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使用状态序列分析发现门诊神经病学预约的模式.

Fran Biggin1, Quinta Ashcroft2, Timothy Howcroft2

  • 1Lancaster Medical School, Lancaster University, Bailrigg, Lancaster, LA1 4YG, UK. f.biggin@lancaster.ac.uk.

BMC health services research
|November 5, 2023
PubMed
概括

英国神经科门诊服务面临着很高的需求. 分析预约序列揭示了,运动障碍和头痛的不同模式,为服务改进提供了见解.

关键词:
神经学 神经学门诊预约 门诊预约常规收集的数据是常规收集的数据.国家序列分析分析.

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科学领域:

  • 神经学 神经学
  • 医疗保健服务研究 医疗服务研究
  • 数据科学数据科学数据科学

背景情况:

  • 由于需求超过容量,英国门诊神经病学服务面临重大压力.
  • 了解当前的预约模式对于改善服务至关重要.

研究的目的:

  • 探索门诊神经病学的预约类型模式.
  • 确定优化神经病理门诊服务的机会.

主要方法:

  • 国家序列分析 (SSA) 应用于从单个神经病诊所例行收集的数据.
  • 对新患者预约后18个月的预约序列的分析.
  • 聚类类似的预约序列,以识别跨诊断类别的共同模式.

主要成果:

  • 在1315名患者中,887人只有一次预约,428人多次预约.
  • 在多次访问的患者中观察到6个月一次的预约周期.
  • 国家序列分析确定了11个不同的任命序列集群.
  • 发作/,运动障碍和头痛诊断显著影响了集群分配.

结论:

  • 神经科门诊预约序列表现出相当大的多样性.
  • 特定的诊断类别具有共同的预约顺序模式.
  • 这些已识别的模式可以为未来的神经学门诊服务的设计和结构提供信息.