探索与错过牙科预约相关的因素:对电子牙科记录的机器学习分析
Hussam M Alqahtani1,2,3, Yasmine N Alawaji1,2,3
1Preventive Dental Science, College of Dentistry, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, SAU.
Cureus
|November 29, 2023
概括
机器学习确定了错过牙科预约的关键因素,周一和特定周的没有出现率更高. 了解这些模式可以提高牙医预约的出席率.
科学领域:
- 牙科公共卫生 牙科公共卫生
- 医疗信息学 医疗信息学
- 医疗保健中的机器学习
背景情况:
- 错过牙医预约是医疗保健提供的一个重大挑战.
- 预测和减轻没有预约的情况对于有效的资源配置和患者护理至关重要.
研究的目的:
- 利用机器学习来识别与错过牙科预约相关的因素.
- 分析电子牙科记录,以了解预约遵守的模式.
主要方法:
- 对14066个电子牙科记录进行了横截面分析.
- 机器学习技术的应用,包括条件推理回归树 (CTree) 和随机森林 (RF).
- 牙医预约遵守的分类,分为出席或错过.
主要成果:
- 大约31%的牙医预约都错过了.
- 在学年第一周的星期一,错过预约的比例最高 (高达60%).
- 错过预约的关键预测因素包括预约周,年龄,临床日和牙科教育水平.
结论:
- 特定的安排模式 (周一,某些星期) 和患者人口统计 (年轻患者,女性牙科学生) 与更高的错过预约率有关.
- 识别这些高风险因素可以告知有针对性的干预措施,以改善牙医预约出席率.
- 机器学习模型有效地预测牙科预约的遵守,为医疗保健提供者和机构提供有价值的见解.
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