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病理学驱动的自动化,以改善结肠镜检查后电子健康记录中记录的随访建议的更新。

Pathology-Driven Automation to Improve Updating Documented Follow-Up Recommendations in the Electronic Health Record After Colonoscopy.

作者信息

Stevens Elizabeth R, Nagler Arielle, Monina Casey, Kwon JaeEun, Olesen Wickline Amanda, Kalkut Gary, Ranson David, Gross Seth A, Shaukat Aasma, Szerencsy Adam

机构信息

Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA.

Department of Health Informatics, NYU Langone Health, New York, New York, USA.

出版信息

Clin Transl Gastroenterol. 2024 Dec 1;15(12):e00785. doi: 10.14309/ctg.0000000000000785.

Abstract

INTRODUCTION

Failure to document colonoscopy follow-up needs postpolypectomy can lead to delayed detection of colorectal cancer (CRC). Automating the update of a unified follow-up date in the electronic health record (EHR) may increase the number of patients with guideline-concordant CRC follow-up screening.

METHODS

Prospective pre-post design study of an automated rules engine-based tool using colonoscopy pathology results to automate updates to documented CRC screening due dates was performed as an operational initiative, deployed enterprise-wide May 2023. Participants were aged 45-75 years who received a colonoscopy November 2022 to November 2023. Primary outcome measure is rate of updates to screening due dates and proportion with recommended follow-up < 10 years. Multivariable log-binomial regression was performed (relative risk, 95% confidence intervals).

RESULTS

Study population included 9,824 standard care and 19,340 intervention patients. Patients had a mean age of 58.6 ± 8.6 years and were 53.4% female, 69.6% non-Hispanic White, 13.5% non-Hispanic Black, 6.5% Asian, and 4.6% Hispanic. Postintervention, 46.7% of follow-up recommendations were updated by the rules engine. The proportion of patients with a 10-year default follow-up frequency significantly decreased (88.7%-42.8%, P < 0.001). The mean follow-up frequency decreased by 1.9 years (9.3-7.4 years, P < 0.001). Overall likelihood of an updated follow-up date significantly increased (relative risk 5.62, 95% confidence intervals: 5.30-5.95, P < 0.001).

DISCUSSION

An automated rules engine-based tool has the potential to increase the accuracy of colonoscopy follow-up dates recorded in patient EHR. The results emphasize the opportunity for more automated and integrated solutions for updating and maintaining EHR health maintenance activities.

摘要

引言

未能记录结肠镜检查息肉切除术后的随访需求可能导致结直肠癌(CRC)的检测延迟。在电子健康记录(EHR)中自动更新统一的随访日期可能会增加接受符合指南的CRC随访筛查的患者数量。

方法

作为一项运营举措,于2023年5月在全企业范围内部署了一项基于自动化规则引擎的工具的前瞻性前后设计研究,该工具使用结肠镜检查病理结果自动更新记录的CRC筛查到期日期。参与者年龄在45 - 75岁之间,于2022年11月至2023年11月接受了结肠镜检查。主要结局指标是筛查到期日期的更新率以及随访建议<10年的比例。进行了多变量对数二项回归分析(相对风险,95%置信区间)。

结果

研究人群包括9824名接受标准护理的患者和19340名干预组患者。患者的平均年龄为58.6±8.6岁,女性占53.4%,非西班牙裔白人占69.6%,非西班牙裔黑人占13.5%,亚洲人占6.5%,西班牙裔占4.6%。干预后,46.7%的随访建议由规则引擎进行了更新。默认随访频率为10年的患者比例显著下降(88.7% - 42.8%,P < 0.001)。平均随访频率下降了1.9年(9.3 - 7.4年,P < 0.001)。随访日期更新的总体可能性显著增加(相对风险5.62,95%置信区间:5.30 - 5.95,P < 0.001)。

讨论

基于自动化规则引擎的工具有可能提高患者EHR中记录的结肠镜检查随访日期的准确性。研究结果强调了采用更多自动化和集成解决方案来更新和维护EHR健康维护活动的机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ff5/11671091/5dcd77979738/ct9-15-e00785-g001.jpg

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