Family Medicine, General Hospital Lagos, Lagos Island, Nigeria
Primary and Community Care, Radboud University Medical Centre, Nijmegen, The Netherlands.
BMJ Open Qual. 2021 Mar;10(1). doi: 10.1136/bmjoq-2020-000938.
Reliable information which can only be derived from accurate data is crucial to the success of the health system. Since encoded data on diagnoses and procedures are put to a broad range of uses, the accuracy of coding is imperative. Accuracy of coding with the International Classification of Diseases, 10th revision (ICD-10) is impeded by a manual coding process that is dependent on the medical records officers' level of experience/knowledge of medical terminologies.
To improve the accuracy of ICD-10 coding of morbidity/mortality data at the general hospitals in Lagos State from 78.7% to ≥95% between March 2018 and September 2018.
A quality improvement (QI) design using the Plan-Do-Study-Act cycle framework. The interventions comprised the introduction of an electronic diagnostic terminology software and training of 52 clinical coders from the 26 general hospitals. An end-of-training coding exercise compared the coding accuracy between the old method and the intervention. The outcome was continuously monitored and evaluated in a phased approach.
Research conducted in the study setting yielded a baseline coding accuracy of 78.7%. The use of the difficult items (wrongly coded items) from the research for the end-of-training coding exercise accounted for a lower coding accuracy when compared with baseline. The difference in coding accuracy between manual coders (47.8%) and browser-assisted coders (54.9%) from the coding exercise was statistically significant. Overall average percentage coding accuracy at the hospitals over the 12-month monitoring and evaluation period was 91.3%.
This QI initiative introduced a stop-gap for improving data coding accuracy in the absence of automated coding and electronic health record. It provides evidence that the electronic diagnostic terminology tool does improve coding accuracy and with continuous use/practice should improve reliability and coding efficiency in resource-constrained settings.
可靠的信息只能来源于准确的数据,这对医疗体系的成功至关重要。由于诊断和操作的编码数据被广泛应用,因此编码的准确性至关重要。国际疾病分类第 10 版(ICD-10)的编码准确性受到依赖于医疗记录官员对医学术语的经验/知识的手动编码过程的阻碍。
提高拉各斯州 26 家综合医院的发病率/死亡率数据 ICD-10 编码的准确性,从 2018 年 3 月至 9 月的 78.7%提高到≥95%。
使用计划-实施-研究-行动(PDSA)周期框架的质量改进(QI)设计。干预措施包括引入电子诊断术语软件和培训来自 26 家综合医院的 52 名临床编码员。培训结束后的编码练习比较了新旧方法的编码准确性。结果通过分阶段的方法进行持续监测和评估。
在研究环境中进行的研究产生了 78.7%的基线编码准确性。与基线相比,使用研究中的困难项目(错误编码项目)进行培训结束后的编码练习导致编码准确性较低。编码练习中手动编码员(47.8%)和浏览器辅助编码员(54.9%)之间的编码准确性差异具有统计学意义。在 12 个月的监测和评估期间,医院的总体平均编码准确性百分比为 91.3%。
这项 QI 倡议在缺乏自动化编码和电子健康记录的情况下,为提高数据编码准确性提供了一种临时解决方案。它提供了证据表明,电子诊断术语工具确实可以提高编码准确性,并且随着持续使用/实践,它应该可以提高资源有限环境中的可靠性和编码效率。