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Patient-reported satisfaction with care and care coordination: Results from an online survey conducted in Manitoba, Canada during the COVID-19 pandemic.

2022· article· en· W4298139105 on OpenAlexaffabout
Maclean Thiessen, Kathleen Decker, Jason Park, Andrea Soriano

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsCancerCare ManitobaUniversity of Manitoba
Fundersnot available
KeywordsMedicineFamily medicinePatient satisfactionHealth careTest (biology)Post-hoc analysisDemographyPandemicDiseaseCoronavirus disease 2019 (COVID-19)NursingInternal medicine

Abstract

fetched live from OpenAlex

258 Background: In Manitoba, Canada, changes to cancer care delivery implemented in response to the COVID19 pandemic included, but were not limited to, restrictions on informal caregiver accompaniment for ambulatory care appointments and implementation of physician care administered over the telephone. These changes were predicted to negatively impact the patient experience, specifically patient satisfaction with care and perceived care coordination. To assess this, a survey of patients on active treatment was conducted. Methods: After ethics approval, a SurveyMonkey survey was conducted of cancer patients receiving radiation and IV treatment at one of the 24 cancer treatment sites across Manitoba. The survey collected demographics, disease characteristics, functional status and responses to validated questionnaires addressing satisfaction with care (PSCC), and care coordination (CCQP, including communication (CCQPcomm) and navigation (CCQPnav) subscales). Mean differences of PSCC and CCQP scores (including subscales) were compared using t-test for dichotomous patient characteristics and ANOVA followed by post-hoc pairwise t-tests for non-dichotomous categorical patient characteristics with statistically significant ANOVA results. Results: Between July 2020 and February 2022, 203 responses were collected. The 154 respondents with complete responses for either PSCC, CCQP or both were included in this analysis. Median age of respondents was 64.6 (SD = 11.7). Sex was balanced (male = 47%, female = 52.3%, other/prefer not to say = 0.7%). Breast (26.1%), hematological (13.7%), and prostate (13.1%) cancers were the most common. PSCC and CCQP scores did not differ by marital status, treatment site, disease type, or treatment intent (i.e., curative versus non-curative). Individuals with lower functional status (i.e., ECOG > 1) were identified to have lower mean scores for CCQP and CCQPcomm. Patients < 59 years had lower mean PSCC scores compared to those 59 – 69, and 70+. See Table for comparison of CCPQ and PSCC scores by age and functional status. Conclusions: Young patients and those with decreased functional status were identified to have statistically significant lower mean scores for PREMs reflecting satisfaction and coordination of care. Further work to identify meaningful strategies to improve the patient experience for these two patient groups is needed.[Table: see text]

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)0.004
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 score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.401
GPT teacher head0.523
Teacher spread0.123 · 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
Published2022
Admission routes2
Has abstractyes

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