改善神经外科质量指标:脊柱外科3年病例回顾。

Neurosurgery practice Pub Date : 2024-01-30 eCollection Date: 2024-03-01 DOI:10.1227/neuprac.0000000000000071
Christina Nicoll Feller, Erin M Bodenbach, Julie M Kolinski, Grant P Sinson
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引用次数: 0

摘要

背景和目的:尽管准确的临床文献对高质量的患者护理很重要,但在实践中往往不优先考虑这一点,并导致各种下游后果。不准确的文档会导致错过完整、准确编码的机会。反过来,它也会对医院和医生质量排名、医疗中心概况和收入产生负面影响。本研究的目的是强调临床文献持续改进的机会,以及准确的临床文献对结果测量的重要性,如预期住院时间(eLOS)。方法:对2019年至2021年接受脊柱手术的患者进行单中心回顾性图表回顾。基于Vizient的eLOS诊断相关群体风险模型,我们审查了192个图表,涵盖10个独特的诊断相关群体,以确定ICD-10的诊断和程序代码没有编码或没有被医生清楚地记录。通过添加新识别的变量重新计算每个患者的新eLOS,然后与原始eLOS进行比较。结果:总的来说,当添加新识别的变量时,原始eLOS与新eLOS之间存在显著差异(P < 0.001)。在192份患者病历中,89.5%至少有一个新变量导致eLOS,平均有2.60(0,12)个新变量。这导致eLOS平均增加2.869天(-0.160,35.129)。与观察到的LOS相比,新LOS差异有统计学意义(P < 0.001),而原始LOS无统计学意义(P = .5661)。结论:不完整的文档和编码可能会歪曲所提供的患者护理质量和其病例的复杂性。这为临床医生、临床文件改进专家和编码人员提供了改进质量指标和医院排名的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Quality Metrics in Neurosurgery: A Spinal Surgery 3-Year Case Review.

Background and objectives: Despite the known importance of accurate clinical documentation as a companion to quality patient care, this is not often prioritized in practice and leads to a variety of downstream consequences. Inaccurate documentation leads to missed opportunities in full, accurate coding. In turn, it also negatively influences hospital and physician quality ranking, medical center profiling, and revenue captured. The aim of this study is to highlight the opportunity for continuous improvement in clinical documentation and the significance accurate clinical documentation has on outcome measures, such as expected length of stay (eLOS).

Methods: A single-center retrospective chart review took place for patients undergoing spinal surgery from 2019 to 2021. Based on Vizient's diagnosis-related group risk model for eLOS, 192 charts spanning 10 unique diagnosis-related groups were reviewed to identify ICD-10 diagnosis and procedure codes that were not coded or not clearly documented by a physician. A new eLOS for each patient was recalculated with the addition of the newly identified variables and then compared with the original eLOS.

Results: Overall, there was a significant difference between the original eLOS and new eLOS when the newly identified variables were added (P < .001). Of 192 patient charts, 89.5% had at least one new variable contributing to eLOS, with an average of 2.60 (0, 12) new variables. This resulted in an average increase in eLOS of 2.869 days (-0.160, 35.129). Compared with the observed LOS, the new eLOS was significantly different (P < .001), whereas the original LOS was not (P = .5661).

Conclusion: Incomplete documentation and coding can misrepresent the quality of patient care provided and the complexity of their cases. This represents an opportunity for improvement for both the clinicians, clinical documentation improvement specialists, and coders to improve quality metrics and hospital rankings.

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