MétaCan
Menu
← Back to cohort

Assessing overall patient satisfaction among cancer patients: A radiotherapy survey.

2020· article· en· W3029325922 on OpenAlexaff
Joanne Meng, Elisabeth Cisa-Paré, Katelyn Balchin, Julie Renaud, Linda Bunch, Paul Wheatley‐Price, Angela McNeil, S. Murray, Rajiv Samant

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineFamily medicineRespondentFeelingPatient satisfactionRadiation therapyCancerHealth careLung cancerHonestyKindnessNursingSurgeryInternal medicine

Abstract

fetched live from OpenAlex

e19249 Background: Healthcare providers (HCPs) strive to maximize the experience for cancer patients. Published reports suggest a variety of characteristics that are considered important. We decided to survey our patients undergoing radiotherapy to determine what they considered desirable traits and characteristics. Methods: An ethics approved 35-item patient satisfaction survey evaluating respondent experience was developed by an interdisciplinary team of HCPs working in the radiation medicine program. It was an anonymous, voluntary, paper-based survey for self-completion. It evaluated a variety of domains with respect to the quality of care patients received, and was administered to patients undergoing radiotherapy. Results: A total of 199 patients completed the survey. The median age was 68, with approximately 54% women and 45% men (1% unreported). Most patients (85%) had been diagnosed with their cancer within the previous year, and the commonly reported malignancies (61%) were breast, prostate and lung cancers. Almost all (95%) “agreed" or "strongly agreed" about the importance of physicians being sensitive and compassionate. Over 90% felt they received adequate explanations about their treatment, and had their questions answered. The vast majority (93%) felt included in the decision-making process. They reported the 5 most important qualities among the HCPs as follows (in descending order): knowledge, kindness, honesty (answering questions/giving information), good communicator and cheerful attitude. Most (>70%) reported feeling connected with their HCPs. Although overall satisfaction was high, there were areas for improvement identified. These included patients being offered future appointments to discuss their diagnosis and treatment, receiving information about clinical trials and other treatment options, and being given contact information for psychosocial and community resources. Also, HCPs tended to focus mainly on the physical needs of patients and to a lesser degree on their emotional needs, but spiritual and cultural needs were not routinely addressed (<10%). Conclusions: Reassuringly, cancer patients receiving radiation report high rates of satisfaction across many aspects of their care. The qualities most appreciated serve as a reminder to clinicians that their role is more than just that of a medical expert. These findings also reinforce the different aspects of holistic care that can be improved.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.549
GPT teacher head0.600
Teacher spread0.052 · 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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical Oncology→Same topicPatient-Provider Communication in Healthcare→French-language works237,207→