澳大利亚全科医院的诊断不足:一项数据质量研究,对人口健康报告产生影响
Rachel Canaway1, Christine Chidgey1, Christine Mary Hallinan1
1Department of General Practice & Primary Care, Faculty of Medicine, Dentistry & Health Sciences, Health & Biomedical Research Information Technology Unit (HaBIC R2), The University of Melbourne, Level 4, Medical Building (BN181), Grattan Street, Melbourne, VIC, 3010, Australia.
BMC medical informatics and decision making
|June 5, 2024
概括
仅依靠电子病历 (EMR) 中编码的诊断,就显著低估了慢性疾病的患病率. 纳入自由文本数据对于准确的人口健康规划和患者护理至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 临床流行病学临床流行病学
- 数据质量数据质量
背景情况:
- 电子医疗记录 (EMR) 通常包含自由文本或编码术语的诊断.
- 当前的医疗保健规划和质量改善举措经常排除自由文本数据,只关注编码诊断.
- 这种依赖编码数据可能导致低估疾病患病率.
研究的目的:
- 评估仅使用编码的诊断数据是否导致疾病流行率报告不足.
- 量化六种常见慢性疾病报告不足的程度.
主要方法:
- 一项横截面数据质量研究分析了来自澳大利亚维多利亚州84家全科医院的非识别EMR数据.
- 该研究包括了456,125名患者,他们在2021年1月至2022年12月期间至少进行了三次EMR访问.
- 比较了来自编码诊断的患者数量与针对喘,COPD,痴呆症和糖尿病类型的临床验证的自由文本条目.
主要成果:
- 所有六种慢性疾病在仅使用编码诊断时都显示出不足的数量,从2.57%到36.72%不等.
- 其中五个不足在统计学上是显著的.
- 总体而言,26.4%的患者诊断没有编码,编码在实践水平上有显著的差异,除了2型糖尿病.
结论:
- 仅依靠澳大利亚EMR中的编码条目进行诊断的诊断数据,与包括验证的自由文本数据相比,严重低于报告的流行率.
- 这种报告不足会影响人口健康,医疗保健规划,资源分配和患者护理.
- 利用经过验证的自由文本条目中的表型可以提高诊断准确性和报告可靠性.
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