Abstract

Objective

Determination of appropriate endoscopy sedation strategy is an important preprocedural consideration. To address manual workflow gaps that lead to sedation-type order errors at our institution, we designed and implemented a clinical decision support system (CDSS) to review orders for patients undergoing outpatient endoscopy.

Materials and Methods

The CDSS was developed and implemented by an expert panel using an agile approach. The CDSS queried patient-specific historical endoscopy records and applied expert consensus-derived logic and natural language processing to identify possible sedation order errors for human review. A retrospective analysis was conducted to evaluate impact, comparing 4-month pre-pilot and 12-month pilot periods.

Results

22 755 endoscopy cases were included (pre-pilot 6434 cases, pilot 16 321 cases). The CDSS decreased the sedation-type order error rate on day of endoscopy (pre-pilot 0.39%, pilot 0.037%, Odds Ratio = 0.094, P-value < 1e-8). There was no difference in background prevalence of erroneous orders (pre-pilot 0.39%, pilot 0.34%, P = .54).

Discussion

At our institution, low prevalence and high volume of cases prevented routine manual review to verify sedation order appropriateness. Using a cohort-enrichment strategy, a CDSS was able to reduce number of chart reviews needed per sedation-order error from 296.7 to 3.5, allowing for integration into the existing workflow to intercept rare but important ordering errors.

Conclusion

A workflow-integrated CDSS with expert consensus-derived logic rules and natural language processing significantly reduced endoscopy sedation-type order errors on day of endoscopy at our institution.

中文翻译：

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临床决策支持系统，使用专家共识衍生逻辑和自然语言处理，减少内窥镜检查患者的镇静类订单错误

摘要

客观的

确定合适的内窥镜镇静策略是一个重要的术前考虑因素。为了解决导致我们机构镇静类订单错误的手动工作流程差距，我们设计并实施了一个临床决策支持系统 (CDSS) 来审查接受门诊内窥镜检查的患者的订单。

材料和方法

CDSS 由专家小组使用敏捷方法开发和实施。CDSS 查询患者特定的历史内窥镜检查记录，并应用专家共识衍生的逻辑和自然语言处理来识别可能的镇静命令错误以供人工审查。进行了回顾性分析以评估影响，比较了 4 个月的试点前和 12 个月的试点期。

结果

共纳入22755例内窥镜病例（预试验6434例，试验16321例）。CDSS 降低了内窥镜检查当天的镇静类命令错误率（预试验 0.39%，试验 0.037%，优势比 = 0.094，P值 < 1e-8）。错误订单的背景流行率没有差异（试点前 0.39%，试点 0.34%，P  = .54）。

讨论

在我们的机构，低流行率和大量病例阻止了常规人工审查以验证镇静令的适当性。使用队列浓缩策略，CDSS 能够将每个镇静订单错误所需的图表审查数量从 296.7 减少到 3.5，从而允许集成到现有工作流程中以拦截罕见但重要的订单错误。

结论

工作流集成 CDSS 与专家共识派生的逻辑规则和自然语言处理显着减少了我们机构内窥镜检查当天的内窥镜镇静类型订单错误。