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Experience and outcomes of the Acute Leukemia Shared-Care Program.

2018· article· en· W2893322250 on OpenAlexaffabout
Amanda Wong, Audrey Wong, Cassandra McKay, Bryan Maguire, Mindaugas Mozuraitis, Jonathan Wang, Kim Maki, Sherrie Hertz, C. Tom Kouroukis, Judy Costello

Bibliographic record

VenueJournal of Clinical Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsUniversity Health NetworkJuravinski Cancer CentreCancer Care Ontario
Fundersnot available
KeywordsMedicineRetrospective cohort studyIntervention (counseling)Patient satisfactionHealth carePatient experienceFamily medicineEmergency medicineNursingInternal medicine

Abstract

fetched live from OpenAlex

184 Background: Acute leukemia (AL) is a rapidly progressive disease requiring timely and intensive treatment. Historically, care for approximately 50% of AL patients in Ontario, Canada has been centralized resulting in significant resource pressures at the specialized center and travel pressures on patients and caregivers. The AL Shared-Care Program was launched in 2014 to enable delivery of appropriate portions of care at an AL Service Site and Partner Cancer Center closer to the patient’s home. Methods: The impact of the Program was evaluated through provider interviews (n = 22) and the Patient Experience Survey which included 20 non-shared-care (control) and 26 shared-care (intervention) patients. A retrospective analysis of 332 control and 70 intervention patients was used to evaluate the Program’s impact on travel, survival outcomes, and resource utilization. Results: Retrospective analysis revealed that an average intervention group patient saved a median round trip travel distance of 115 km [IQR: 88-179] and time of 91 min [IQR: 62-141]. 91% of health care providers reported that the Program provided person-centered care. Patients reported positive experiences with no statistically significant differences between the intervention and control groups in coordination of care (81% vs 90%, p = 0.39), overall care (88% vs 100%, p = 0.12), and experience (85% vs 90%, p = 0.60). There was no statistically significant correlation between patient satisfaction scores and patient-reported health status (r = 0.10, p = 0.51) and state of health (r = 0.03, p = 0.87). There was no significant difference in survival between groups (HR = 0.73, 95% CI [0.49, 1.13], p = 0.16). Finally, system cost estimated based on emergency department visits, admissions for febrile neutropenia, and follow-up clinic visits showed that there was no statistically significant difference in average monthly cost per patient between the intervention and control groups ($943 vs $1,197 respectively, p = 0.48). Conclusions: The AL Shared-Care Program reduced the travel burden for patients and caregivers without negatively impacting provider and patient experience, survival and system costs. Findings of this work will support the expansion of the Program to additional sites.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalmedium
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.112
GPT teacher head0.525
Teacher spread0.414 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2018
Admission routes2
Has abstractyes

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