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Patient-reported care satisfaction and symptom burden in hospitalized patients with cancer.

2020· article· en· W3032643077 on OpenAlexaboutno aff
Emilia Kaslow-Zieve, Carolyn L. Qian, Chinenye C. Azoba, Irène Wang, Emily E. Van Seventer, Richard Newcomb, Vicki A. Jackson, David P. Ryan, Joseph A. Greer, Areej El‐Jawahri, Jennifer S. Temel, Ryan David Nipp

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePatient satisfactionCancerDepression (economics)ComorbidityMarital statusHealth careFamily medicineInternal medicinePopulationNursing

Abstract

fetched live from OpenAlex

2013 Background: Hospitalized patients with cancer often experience high symptom burden, which may impact their care satisfaction and use of health care services. Yet, studies describing these patients’ care satisfaction, symptom burden, and health care utilization are lacking. Methods: We prospectively enrolled patients with cancer and unplanned hospitalizations from 9/2014-4/2017. Upon admission, patients self-reported their care satisfaction (FAMCARE items asking about satisfaction regarding speed with which symptoms are treated and coordination of care) and physical (Edmonton Symptom Assessment System [ESAS]) and psychological (Patient Health Questionnaire 4 [PHQ4]) symptom burden. We used regression models to identify patient factors associated with care satisfaction. We also explored associations between patients’ care satisfaction, symptom burden, and hospital length of stay (LOS) in models adjusted for age, sex, marital status, comorbidity score, cancer type, cancer documented as curable/incurable, time since cancer diagnosis, and admission to a dedicated oncology service. Results: We enrolled 1,576 of 1,749 (90.1%) consecutive patients (mean age = 63.19±13.39 years, 46.3% female). Most reported being very satisfied/satisfied with the speed with which symptoms are treated (89.0%) and coordination of care (90.1%). Older age (B = 0.01, P < .02 for both) and admission to a dedicated oncology service (B = 0.20, P < .01 for both) were each independently associated with higher satisfaction with the speed with which symptoms are treated and coordination of care. Higher satisfaction with the speed with which symptoms are treated was associated with lower PHQ4 depression (B = -0.14, P = .01), PHQ4 anxiety (B = -0.11, P < .01), ESAS physical (B = -1.30, P < .01), and ESAS total (B = -2.44, P < .01) symptoms. Higher satisfaction with coordination of care was associated with lower PHQ4 depression (B = -0.14, P = .02), PHQ4 anxiety (B = -0.16, P < .01), ESAS physical (B = -1.30, P < .01), and ESAS total (B = -2.75, P < .01) symptoms. Satisfaction with the speed with which symptoms are treated (B = -0.47, P = .03) and coordination of care (B = -0.50, P = .03) were both associated with shorter hospital LOS. Conclusions: Most hospitalized patients with cancer reported high care satisfaction, which was associated with older age and admission to a dedicated oncology service. We found relationships among higher care satisfaction, lower symptom burden, and shorter hospital LOS, underscoring the importance of efforts to enhance symptom management and care coordination in this population.

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

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)0.002
metaresearch head score (Gemma)0.007
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.044
GPT teacher head0.392
Teacher spread0.348 · 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 source (direct Gemma or distilled Codex), not a consensus.

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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