昂贵手术资源，并且患者满意度受到不利影响。这项研究做出了两个贡献：（1）描述了一种有效制定和执行手术计划的系统，以及（2）描述了一种算法，该算法通过将外科医生对拟议程序的描述性编码与以下方法进行比较来估计未来手术的手术时间类似程序的历史数据库，它证明了所实施的算法产生的手术估计时间在统计学上比外科医生对相同手术的估计更为准确。生成的算法使用经过修改的分类树方法，以消除“经典”分类树的计算难点，并且修改后的方法提供了为何选择最终手术持续时间的解释。随着包含历史外科信息的数据库的大小的增长，算法表现良好-生成的分类树的大小，生成树所需的计算机时间以及从树中找到持续时间估算值所需的访问时间全部比线性增长快一点。该算法可以使用适当的计算机硬件资源来容纳多年的外科手术历史。凭借28.3％的累积绝对错误率，该算法在估计14,250个手术的持续时间方面比执行手术的外科医生的33.0％的错误率更加准确。

著录项

  • 作者

    Lease, Mark Wayne.;

  • 作者单位

    Texas A&M University.;

  • 授予单位 Texas A&M University.;
  • 学科 Health Sciences Health Care Management.; Health Sciences Medicine and Surgery.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 118 p.
  • 总页数 118
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 预防医学、卫生学;
  • 关键词

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