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Baseline practice-level financial screening processes and resources among Children’s Oncology Group National Cancer Institute Community Oncology Research Programs (NCORP).

2024· article· en· W4402986678 on OpenAlexaff
Melissa Beauchemin, Sheila Judge Santacroce, Olivia Ponce, Lingyun Ji, Subhash Ramakrishnan, Kira Bona, Yudy Muneton Castano, Joanna Robles, Kamala Allen, Lillian Sung, Susan K. Parsons

Bibliographic record

VenueJCO Oncology Practice · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsBaseline (sea)Internal medicineMedicineOncologyClinical OncologyCancerFamily medicinePolitical science

Abstract

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34 Background: Financial toxicity is an increasingly recognized and prevalent adverse effect during cancer treatment. Systematic financial screening is recommended for families of children with cancer, and emerging data support the importance of system-level support and interventions to mitigate financial toxicity. Financial distress is a key, measurable domain of financial toxicity. Methods: To inform interventions for pediatric oncology settings, we are conducting ACCL20N1CD, a Children’s Oncology Group (COG) prospective, multilevel observational study among NCORP practices in the US, to determine the risk and trajectory for financial distress in guardians of children with newly diagnosed acute lymphoblastic leukemia. We analyzed baseline survey data from COG NCORP practices that enrolled at least one parent. Data were collected via REDCap following the practice’s first parent enrollment. We describe practice participation patterns, current approaches to financial screening, and available resources to address identified needs including navigation. Results: Of 50 eligible COG NCORP practices, 40 (80%) activated the study, and 28 (56%) enrolled at least 1 participant and thus, completed the survey. Most (61%) of these practices treated 50-99 new pediatric oncology patients annually; 10 (36%) enrolled at least 5 participants in ACCL20N1CD. Twenty (71%) reported that their practice routinely conducted financial screening in addition to insurance assessment; 15 (75%) of these 20 practices conducted financial screening at more than one timepoint. Social workers were primarily responsible for screening (16/20; 80%). Only three practices (3/28; 11%) used a standardized financial screening tool. Most practices had access to a private foundation/organization (25/28, 89%), institutional support (23/28, 82%), or local referrals to organizations (22/28, 78%) that provided financial support for patients/families. Fewer practices had patient navigators (9/28, 32%), financial navigators (8/28, 28%), or legal advocates (3/28, 11%) available to assist families. Conclusions: Though most COG practices treating children of parents enrolled in 20N1CD conduct financial screening, processes are not standardized, and resources available to address identified needs and potentially mitigate financial toxicity vary. Further, these data represent enrolling sites which may overestimate screening practices within COG NCORP practices. Variations in financial screening procedures and lack of individual-level resources to facilitate screening may impact delivery of equitable high-quality cancer care across NCORP COG practices. Clinical trial information: NCT04928599 .

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.005
Open science0.0010.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.203
GPT teacher head0.417
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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