[私人医疗保险中的保险人特定门诊索赔数据 - 第2部分:数据来源和数据流]
Christoph Stallmann1, Katharina Achstetter2, Ludwig Goldhahn1
1Institut für Sozialmedizin und Gesundheitssystemforschung, Otto-von-Guericke-Universität Magdeburg Medizinische Fakultät, Magdeburg, Germany.
概括
了解私人医疗保险 (PHI) 索赔数据对于研究至关重要. 这项研究详细介绍了门诊护理中的数据创建和流动,帮助研究人员有效地利用PHI数据.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
背景情况:
- 使用私人医疗保险 (PHI) 公司索赔数据的科学研究需要了解监管流程,数据提交,计费和存储.
- 之前的研究表明,PHI索赔数据可以与法定医疗保险公司数据相似地使用,只要了解其特定特征.
研究的目的:
- 提供对私人医疗保险系统内,包括药物在内的门诊医疗护理的保险人和计费数据的创建和流动的基本理解.
- 用一个示例数据流模型来说明私人医疗保险系统的流程和独特特征.
- 通过突出管理和内容相关的挑战,协助决策者和数据分析师规划研究,准备/评估PHI索赔数据.
主要方法:
- 系统说明私人医疗保险系统中的流程和特殊特征,使用门诊护理和药物治疗的示例数据流模型.
- 分析数据生成的特殊性及其与内容相关的后果.
主要成果:
- 该研究详细概述了私人医疗保险部门对门诊服务的保险人数据流和相关计费情况.
- 它强调了了解私人医疗保险索赔数据中独特的特定流程和数据特征的重要性.
- 由于不同的IT基础设施和保险费率,必须针对每个PHI公司单独进行数据可用性和质量评估.
结论:
- 对数据流和相关挑战的彻底理解对于处理私人医疗保险索赔数据的数据分析师至关重要.
- 未来的研究应该专注于链接方法和整合初级/调查数据用于验证研究,以增强经验知识基础.
- 数字化趋势,如电子发票和处方,有可能改善与健康有关的索赔数据的内容和可用性.
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