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自动化与半自动实验室值提取在 VA 心脏手术质量改进计划中的应用。

Automated Versus Semi-Automated Lab Value Extraction for the VA Cardiac Surgical Quality Improvement Program.

机构信息

Veterans Affairs Health Services Research, Development Center for Innovation to Implementation, Palo Alto Veterans Affairs Health Care System, Palo Alto, California; Department of Surgery, Stanford University, Palo Alto, California.

Veterans Affairs Health Services Research, Development Center for Innovation to Implementation, Palo Alto Veterans Affairs Health Care System, Palo Alto, California.

出版信息

J Surg Res. 2024 Oct;302:47-52. doi: 10.1016/j.jss.2024.07.010. Epub 2024 Jul 30.

Abstract

INTRODUCTION

The Veterans Affairs Surgical Quality Improvement Program (VASQIP) trains surgical quality nurses (SQNs) at each Veterans Affairs (VA) hospital to extract or verify 187 variables from the medical record for all cardiac surgical cases. For ten preoperative laboratory values, VASQIP has a semiautomated (SA) system in which local lab values are automatically extracted, verified by SQNs, and lab values recorded at other VA facilities are manually extracted. The objective of this study was to develop and validate a method to automate the extraction of these ten preoperative laboratory values and compare results with the current SA method.

MATERIALS AND METHODS

We developed methods to extract ten preoperative laboratory values and measurement dates from the VA Corporate Data Warehouse using Logical Observation Identifiers Names and Codes. Automated (A) versus SA information extraction was compared in terms of agreement, conformance to data definitions, proximity to surgery, and missingness.

RESULTS

For surgeries with both A and SA lab values, the intraclass correlation coefficients for the ten variables ranged from 0.90 to 0.98. For several variables, the A method resulted in much lower rates of missing data (e.g., 2.4% versus 22.5% missing data for high-density lipoprotein) and eliminated out-of-date-range entries.

CONCLUSIONS

Although SQN-extracted data are widely considered the gold standard within National Surgical Quality Improvement Programs, there may be advantages to fully automating extraction of lab values, including high congruence with SA SQN-extracted or verified values and lower rates of missingness and out-of-date-range data.

摘要

简介

退伍军人事务部手术质量改进计划(VASQIP)培训退伍军人事务部(VA)每家医院的外科质量护士(SQN),从所有心脏外科病例的病历中提取或验证 187 个变量。对于十个术前实验室值,VASQIP 有一个半自动(SA)系统,其中本地实验室值自动提取,由 SQN 验证,并手动提取在其他 VA 设施记录的实验室值。本研究的目的是开发和验证一种自动提取这十个术前实验室值的方法,并将结果与当前的 SA 方法进行比较。

材料与方法

我们使用逻辑观察标识符名称和代码,开发了从 VA 公司数据仓库中提取十个术前实验室值和测量日期的方法。比较了自动(A)与 SA 信息提取在一致性、数据定义一致性、手术临近性和缺失性方面的差异。

结果

对于同时具有 A 和 SA 实验室值的手术,十个变量的组内相关系数范围为 0.90 至 0.98。对于几个变量,A 方法导致的缺失数据率要低得多(例如,高密度脂蛋白的缺失数据率为 2.4%,而不是 22.5%),并且消除了过时范围的条目。

结论

尽管 SQN 提取的数据被广泛认为是国家手术质量改进计划中的黄金标准,但完全自动化实验室值的提取可能具有优势,包括与 SA SQN 提取或验证值高度一致,以及更低的缺失率和过时范围数据。

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