ArticleNEJM catalyst innovations in care delivery2025
A Text Message Intervention to Minimize the Time Burden of Cancer Care.
Article in NEJM catalyst innovations in care delivery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Feasibility and Acceptability of Automated Texts to Offer, Screen, and Enroll Patients in a Cancer Clinical Trial Financial Reimbursement Program: Mixed Methods Study.JMIR formative research · 2026Article
- Time-Toxicity Indicators and Mitigation Strategies in Cancer Care: A Scoping Review.Journal of multidisciplinary healthcare · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
28 authors.
Funding
Abstract
Patients with cancer spend considerable time commuting to, waiting for, and receiving health care. Patient-reported outcomes have been collected electronically to monitor patients for toxicity related to treatment, but, to the authors' knowledge, they have not been used as a strategy to minimize patients' time spent on cancer care by streamlining care delivery. Researchers at Penn Medicine set an objective to assess the effectiveness and implementation of a text message-based symptom reporting electronic triage (e-triage) versus usual care to minimize the time toxicity associated with ambulatory cancer care. The methods employed included a hybrid type 1 effectiveness-implementation, unblinded, randomized controlled trial and sequential mixed-methods study, which was conducted between December 1, 2021, and December 31, 2022, with a follow-up period of 3 months or three visits (whichever came first, but all within the 2-year window). Adult patients with solid tumors receiving single-agent immune checkpoint inhibitors (ICIs) with access to a text-messaging device were enrolled, with a target sample size of 176. The intervention was a symptom-based e-triage via mobile text messaging combined with routine laboratory testing. Participants in the e-triage group with normal bloodwork and no symptoms of drug toxicity on e-triage were eligible to fast-track to ICI infusion, bypassing the pretreatment office visit. The primary end point was total time per ambulatory encounter; secondary end points included wait time, ED or hospital visits, health-related quality of life, patient satisfaction, and implementation (reach and fidelity). Implementation readiness (acceptability, appropriateness, and feasibility), barriers, and facilitators were evaluated in a mixed-methods analysis among treating oncologists, measured via surveys and focus groups. For the study, 40 patients were randomly assigned, of which 31 were evaluated for the primary end point; the median age among the 40 participants was 67.5 years of age (interquartile range 59.5-71.5 years of age), 80.0% were male, and 84.6% were white. Those randomly assigned to the e-triage group of the pilot randomized controlled trial (n=19, n=16 evaluable) had an average of 66.0 minutes less total time (95% confidence interval [CI], -123.7 to -8.08 minutes;
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.