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首页> 外文期刊>Patient Safety in Surgery >Refining the predictive variables in the “Surgical Risk Preoperative Assessment System” (SURPAS): a descriptive analysis
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Refining the predictive variables in the “Surgical Risk Preoperative Assessment System” (SURPAS): a descriptive analysis

机译：完善“手术风险术前评估系统”（SURPAS）中的预测变量：描述性分析

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The Surgical Risk Preoperative Assessment System (SURPAS) is a parsimonious set of models providing accurate preoperative prediction of common adverse outcomes for individual patients. However, focus groups with surgeons and patients have developed a list of questions about and recommendations for how to further improve SURPAS’s usability and usefulness. Eight issues were systematically evaluated to improve SURPAS. The eight issues were divided into three groups: concerns to be addressed through further analysis of the database; addition of features to the SURPAS tool; and the collection of additional outcomes. Standard multiple logistic regression analysis was performed using the 2005–2015 American College of Surgeons National Surgical Quality Improvement Participant Use File (ACS NSQIP PUF) to refine models: substitution of the preoperative sepsis variable with a procedure-related risk variable; testing of an indicator variable for multiple concurrent procedure codes in complex operations; and addition of outcomes to increase clinical applicability. Automated risk documentation in the electronic health record and a patient handout and supporting documentation were developed. Long term functional outcomes were considered. Model discrimination and calibration improved when preoperative sepsis was replaced with a procedure-related risk variable. Addition of an indicator variable for multiple concurrent procedures did not significantly improve the models. Models were developed for a revised set of eleven adverse postoperative outcomes that separated bleeding/transfusion from the cardiac outcomes, UTI from the other infection outcomes, and added a predictive model for unplanned readmission. Automated documentation of risk assessment in the electronic health record, visual displays of risk for providers and patients and an “About” section describing the development of the tool were developed and implemented. Long term functional outcomes were considered to be beyond the scope of the current SURPAS tool. Refinements to SURPAS were successful in improving the accuracy of the models, while reducing manual entry to five of the eight variables. Adding a predictor variable to indicate a complex operation with multiple current procedure codes did not improve the accuracy of the models. We developed graphical displays of risk for providers and patients, including a take-home handout and automated documentation of risk in the electronic health record. These improvements should facilitate easier implementation of SURPAS.
机译：手术风险术前评估系统（SURPAS）是一组简化的模型，可为各个患者提供术前常见不良后果的准确预测。但是，由外科医生和患者组成的焦点小组已经就如何进一步改善SURPAS的可用性和实用性提出了一系列问题和建议。系统地评估了八个问题以改善SURPAS。八个问题分为三类：将通过进一步分析数据库解决的问题;向SURPAS工具添加功能;并收集其他结果。使用2005-2015年美国外科医生学会国家外科手术质量改善参与者使用文件（ACS NSQIP PUF）进行标准的多元logistic回归分析，以完善模型：术前败血症变量替换为与手术相关的风险变量;在复杂操作中测试用于多个并发过程代码的指标变量;以及增加结果以增加临床适用性。开发了电子健康记录中的自动化风险文档以及患者手册和支持文档。考虑了长期功能结局。当术前败血症被手术相关的风险变量所取代时，模型识别和校准得到改善。为多个并发过程添加指标变量并不能显着改善模型。针对十一项不利的术后预后结果修订版开发了模型，这些预后结果将出血/输血与心脏预后分开，将UTI与其他感染预后分开，并增加了计划外再次入院的预测模型。开发并实施了电子健康记录中风险评估的自动文档，提供者和患者的风险可视化显示以及描述工具开发的“关于”部分。长期功能性结果被认为超出了当前SURPAS工具的范围。对SURPAS的改进成功地提高了模型的准确性，同时将手动输入减少到八个变量中的五个。添加预测变量以指示具有多个当前过程代码的复杂操作不会提高模型的准确性。我们开发了针对提供者和患者的风险图形显示，包括带回家的讲义和电子健康记录中的风险自动记录。这些改进应有助于简化SURPAS的实施。

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