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一种用于脊柱手术手术指征和手术特征分类的管理编码算法的验证

Validation of an administrative coding algorithm for classifying surgical indication and operative features of spine surgery.

作者信息

Kazberouk Alexander, Martin Brook I, Stevens Jennifer P, McGuire Kevin J

机构信息

*Harvard Medical School, Boston, MA †Department of Orthopaedic Surgery, Geisel School of Medicine at Dartmouth, Dartmouth-Hitchcock Medical Center, Lebanon, NH ‡Center for Healthcare Delivery Science, Pulmonary and Critical Care, Beth Israel Deaconess Medical Center, Boston, MA; and §Department of Orthopedic Surgery, Center for Health Care Delivery Science, Beth Israel Deaconess Medical Center, Boston, MA.

出版信息

Spine (Phila Pa 1976). 2015 Jan 15;40(2):114-20. doi: 10.1097/BRS.0000000000000682.

Abstract

STUDY DESIGN

Retrospective review of medical records and administrative data.

OBJECTIVE

Validate a claims-based algorithm for classifying surgical indication and operative features in lumbar surgery.

SUMMARY OF BACKGROUND DATA

Administrative data are valuable to study rates, safety, outcomes, and costs in spine surgery. Previous research evaluates outcomes by procedure, not indications and operative features. One previous study validated a coding algorithm for classifying surgical indication. Few studies examined claims data for classifying patients by operative features.

METHODS

Patients undergoing lumbar decompression or fusion at a single institution in 2009 for back pain, herniated disc, stenosis, spondylolisthesis, or scoliosis were included. Sensitivity and specificity of a claims-based algorithm for indication and operative features were examined versus medical record abstraction.

RESULTS

A total of 477 patients, including 246 (52%) undergoing fusion and 231 (48%) undergoing decompression were included in this study. Sensitivity of the claims-based coding algorithm for classifying the indication for the procedure was 71.9% for degenerative disc disease, 81.9% for disc herniation, 32.7% for spinal stenosis, 90.4% for degenerative spondylolisthesis, and 93.8% for scoliosis. Specificity was 87.9% for degenerative disc, 85.6% for disc herniation, 90.7% for spinal stenosis, 95.0% for degenerative spondylolisthesis, and 97.3% for scoliosis. Sensitivity and specificity of claims data for identifying the type of procedure for fusion cases was 97.6% and 99.1%, respectively. Sensitivity of claims data for characterizing key operative features was 81.7%, 96.4%, and 53.0% for use of instrumentation, combined (anterior and posterior) surgical approach, and 3 or more disc levels fused, respectively. Specificity was 57.1% for instrumentation, 94.5% for combined approaches, and 71.9% for 3 or more disc levels fused.

CONCLUSION

Claims data accurately reflected certain diagnoses and type of procedures, but were less accurate at characterizing operative features other than the surgical approach. This study highlights both the potential and current limitations of claims-based analysis for spine surgery.

摘要

研究设计

对病历和管理数据进行回顾性分析。

目的

验证一种基于索赔的算法,用于对腰椎手术的手术指征和手术特征进行分类。

背景数据总结

管理数据对于研究脊柱手术的发生率、安全性、结局和成本很有价值。以往的研究按手术方式评估结局,而非手术指征和手术特征。此前有一项研究验证了一种用于对手术指征进行分类的编码算法。很少有研究通过手术特征对索赔数据进行分析以对患者进行分类。

方法

纳入2009年在一家机构因背痛、椎间盘突出、椎管狭窄、椎体滑脱或脊柱侧弯接受腰椎减压或融合手术的患者。将基于索赔的算法用于指征和手术特征的敏感度和特异度与病历摘要进行对比研究。

结果

本研究共纳入477例患者,其中246例(52%)接受融合手术,231例(48%)接受减压手术。基于索赔的编码算法对手术指征进行分类的敏感度分别为:退变性椎间盘疾病71.9%、椎间盘突出81.9%、椎管狭窄32.7%、退变性椎体滑脱90.4%、脊柱侧弯93.8%。特异度分别为:退变性椎间盘87.9%、椎间盘突出85.6%、椎管狭窄90.7%、退变性椎体滑脱95.0%及脊柱侧弯97.3%。索赔数据对融合病例手术方式类型的识别敏感度和特异度分别为97.6%和99.1%。索赔数据对关键手术特征的特征化敏感度分别为:使用内固定器械81.7%、联合(前后路)手术入路96.4%、融合3个或更多椎间盘节段53.0%。特异度分别为:使用内固定器械57.1%、联合手术入路94.5%、融合3个或更多椎间盘节段71.9%。

结论

索赔数据能准确反映某些诊断和手术方式,但在描述除手术入路以外的手术特征方面准确性较差。本研究凸显了基于索赔分析在脊柱手术中的潜力和当前局限性。

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