In:
PLOS ONE, Public Library of Science (PLoS), Vol. 17, No. 5 ( 2022-5-27), p. e0267012-
Abstract:
While health systems have implemented multifaceted interventions to improve physician and patient communication in serious illnesses such as cancer, clinicians vary in their response to these initiatives. In this secondary analysis of a randomized trial, we identified phenotypes of oncology clinicians based on practice pattern and demographic data, then evaluated associations between such phenotypes and response to a machine learning (ML)-based intervention to prompt earlier advance care planning (ACP) for patients with cancer. Methods and findings Between June and November 2019, we conducted a pragmatic randomized controlled trial testing the impact of text message prompts to 78 oncology clinicians at 9 oncology practices to perform ACP conversations among patients with cancer at high risk of 180-day mortality, identified using a ML prognostic algorithm. All practices began in the pre-intervention group, which received weekly emails about ACP performance only; practices were sequentially randomized to receive the intervention at 4-week intervals in a stepped-wedge design. We used latent profile analysis (LPA) to identify oncologist phenotypes based on 11 baseline demographic and practice pattern variables identified using EHR and internal administrative sources. Difference-in-differences analyses assessed associations between oncologist phenotype and the outcome of change in ACP conversation rate, before and during the intervention period. Primary analyses were adjusted for patients’ sex, age, race, insurance status, marital status, and Charlson comorbidity index. The sample consisted of 2695 patients with a mean age of 64.9 years, of whom 72% were White, 20% were Black, and 52% were male. 78 oncology clinicians (42 oncologists, 36 advanced practice providers) were included. Three oncologist phenotypes were identified: Class 1 (n = 9) composed primarily of high-volume generalist oncologists, Class 2 (n = 5) comprised primarily of low-volume specialist oncologists; and 3) Class 3 (n = 28), composed primarily of high-volume specialist oncologists. Compared with class 1 and class 3, class 2 had lower mean clinic days per week (1.6 vs 2.5 [class 3] vs 4.4 [class 1] ) a higher percentage of new patients per week (35% vs 21% vs 18%), higher baseline ACP rates (3.9% vs 1.6% vs 0.8%), and lower baseline rates of chemotherapy within 14 days of death (1.4% vs 6.5% vs 7.1%). Overall, ACP rates were 3.6% in the pre-intervention wedges and 15.2% in intervention wedges (11.6 percentage-point difference). Compared to class 3, oncologists in class 1 (adjusted percentage-point difference-in-differences 3.6, 95% CI 1.0 to 6.1, p = 0.006) and class 2 (adjusted percentage-point difference-in-differences 12.3, 95% confidence interval [CI] 4.3 to 20.3, p = 0.003) had greater response to the intervention. Conclusions Patient volume and time availability may be associated with oncologists’ response to interventions to increase ACP. Future interventions to prompt ACP should prioritize making time available for such conversations between oncologists and their patients.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0267012
DOI:
10.1371/journal.pone.0267012.g001
DOI:
10.1371/journal.pone.0267012.g002
DOI:
10.1371/journal.pone.0267012.t001
DOI:
10.1371/journal.pone.0267012.t002
DOI:
10.1371/journal.pone.0267012.s001
DOI:
10.1371/journal.pone.0267012.s002
DOI:
10.1371/journal.pone.0267012.s003
DOI:
10.1371/journal.pone.0267012.s004
DOI:
10.1371/journal.pone.0267012.s005
DOI:
10.1371/journal.pone.0267012.s006
DOI:
10.1371/journal.pone.0267012.s007
DOI:
10.1371/journal.pone.0267012.s008
DOI:
10.1371/journal.pone.0267012.s009
DOI:
10.1371/journal.pone.0267012.r001
DOI:
10.1371/journal.pone.0267012.r002
DOI:
10.1371/journal.pone.0267012.r003
DOI:
10.1371/journal.pone.0267012.r004
DOI:
10.1371/journal.pone.0267012.r005
DOI:
10.1371/journal.pone.0267012.r006
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2267670-3
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