Using Oncology Treatment Pathway Data to Evaluate Serious Illness Communication, Care Utilization, and End-of-Life Care for Patients With Cancer.

IF 4.7 3区 医学 Q1 ONCOLOGY
Cody E Cotner, Angela C Tramontano, Alex Post, Brian Finn, Saima Awan, Nathaniel Gwynne, Sishemo Mwesigwa, Charlotta Lindvall, James A Tulsky, Joseph O Jacobson, David M Jackman, Alexi A Wright, Christopher R Manz
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Abstract

Purpose: Oncology treatment pathways provide decision support and encourage guideline adherence. Pathway data combined with electronic health record (EHR) data can identify patient populations with poor prognoses, low serious illness conversation (SIC) rates, and high acute care utilization that may benefit from targeted interventions.

Patients and methods: We conducted a retrospective cohort analysis among adults with cancer treated at seven affiliated sites of the Dana-Farber Cancer Institute (DFCI) who had navigations within 21 treatment pathways between July 29, 2019, and March 8, 2023. DFCI clinicians previously identified pathway nodes with an estimated survival less than 1 year, termed poor prognosis (PP) nodes. We combined pathway data with EHR data to calculate the median overall survival (OS) and proportion of patients with SICs, acute care utilization (hospitalizations and emergency department visits), and outpatient palliative care 6 months after treatment node navigation for all, PP, and nonpoor prognosis (nPP) nodes. SICs were identified using the EHR advanced care planning (ACP) tab.

Results: There were 15,261 navigations for 10,203 patients (median age 66 years, 55% female, 85% White). The median OS was 13.8 months for all nodes, 7.8 months for PP nodes, and 21.0 months for nPP nodes. The ACP section of the EHR rate 6 months after navigation was 19.6% for PP nodes versus 11.0% for nPP nodes. There was substantial intragroup variability in OS and SIC rates among all nodes. SICs were recorded in the ACP tab for only 34.3% of decedents. Patients who navigated to PP nodes had higher levels of acute care utilization and palliative care encounters.

Conclusion: Treatment pathway data enabled identification of patient populations with poor prognoses, low SIC rates, and high acute care utilization.

利用肿瘤治疗路径数据评估癌症患者的重病沟通、护理利用和临终关怀。
目的:肿瘤治疗路径可提供决策支持并鼓励遵守指南。路径数据与电子健康记录(EHR)数据相结合,可以识别出预后不良、重病会话(SIC)率低、急症护理使用率高的患者群体,这些患者可能会从有针对性的干预措施中受益:我们对在丹娜法伯癌症研究所(DFCI)七个附属机构接受治疗的成人癌症患者进行了一项回顾性队列分析,这些患者在 2019 年 7 月 29 日至 2023 年 3 月 8 日期间在 21 个治疗路径中进行了导航。DFCI 的临床医生之前确定了估计生存期少于 1 年的路径节点,这些节点被称为预后不良(PP)节点。我们将路径数据与 EHR 数据相结合,计算出所有、PP 和预后不良 (nPP) 节点治疗节点导航 6 个月后的中位总生存期 (OS) 和 SIC 患者比例、急性护理利用率(住院和急诊就诊)以及门诊姑息治疗。使用电子病历高级护理计划(ACP)选项卡确定 SIC:10203名患者共进行了15261次导航(中位年龄66岁,55%为女性,85%为白人)。所有结节的中位 OS 为 13.8 个月,PP 结节为 7.8 个月,nPP 结节为 21.0 个月。导航 6 个月后,EHR 的 ACP 部分比例为 PP 结节 19.6%,nPP 结节 11.0%。所有节点的 OS 和 SIC 率在组内存在很大差异。只有 34.3% 的死者在 ACP 标签中记录了 SIC。导航到 PP 节点的患者使用急症护理和姑息治疗的比例较高:治疗路径数据有助于识别预后不良、SIC率低和急症护理使用率高的患者群体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.40
自引率
7.50%
发文量
518
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