Parikh Ravi B, Ferrell William J, Li Yang, Chen Jinbo, Bilbrey Larry, Johnson Nicole, White Jenna, Sedhom Ramy, Dickson Natalie R, Schleicher Stephen, Bekelman Justin E, Mudumbi Sandhya
Division of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, Georgia.
Winship Cancer Institute, Atlanta, Georgia.
JAMA Netw Open. 2025 Feb 3;8(2):e2458576. doi: 10.1001/jamanetworkopen.2024.58576.
Among patients with advanced solid malignant tumors, early specialty palliative care (PC) is guideline recommended, but strategies to increase PC access and effectiveness in community oncology are lacking.
To test whether algorithm-based defaults with opting out and accountable justification embedded in the electronic health record (EHR) increase completed PC visits.
DESIGN, SETTING, AND PARTICIPANTS: This 2-arm cluster randomized clinical trial was conducted from November 1, 2022, to December 31, 2023. Eligible patients from 15 urban or rural clinics within a large community oncology network in Tennessee had advanced lung or noncolorectal gastrointestinal cancer and were identified by an automated EHR algorithm adapted from national guidelines. Data were analyzed between November 1, 2023, and March 4, 2024.
At sites randomized to control, clinicians received weekly reports detailing PC referral rates compared with peer clinicians (peer comparison) and referred patients to PC at their discretion. At sites randomized to intervention, clinicians also received default PC orders using the EHR. Clinicians who opted out of PC consultation were asked to provide justification (accountable justification). If clinicians did not opt out, a study coordinator contacted patients to introduce and schedule PC visits using a standardized, predefined script.
The primary outcome was a completed PC consultation within 12 weeks of enrollment. Exploratory outcomes included quality of life, feeling heard and understood, and intensive end-of-life care. Outcomes were analyzed using clustered generalized linear and logistic regression models.
The trial enrolled 562 patients (mean [SD] age, 68.5 [10.1] years; 288 male [51.2%]), of whom 433 (77.0%) had lung cancer. There were 130 of 296 patients (43.9%) randomized to the intervention group and 22 of 266 (8.3%) randomized to the control group who completed PC visits (adjusted odds ratio, 8.9 [95% CI, 5.5-14.6]; P < .001). Among 179 patients who died at the 24-week follow-up, 6 of 92 (6.5%) in the intervention group compared with 14 of 87 (16.1%) in the control group received systemic therapy within 14 days of death (adjusted odds ratio, 0.3 [95% CI, 0.1-0.7]; P = .05). There were no differences in quality of life, feeling heard and understood, or late hospice referral.
In this randomized clinical trial of algorithm-based EHR defaults, the intervention increased PC consultations and decreased end-of-life systemic therapy. The intervention provides a scalable implementation strategy to increase specialty PC referrals in the community oncology setting.
ClinicalTrials.gov Identifier: NCT05590962.
在晚期实体恶性肿瘤患者中，早期专科姑息治疗（PC）是指南推荐的，但在社区肿瘤学中增加获得PC服务的机会和提高其有效性的策略尚缺乏。
测试电子健康记录（EHR）中基于算法的默认选择退出和可问责理由是否能增加完成的PC就诊次数。
设计、设置和参与者：这项双臂整群随机临床试验于2022年11月1日至2023年12月31日进行。田纳西州一个大型社区肿瘤学网络中15个城市或农村诊所的符合条件的患者患有晚期肺癌或非结直肠癌性胃肠道癌，通过根据国家指南改编的自动化EHR算法识别。数据于2023年11月1日至2024年3月4日进行分析。
在随机分配到对照组的地点，临床医生每周收到详细的PC转诊率报告，并与同行临床医生进行比较（同行比较），并自行决定将患者转诊至PC。在随机分配到干预组的地点，临床医生还使用EHR接收默认的PC医嘱。选择不进行PC咨询的临床医生被要求提供理由（可问责理由）。如果临床医生没有选择退出，研究协调员会联系患者，使用标准化的预定义脚本介绍并安排PC就诊。
主要结局是在入组后12周内完成PC咨询。探索性结局包括生活质量、感到被倾听和理解以及强化临终关怀。使用整群广义线性和逻辑回归模型分析结局。
该试验招募了562名患者（平均[标准差]年龄，68.5[10.1]岁；288名男性[51.2%]），其中433名（77.0%）患有肺癌。随机分配到干预组的296名患者中有130名（43.9%）完成了PC就诊，随机分配到对照组的266名患者中有22名（8.3%）完成了PC就诊（调整后的优势比，8.9[95%CI，5.5-14.6]；P < .001）。在24周随访时死亡的179名患者中，干预组92名中有6名（6.5%）在死亡前14天内接受了全身治疗，而对照组87名中有14名（16.1%）接受了全身治疗（调整后的优势比，0.3[95%CI，0.1-0.7]；P = .05）。在生活质量、感到被倾听和理解或晚期临终关怀转诊方面没有差异。
在这项基于算法的EHR默认设置的随机临床试验中，干预措施增加了PC咨询次数并减少了临终全身治疗。该干预措施提供了一种可扩展的实施策略以增加社区肿瘤学环境中专科PC转诊。
ClinicalTrials.gov标识符：NCT05590962。
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